Patent Grant
12061798
Businesses worldwide recognize the commercial value of their data and seek reliable, cost-effective ways to protect the information stored on their computer networks while minimizing impact on productivity. Protecting information is often part of a routine process that is performed within an organization.
A company might back up critical computing systems such as databases, file servers, web servers, and so on as part of a daily, weekly, or monthly maintenance schedule. The company may similarly protect computing systems used by each of its employees, such as those used by an accounting department, marketing department, engineering department, and so forth.
Given the rapidly expanding volume of data under management, companies also continue to seek innovative techniques for managing data growth, in addition to protecting data. For instance, companies often implement migration techniques for moving data to lower cost storage over time and data reduction techniques for reducing redundant data, pruning lower priority data, etc.
Enterprises also increasingly view their stored data as a valuable asset. Along these lines, customers are looking for solutions that not only protect and manage, but also leverage their data. For instance, solutions providing data analysis capabilities, information management, improved data presentation and access features, and the like, are in increasing demand.
Often, virtual machines (VMs) are backed up so that the VMs can be restored to a previous point in time in the event of data corruption or the like. The backups may be full backups (e.g., all of the data of the VM is backed up) or the backups may be incremental backups (e.g., only the data of the VM that changed since the last backup is backed up). Incremental backups may be useful in that a reduced amount of memory is needed to store a restorable backup. Generally, for incremental backups, to determine the data of the VM that changed since the last backup, the system runs a check, such as a cyclic redundancy check (CRC), on each sector in a virtual hard disk associated with the VM. The CRC may indicate whether data in the respective sector has changed (e.g., the CRC may be based on the data in the sector as of the last backup, and a change in the data in the sector would result in the CRC failing). If the data in the sector has changed, the sector data is included in the incremental backup.
Performing the CRC check may involve performing a read operation on each sector in the virtual hard disk in addition to the actual CRC comparison. Thus, even though an incremental backup may include a subset of all of the data stored in the virtual hard disk, the entire virtual hard disk is still accessed to determine what data to include in the backup. In some cases, these read operations and/or CRC comparisons are more resource intensive than the actual transmission of data to the secondary storage devices. Accordingly, while the incremental backups may reduce memory consumption, the incremental backups may not reduce processor usage or latency and the VM may suffer a performance penalty.
In order to address these and other challenges, an information management system according to certain aspects can implement an incremental VM backup operation that reduces a number of read operations on the virtual hard disk of the VM. For example, the information management system can include a driver residing within the I/O stack of the VM host (e.g., the hypervisor) and generate a block change bitmap file that is stored in conjunction with the virtual hard disk file of the VM. The driver may intercept write operations generated by the VM and store, in the block change bitmap file, an indication of what sector or groups of sectors in the virtual hard disk correspond with the given write operation. Once a policy indicates that a backup is to occur, the information management system may parse the block change bitmap file to identify sectors or groups of sectors in the virtual hard disk that have changed, and the data in the identified sectors or groups of sectors may be included in the backup. Thus, read operations may occur only on the sectors or groups of sectors in which data has changed since the previous backup.
One aspect of the disclosure provides a system configured to backup a virtual machine. The system comprises a client device comprising computer hardware, where the client device includes: a virtual machine (VM) executed by a hypervisor, where the VM comprises a virtual hard disk file and a change block bitmap file, where the virtual hard disk file stores data associated with a virtual hard disk; a driver module under control of the hypervisor, where the driver module is configured to: intercept a first write operation generated by the VM to store data in a first sector, determine an identity of the first sector based on the intercepted write operation, determine an entry in the change block bitmap file that corresponds with the first sector, and modify the entry in the change block bitmap file to indicate that data in the first sector has changed; and a data agent configured to gather data for use in performance of an incremental backup of the VM based on the change block bitmap file in response to an instruction from a storage manager, where the incremental backup comprises the data in the first sector.
The system of the preceding paragraph can have any sub-combination of the following features: where the hypervisor comprises an I/O stack, and where the I/O stack comprises the driver module; where the data agent is further configured to: parse the change block bitmap file, identify each entry in the change block bitmap file that indicates that data in a sector associated with the respective entry has changed, for each identified entry, determine an associated sector and read data from the associated sector in the virtual hard disk file, and for each identified entry, include the read data in the incremental backup; where the driver is further configured to modify the entry in the change block bitmap file from a logical 0 to a logical 1 to indicate that data in the first sector has changed; where the virtual hard disk file and the change block bitmap file are stored in a volume of the VM; where the driver is further configured to: intercept an open operation generated by the VM to open the virtual hard disk file, and begin monitoring the virtual hard disk file in response to intercepting the open operation; where the change block bitmap file is associated with a first period of time; where the driver is further configured to generate a second change block bitmap file associated with a second period of time after the first period of time and store the second change block bitmap file in the VM; where the driver is configured to generate the second change block bitmap file after the data agent performs the incremental backup based on the change block bitmap file; and where the data agent is further configured to gather data for use in performance of a second incremental backup at a time after the incremental backup based on the second change block bitmap file.
Another aspect of the disclosure provides a method of backing up a virtual machine. The method comprises intercepting, by a driver under the control of a hypervisor which executes on a client computing device, a first write operation generated by a virtual machine (VM) to store data in a first sector of a virtual hard disk, where the VM is executed by the hypervisor, wherein the VM comprises a virtual hard disk file and a change block bitmap file, and where the virtual hard disk file stores data associated with the virtual hard disk; and, with the client computing device, determining an identity of the first sector based on the intercepted write operation, determining an entry in the change block bitmap file that corresponds with the first sector, and modifying the entry in the change block bitmap file to indicate that data in the first sector has changed.
The method of the preceding paragraph can have any sub-combination of the following features: where the method further comprises receiving an instruction from a storage manager to begin a backup of the VM and gathering data for use in performance of an incremental backup of the VM based on the change block bitmap file in response to the received instruction, where the incremental backup comprises the data in the first sector; where the method further comprises parsing the change block bitmap file, identifying each entry in the change block bitmap file that indicates that data in a sector associated with the respective entry has changed, for each identified entry, determining an associated sector and read data from the associated sector in the virtual hard disk file, and for each identified entry, including the read data in the incremental backup; where the hypervisor comprises an I/O stack, and wherein the I/O stack comprises the driver module; where the method further comprises modifying the entry in the change block bitmap file from a logical 0 to a logical 1 to indicate that data in the first sector has changed; where the virtual hard disk file and the change block bitmap file are stored in a volume of the VM; where the method further comprises intercepting an open operation generated by the VM to open the virtual hard disk file, and begin monitoring the virtual hard disk file in response to intercepting the open operation; where the change block bitmap file is associated with a first period of time; where the method further comprises generating a second change block bitmap file associated with a second period of time after the first period of time and store the second change block bitmap file in the VM, where the second change block bitmap file is generated after a first incremental backup based on the change block bitmap file is performed; where the method further comprises gathering data for use in performance of a second incremental backup at a time after the first incremental backup based on the second change block bitmap file; and where the driver forms a part of the hypervisor.
For purposes of summarizing the disclosure, certain aspects, advantages and novel features of the inventions have been described herein. It is to be understood that not necessarily all such advantages may be achieved in accordance with any particular embodiment of the invention. Thus, the invention may be embodied or carried out in a manner that achieves or optimizes one advantage or group of advantages as taught herein without necessarily achieving other advantages as may be taught or suggested herein.
Systems and methods are described herein for implementing efficient virtual machine (VM) backup procedures. Examples of such systems and methods are discussed in further detail herein, e.g., with respect to
Information Management System Overview
With the increasing importance of protecting and leveraging data, organizations simply cannot afford to take the risk of losing critical data. Moreover, runaway data growth and other modern realities make protecting and managing data an increasingly difficult task. There is therefore a need for efficient, powerful, and user-friendly solutions for protecting and managing data.
Depending on the size of the organization, there are typically many data production sources which are under the purview of tens, hundreds, or even thousands of employees or other individuals. In the past, individual employees were sometimes responsible for managing and protecting their data. A patchwork of hardware and software point solutions has been applied in other cases. These solutions were often provided by different vendors and had limited or no interoperability.
Certain embodiments described herein provide systems and methods capable of addressing these and other shortcomings of prior approaches by implementing unified, organization-wide information management.
Generally, the systems and associated components described herein may be compatible with and/or provide some or all of the functionality of the systems and corresponding components described in one or more of the following U.S. patents and patent application publications assigned to CommVault Systems, Inc., each of which is hereby incorporated in its entirety by reference herein:
The information management system 100 can include a variety of different computing devices. For instance, as will be described in greater detail herein, the information management system 100 can include one or more client computing devices 102 and secondary storage computing devices 106.
Computing devices can include, without limitation, one or more: workstations, personal computers, desktop computers, or other types of generally fixed computing systems such as mainframe computers and minicomputers. Other computing devices can include mobile or portable computing devices, such as one or more laptops, tablet computers, personal data assistants, mobile phones (such as smartphones), and other mobile or portable computing devices such as embedded computers, set top boxes, vehicle-mounted devices, wearable computers, etc. Computing devices can include servers, such as mail servers, file servers, database servers, and web servers.
In some cases, a computing device includes virtualized and/or cloud computing resources. For instance, one or more virtual machines may be provided to the organization by a third-party cloud service vendor. Or, in some embodiments, computing devices can include one or more virtual machine(s) running on a physical host computing device (or “host machine”) operated by the organization. As one example, the organization may use one virtual machine as a database server and another virtual machine as a mail server, both virtual machines operating on the same host machine.
A virtual machine includes an operating system and associated virtual resources, and is hosted simultaneously with another operating system on a physical host computer (or host machine). A hypervisor (typically software, and also known in the art as a virtual machine monitor or a virtual machine manager or “VMM”) sits between the virtual machine and the hardware of the physical host machine. One example of hypervisor as virtualization software is ESX Server, by VMware, Inc. of Palo Alto, California; other examples include Microsoft Virtual Server and Microsoft Windows Server Hyper-V, both by Microsoft Corporation of Redmond, Washington, and Sun xVM by Oracle America Inc. of Santa Clara, California In some embodiments, the hypervisor may be firmware or hardware or a combination of software and/or firmware and/or hardware.
The hypervisor provides to each virtual operating system virtual resources, such as a virtual processor, virtual memory, a virtual network device, and a virtual disk. Each virtual machine has one or more virtual disks. The hypervisor typically stores the data of virtual disks in files on the file system of the physical host machine, called virtual machine disk files (in the case of VMware virtual servers) or virtual hard disk image files (in the case of Microsoft virtual servers). For example, VMware's ESX Server provides the Virtual Machine File System (VMFS) for the storage of virtual machine disk files. A virtual machine reads data from and writes data to its virtual disk much the same way that an actual physical machine reads data from and writes data to an actual disk.
Examples of techniques for implementing information management techniques in a cloud computing environment are described in U.S. Pat. No. 8,285,681, which is incorporated by reference herein. Examples of techniques for implementing information management techniques in a virtualized computing environment are described in U.S. Pat. No. 8,307,177, also incorporated by reference herein.
The information management system 100 can also include a variety of storage devices, including primary storage devices 104 and secondary storage devices 108, for example. Storage devices can generally be of any suitable type including, without limitation, disk drives, hard-disk arrays, semiconductor memory (e.g., solid state storage devices), network attached storage (NAS) devices, tape libraries or other magnetic, non-tape storage devices, optical media storage devices, DNA/RNA-based memory technology, combinations of the same, and the like. In some embodiments, storage devices can form part of a distributed file system. In some cases, storage devices are provided in a cloud (e.g., a private cloud or one operated by a third-party vendor). A storage device in some cases comprises a disk array or portion thereof.
The illustrated information management system 100 includes one or more client computing device 102 having at least one application 110 executing thereon, and one or more primary storage devices 104 storing primary data 112. The client computing device(s) 102 and the primary storage devices 104 may generally be referred to in some cases as a primary storage subsystem 117. A computing device in an information management system 100 that has a data agent 142 installed and operating on it is generally referred to as a client computing device 102 (or, in the context of a component of the information management system 100 simply as a “client”).
Depending on the context, the term “information management system” can refer to generally all of the illustrated hardware and software components. Or, in other instances, the term may refer to only a subset of the illustrated components.
For instance, in some cases, the information management system 100 generally refers to a combination of specialized components used to protect, move, manage, manipulate, analyze, and/or process data and metadata generated by the client computing devices 102. However, the information management system 100 in some cases does not include the underlying components that generate and/or store the primary data 112, such as the client computing devices 102 themselves, the applications 110 and operating system operating on the client computing devices 102, and the primary storage devices 104. As an example, “information management system” may sometimes refer to one or more of the following components and corresponding data structures: storage managers, data agents, and media agents. These components will be described in further detail below.
Client Computing Devices
There are typically a variety of sources in an organization that produce data to be protected and managed. As just one illustrative example, in a corporate environment such data sources can be employee workstations and company servers such as a mail server, a web server, a database server, a transaction server, or the like. In the information management system 100, the data generation sources include the one or more client computing devices 102.
The client computing devices 102 may include any of the types of computing devices described above, without limitation, and in some cases the client computing devices 102 are associated with one or more users and/or corresponding user accounts, of employees or other individuals.
The information management system 100 generally addresses and handles the data management and protection needs for the data generated by the client computing devices 102. However, the use of this term does not imply that the client computing devices 102 cannot be “servers” in other respects. For instance, a particular client computing device 102 may act as a server with respect to other devices, such as other client computing devices 102. As just a few examples, the client computing devices 102 can include mail servers, file servers, database servers, and web servers.
Each client computing device 102 may have one or more applications 110 (e.g., software applications) executing thereon which generate and manipulate the data that is to be protected from loss and managed. The applications 110 generally facilitate the operations of an organization (or multiple affiliated organizations), and can include, without limitation, mail server applications (e.g., Microsoft Exchange Server), file server applications, mail client applications (e.g., Microsoft Exchange Client), database applications (e.g., SQL, Oracle, SAP, Lotus Notes Database), word processing applications (e.g., Microsoft Word), spreadsheet applications, financial applications, presentation applications, graphics and/or video applications, browser applications, mobile applications, entertainment applications, and so on.
The client computing devices 102 can have at least one operating system (e.g., Microsoft Windows, Mac OS X, iOS, IBM z/OS, Linux, other Unix-based operating systems, etc.) installed thereon, which may support or host one or more file systems and other applications 110.
The client computing devices 102 and other components in information management system 100 can be connected to one another via one or more communication pathways 114. For example, a first communication pathway 114 may connect (or communicatively couple) client computing device 102 and secondary storage computing device 106; a second communication pathway 114 may connect storage manager 140 and client computing device 102; and a third communication pathway 114 may connect storage manager 140 and secondary storage computing device 106, etc. (see, e.g.,
Primary Data and Exemplary Primary Storage Devices
Primary data 112 according to some embodiments is production data or other “live” data generated by the operating system and/or applications 110 operating on a client computing device 102. The primary data 112 is generally stored on the primary storage device(s) 104 and is organized via a file system supported by the client computing device 102. For instance, the client computing device(s) 102 and corresponding applications 110 may create, access, modify, write, delete, and otherwise use primary data 112. In some cases, some or all of the primary data 112 can be stored in cloud storage resources (e.g., primary storage device 104 may be a cloud-based resource).
Primary data 112 is generally in the native format of the source application 110. According to certain aspects, primary data 112 is an initial or first (e.g., created before any other copies or before at least one other copy) stored copy of data generated by the source application 110. Primary data 112 in some cases is created substantially directly from data generated by the corresponding source applications 110.
The primary storage devices 104 storing the primary data 112 may be relatively fast and/or expensive technology (e.g., a disk drive, a hard-disk array, solid state memory, etc.). In addition, primary data 112 may be highly changeable and/or may be intended for relatively short term retention (e.g., hours, days, or weeks).
According to some embodiments, the client computing device 102 can access primary data 112 from the primary storage device 104 by making conventional file system calls via the operating system. Primary data 112 may include structured data (e.g., database files), unstructured data (e.g., documents), and/or semi-structured data. Some specific examples are described below with respect to
It can be useful in performing certain tasks to organize the primary data 112 into units of different granularities. In general, primary data 112 can include files, directories, file system volumes, data blocks, extents, or any other hierarchies or organizations of data objects. As used herein, a “data object” can refer to both (1) any file that is currently addressable by a file system or that was previously addressable by the file system (e.g., an archive file) and (2) a subset of such a file (e.g., a data block).
As will be described in further detail, it can also be useful in performing certain functions of the information management system 100 to access and modify metadata within the primary data 112. Metadata generally includes information about data objects or characteristics associated with the data objects. For simplicity herein, it is to be understood that, unless expressly stated otherwise, any reference to primary data 112 generally also includes its associated metadata, but references to the metadata do not include the primary data.
Metadata can include, without limitation, one or more of the following: the data owner (e.g., the client or user that generates the data), the last modified time (e.g., the time of the most recent modification of the data object), a data object name (e.g., a file name), a data object size (e.g., a number of bytes of data), information about the content (e.g., an indication as to the existence of a particular search term), user-supplied tags, to/from information for email (e.g., an email sender, recipient, etc.), creation date, file type (e.g., format or application type), last accessed time, application type (e.g., type of application that generated the data object), location/network (e.g., a current, past or future location of the data object and network pathways to/from the data object), geographic location (e.g., GPS coordinates), frequency of change (e.g., a period in which the data object is modified), business unit (e.g., a group or department that generates, manages or is otherwise associated with the data object), aging information (e.g., a schedule, such as a time period, in which the data object is migrated to secondary or long term storage), boot sectors, partition layouts, file location within a file folder directory structure, user permissions, owners, groups, access control lists [ACLs]), system metadata (e.g., registry information), combinations of the same or other similar information related to the data object.
In addition to metadata generated by or related to file systems and operating systems, some of the applications 110 and/or other components of the information management system 100 maintain indices of metadata for data objects, e.g., metadata associated with individual email messages. Thus, each data object may be associated with corresponding metadata. The use of metadata to perform classification and other functions is described in greater detail below.
Each of the client computing devices 102 are generally associated with and/or in communication with one or more of the primary storage devices 104 storing corresponding primary data 112. A client computing device 102 may be considered to be “associated with” or “in communication with” a primary storage device 104 if it is capable of one or more of: routing and/or storing data (e.g., primary data 112) to the particular primary storage device 104, coordinating the routing and/or storing of data to the particular primary storage device 104, retrieving data from the particular primary storage device 104, coordinating the retrieval of data from the particular primary storage device 104, and modifying and/or deleting data retrieved from the particular primary storage device 104.
The primary storage devices 104 can include any of the different types of storage devices described above, or some other kind of suitable storage device. The primary storage devices 104 may have relatively fast I/O times and/or are relatively expensive in comparison to the secondary storage devices 108. For example, the information management system 100 may generally regularly access data and metadata stored on primary storage devices 104, whereas data and metadata stored on the secondary storage devices 108 is accessed relatively less frequently.
Primary storage device 104 may be dedicated or shared. In some cases, each primary storage device 104 is dedicated to an associated client computing device 102. For instance, a primary storage device 104 in one embodiment is a local disk drive of a corresponding client computing device 102. In other cases, one or more primary storage devices 104 can be shared by multiple client computing devices 102, e.g., via a network such as in a cloud storage implementation. As one example, a primary storage device 104 can be a disk array shared by a group of client computing devices 102, such as one of the following types of disk arrays: EMC Clariion, EMC Symmetrix, EMC Celerra, Dell EqualLogic, IBM XIV, NetApp FAS, HP EVA, and HP 3PAR.
The information management system 100 may also include hosted services (not shown), which may be hosted in some cases by an entity other than the organization that employs the other components of the information management system 100. For instance, the hosted services may be provided by various online service providers to the organization. Such service providers can provide services including social networking services, hosted email services, or hosted productivity applications or other hosted applications). Hosted services may include software-as-a-service (SaaS), platform-as-a-service (PaaS), application service providers (ASPs), cloud services, or other mechanisms for delivering functionality via a network. As it provides services to users, each hosted service may generate additional data and metadata under management of the information management system 100, e.g., as primary data 112. In some cases, the hosted services may be accessed using one of the applications 110. As an example, a hosted mail service may be accessed via browser running on a client computing device 102. The hosted services may be implemented in a variety of computing environments. In some cases, they are implemented in an environment having a similar arrangement to the information management system 100, where various physical and logical components are distributed over a network.
Secondary Copies and Exemplary Secondary Storage Devices
The primary data 112 stored on the primary storage devices 104 may be compromised in some cases, such as when an employee deliberately or accidentally deletes or overwrites primary data 112 during their normal course of work. Or the primary storage devices 104 can be damaged, lost, or otherwise corrupted. For recovery and/or regulatory compliance purposes, it is therefore useful to generate copies of the primary data 112. Accordingly, the information management system 100 includes one or more secondary storage computing devices 106 and one or more secondary storage devices 108 configured to create and store one or more secondary copies 116 of the primary data 112 and associated metadata. The secondary storage computing devices 106 and the secondary storage devices 108 may sometimes be referred to as a secondary storage subsystem 118.
Creation of secondary copies 116 can help in search and analysis efforts and meet other information management goals, such as: restoring data and/or metadata if an original version (e.g., of primary data 112) is lost (e.g., by deletion, corruption, or disaster); allowing point-in-time recovery; complying with regulatory data retention and electronic discovery (e-discovery) requirements; reducing utilized storage capacity; facilitating organization and search of data; improving user access to data files across multiple computing devices and/or hosted services; and implementing data retention policies.
The client computing devices 102 access or receive primary data 112 and communicate the data, e.g., over one or more communication pathways 114, for storage in the secondary storage device(s) 108.
A secondary copy 116 can comprise a separate stored copy of application data that is derived from one or more earlier-created, stored copies (e.g., derived from primary data 112 or another secondary copy 116). Secondary copies 116 can include point-in-time data, and may be intended for relatively long-term retention (e.g., weeks, months or years), before some or all of the data is moved to other storage or is discarded.
In some cases, a secondary copy 116 is a copy of application data created and stored subsequent to at least one other stored instance (e.g., subsequent to corresponding primary data 112 or to another secondary copy 116), in a different storage device than at least one previous stored copy, and/or remotely from at least one previous stored copy. In some other cases, secondary copies can be stored in the same storage device as primary data 112 and/or other previously stored copies. For example, in one embodiment a disk array capable of performing hardware snapshots stores primary data 112 and creates and stores hardware snapshots of the primary data 112 as secondary copies 116. Secondary copies 116 may be stored in relatively slow and/or low cost storage (e.g., magnetic tape). A secondary copy 116 may be stored in a backup or archive format, or in some other format different than the native source application format or other primary data format.
In some cases, secondary copies 116 are indexed so users can browse and restore at another point in time. After creation of a secondary copy 116 representative of certain primary data 112, a pointer or other location indicia (e.g., a stub) may be placed in primary data 112, or be otherwise associated with primary data 112 to indicate the current location on the secondary storage device(s) 108 of secondary copy 116.
Since an instance of a data object or metadata in primary data 112 may change over time as it is modified by an application 110 (or hosted service or the operating system), the information management system 100 may create and manage multiple secondary copies 116 of a particular data object or metadata, each representing the state of the data object in primary data 112 at a particular point in time. Moreover, since an instance of a data object in primary data 112 may eventually be deleted from the primary storage device 104 and the file system, the information management system 100 may continue to manage point-in-time representations of that data object, even though the instance in primary data 112 no longer exists.
For virtualized computing devices the operating system and other applications 110 of the client computing device(s) 102 may execute within or under the management of virtualization software (e.g., a VMM), and the primary storage device(s) 104 may comprise a virtual disk created on a physical storage device. The information management system 100 may create secondary copies 116 of the files or other data objects in a virtual disk file and/or secondary copies 116 of the entire virtual disk file itself (e.g., of an entire .vmdk file).
Secondary copies 116 may be distinguished from corresponding primary data 112 in a variety of ways, some of which will now be described. First, as discussed, secondary copies 116 can be stored in a different format (e.g., backup, archive, or other non-native format) than primary data 112. For this or other reasons, secondary copies 116 may not be directly useable by the applications 110 of the client computing device 102, e.g., via standard system calls or otherwise without modification, processing, or other intervention by the information management system 100.
Secondary copies 116 are also in some embodiments stored on a secondary storage device 108 that is inaccessible to the applications 110 running on the client computing devices 102 (and/or hosted services). Some secondary copies 116 may be “offline copies,” in that they are not readily available (e.g., not mounted to tape or disk). Offline copies can include copies of data that the information management system 100 can access without human intervention (e.g., tapes within an automated tape library, but not yet mounted in a drive), and copies that the information management system 100 can access only with at least some human intervention (e.g., tapes located at an offsite storage site).
The Use of Intermediate Devices for Creating Secondary Copies
Creating secondary copies can be a challenging task. For instance, there can be hundreds or thousands of client computing devices 102 continually generating large volumes of primary data 112 to be protected. Also, there can be significant overhead involved in the creation of secondary copies 116. Moreover, secondary storage devices 108 may be special purpose components, and interacting with them can require specialized intelligence.
In some cases, the client computing devices 102 interact directly with the secondary storage device 108 to create the secondary copies 116. However, in view of the factors described above, this approach can negatively impact the ability of the client computing devices 102 to serve the applications 110 and produce primary data 112. Further, the client computing devices 102 may not be optimized for interaction with the secondary storage devices 108.
Thus, in some embodiments, the information management system 100 includes one or more software and/or hardware components which generally act as intermediaries between the client computing devices 102 and the secondary storage devices 108. In addition to off-loading certain responsibilities from the client computing devices 102, these intermediate components can provide other benefits. For instance, as discussed further below with respect to
The intermediate components can include one or more secondary storage computing devices 106 as shown in
The secondary storage computing device(s) 106 can comprise any of the computing devices described above, without limitation. In some cases, the secondary storage computing device(s) 106 include specialized hardware and/or software componentry for interacting with the secondary storage devices 108.
To create a secondary copy 116 involving the copying of data from the primary storage subsystem 117 to the secondary storage subsystem 118, the client computing device 102 in some embodiments communicates the primary data 112 to be copied (or a processed version thereof) to the designated secondary storage computing device 106, via the communication pathway 114. The secondary storage computing device 106 in turn conveys the received data (or a processed version thereof) to the secondary storage device 108. In some such configurations, the communication pathway 114 between the client computing device 102 and the secondary storage computing device 106 comprises a portion of a LAN, WAN or SAN. In other cases, at least some client computing devices 102 communicate directly with the secondary storage devices 108 (e.g., via Fibre Channel or SCSI connections). In some other cases, one or more secondary copies 116 are created from existing secondary copies, such as in the case of an auxiliary copy operation, described in greater detail below.
Exemplary Primary Data and an Exemplary Secondary Copy
Some or all primary data objects are associated with corresponding metadata (e.g., “Meta1-11”), which may include file system metadata and/or application specific metadata. Stored on the secondary storage device(s) 108 are secondary copy data objects 134A-C which may include copies of or otherwise represent corresponding primary data objects and metadata.
As shown, the secondary copy data objects 134A-C can individually represent more than one primary data object. For example, secondary copy data object 134A represents three separate primary data objects 133C, 122, and 129C (represented as 133C′, 122′, and 129C′, respectively, and accompanied by the corresponding metadata Meta11, Meta3, and Meta8, respectively). Moreover, as indicated by the prime mark (′), a secondary copy object may store a representation of a primary data object and/or metadata differently than the original format, e.g., in a compressed, encrypted, deduplicated, or other modified format. Likewise, secondary data object 134B represents primary data objects 120, 133B, and 119A as 120′, 133B′, and 119A′, respectively and accompanied by corresponding metadata Meta2, Meta10, and Meta1, respectively. Also, secondary data object 134C represents primary data objects 133A, 119B, and 129A as 133A′, 119B′, and 129A′, respectively, accompanied by corresponding metadata Meta9, Meta5, and Meta6, respectively.
Exemplary Information Management System Architecture
The information management system 100 can incorporate a variety of different hardware and software components, which can in turn be organized with respect to one another in many different configurations, depending on the embodiment. There are critical design choices involved in specifying the functional responsibilities of the components and the role of each component in the information management system 100. For instance, as will be discussed, such design choices can impact performance as well as the adaptability of the information management system 100 to data growth or other changing circumstances.
Storage Manager
As noted, the number of components in the information management system 100 and the amount of data under management can be quite large. Managing the components and data is therefore a significant task, and a task that can grow in an often unpredictable fashion as the quantity of components and data scale to meet the needs of the organization. For these and other reasons, according to certain embodiments, responsibility for controlling the information management system 100, or at least a significant portion of that responsibility, is allocated to the storage manager 140. By distributing control functionality in this manner, the storage manager 140 can be adapted independently according to changing circumstances. Moreover, a computing device for hosting the storage manager 140 can be selected to best suit the functions of the storage manager 140. These and other advantages are described in further detail below with respect to
The storage manager 140 may be a software module or other application, which, in some embodiments operates in conjunction with one or more associated data structures, e.g., a dedicated database (e.g., management database 146). In some embodiments, storage manager 140 is a computing device comprising circuitry for executing computer instructions and performs the functions described herein. The storage manager generally initiates, performs, coordinates and/or controls storage and other information management operations performed by the information management system 100, e.g., to protect and control the primary data 112 and secondary copies 116 of data and metadata. In general, storage manager 100 may be said to manage information management system 100, which includes managing the constituent components, e.g., data agents and media agents, etc.
As shown by the dashed arrowed lines 114 in
In other embodiments, some information management operations are controlled by other components in the information management system 100 (e.g., the media agent(s) 144 or data agent(s) 142), instead of or in combination with the storage manager 140.
According to certain embodiments, the storage manager 140 provides one or more of the following functions:
The storage manager 140 may maintain a database 146 (or “storage manager database 146” or “management database 146”) of management-related data and information management policies 148. The database 146 may include a management index 150 (or “index 150”) or other data structure that stores logical associations between components of the system, user preferences and/or profiles (e.g., preferences regarding encryption, compression, or deduplication of primary or secondary copy data, preferences regarding the scheduling, type, or other aspects of primary or secondary copy or other operations, mappings of particular information management users or user accounts to certain computing devices or other components, etc.), management tasks, media containerization, or other useful data. For example, the storage manager 140 may use the index 150 to track logical associations between media agents 144 and secondary storage devices 108 and/or movement of data from primary storage devices 104 to secondary storage devices 108. For instance, the index 150 may store data associating a client computing device 102 with a particular media agent 144 and/or secondary storage device 108, as specified in an information management policy 148 (e.g., a storage policy, which is defined in more detail below).
Administrators and other people may be able to configure and initiate certain information management operations on an individual basis. But while this may be acceptable for some recovery operations or other relatively less frequent tasks, it is often not workable for implementing on-going organization-wide data protection and management. Thus, the information management system 100 may utilize information management policies 148 for specifying and executing information management operations (e.g., on an automated basis). Generally, an information management policy 148 can include a data structure or other information source that specifies a set of parameters (e.g., criteria and rules) associated with storage or other information management operations.
The storage manager database 146 may maintain the information management policies 148 and associated data, although the information management policies 148 can be stored in any appropriate location. For instance, an information management policy 148 such as a storage policy may be stored as metadata in a media agent database 152 or in a secondary storage device 108 (e.g., as an archive copy) for use in restore operations or other information management operations, depending on the embodiment. Information management policies 148 are described further below.
According to certain embodiments, the storage manager database 146 comprises a relational database (e.g., an SQL database) for tracking metadata, such as metadata associated with secondary copy operations (e.g., what client computing devices 102 and corresponding data were protected). This and other metadata may additionally be stored in other locations, such as at the secondary storage computing devices 106 or on the secondary storage devices 108, allowing data recovery without the use of the storage manager 140 in some cases.
As shown, the storage manager 140 may include a jobs agent 156, a user interface 158, and a management agent 154, all of which may be implemented as interconnected software modules or application programs.
The jobs agent 156 in some embodiments initiates, controls, and/or monitors the status of some or all storage or other information management operations previously performed, currently being performed, or scheduled to be performed by the information management system 100. For instance, the jobs agent 156 may access information management policies 148 to determine when and how to initiate and control secondary copy and other information management operations, as will be discussed further.
The user interface 158 may include information processing and display software, such as a graphical user interface (“GUI”), an application program interface (“API”), or other interactive interface(s) through which users and system processes can retrieve information about the status of information management operations (e.g., storage operations) or issue instructions to the information management system 100 and its constituent components. Via the user interface 158, users may optionally issue instructions to the components in the information management system 100 regarding performance of storage and recovery operations. For example, a user may modify a schedule concerning the number of pending secondary copy operations. As another example, a user may employ the GUI to view the status of pending storage operations or to monitor the status of certain components in the information management system 100 (e.g., the amount of capacity left in a storage device).
An “information management cell” (or “storage operation cell” or “cell”) may generally include a logical and/or physical grouping of a combination of hardware and software components associated with performing information management operations on electronic data, typically one storage manager 140 and at least one client computing device 102 (comprising data agent(s) 142) and at least one media agent 144. For instance, the components shown in
The storage manager 140 may also track information that permits it to select, designate, or otherwise identify content indices, deduplication databases, or similar databases or resources or data sets within its information management cell (or another cell) to be searched in response to certain queries. Such queries may be entered by the user via interaction with the user interface 158. In general, the management agent 154 allows multiple information management cells to communicate with one another. For example, the information management system 100 in some cases may be one information management cell of a network of multiple cells adjacent to one another or otherwise logically related in a WAN or LAN. With this arrangement, the cells may be connected to one another through respective management agents 154.
For instance, the management agent 154 can provide the storage manager 140 with the ability to communicate with other components within the information management system 100 (and/or other cells within a larger information management system) via network protocols and application programming interfaces (“APIs”) including, e.g., HTTP, HTTPS, FTP, REST, virtualization software APIs, cloud service provider APIs, and hosted service provider APIs. Inter-cell communication and hierarchy is described in greater detail in e.g., U.S. Pat. Nos. 7,747,579 and 7,343,453, which are incorporated by reference herein.
Data Agents
As discussed, a variety of different types of applications 110 can operate on a given client computing device 102, including operating systems, database applications, e-mail applications, and virtual machines, just to name a few. And, as part of the process of creating and restoring secondary copies 116, the client computing devices 102 may be tasked with processing and preparing the primary data 112 from these various different applications 110. Moreover, the nature of the processing/preparation can differ across clients and application types, e.g., due to inherent structural and formatting differences among applications 110.
The one or more data agent(s) 142 are therefore advantageously configured in some embodiments to assist in the performance of information management operations based on the type of data that is being protected, at a client-specific and/or application-specific level.
The data agent 142 may be a software module or component that is generally responsible for managing, initiating, or otherwise assisting in the performance of information management operations in information management system 100, generally as directed by storage manager 140. For instance, the data agent 142 may take part in performing data storage operations such as the copying, archiving, migrating, and/or replicating of primary data 112 stored in the primary storage device(s) 104. The data agent 142 may receive control information from the storage manager 140, such as commands to transfer copies of data objects, metadata, and other payload data to the media agents 144.
In some embodiments, a data agent 142 may be distributed between the client computing device 102 and storage manager 140 (and any other intermediate components) or may be deployed from a remote location or its functions approximated by a remote process that performs some or all of the functions of data agent 142. In addition, a data agent 142 may perform some functions provided by a media agent 144, or may perform other functions such as encryption and deduplication.
As indicated, each data agent 142 may be specialized for a particular application 110, and the system can employ multiple application-specific data agents 142, each of which may perform information management operations (e.g., perform backup, migration, and data recovery) associated with a different application 110. For instance, different individual data agents 142 may be designed to handle Microsoft Exchange data, Lotus Notes data, Microsoft Windows file system data, Microsoft Active Directory Objects data, SQL Server data, SharePoint data, Oracle database data, SAP database data, virtual machines and/or associated data, and other types of data.
A file system data agent, for example, may handle data files and/or other file system information. If a client computing device 102 has two or more types of data, a specialized data agent 142 may be used for each data type to copy, archive, migrate, and restore the client computing device 102 data. For example, to backup, migrate, and/or restore all of the data on a Microsoft Exchange server, the client computing device 102 may use a Microsoft Exchange Mailbox data agent 142 to back up the Exchange mailboxes, a Microsoft Exchange Database data agent 142 to back up the Exchange databases, a Microsoft Exchange Public Folder data agent 142 to back up the Exchange Public Folders, and a Microsoft Windows File System data agent 142 to back up the file system of the client computing device 102. In such embodiments, these specialized data agents 142 may be treated as four separate data agents 142 even though they operate on the same client computing device 102.
Other embodiments may employ one or more generic data agents 142 that can handle and process data from two or more different applications 110, or that can handle and process multiple data types, instead of or in addition to using specialized data agents 142. For example, one generic data agent 142 may be used to back up, migrate and restore Microsoft Exchange Mailbox data and Microsoft Exchange Database data while another generic data agent may handle Microsoft Exchange Public Folder data and Microsoft Windows File System data.
Each data agent 142 may be configured to access data and/or metadata stored in the primary storage device(s) 104 associated with the data agent 142 and process the data as appropriate. For example, during a secondary copy operation, the data agent 142 may arrange or assemble the data and metadata into one or more files having a certain format (e.g., a particular backup or archive format) before transferring the file(s) to a media agent 144 or other component. The file(s) may include a list of files or other metadata. Each data agent 142 can also assist in restoring data or metadata to primary storage devices 104 from a secondary copy 116. For instance, the data agent 142 may operate in conjunction with the storage manager 140 and one or more of the media agents 144 to restore data from secondary storage device(s) 108.
Media Agents
As indicated above with respect to
Generally speaking, a media agent 144 may be implemented as a software module that manages, coordinates, and facilitates the transmission of data, as directed by the storage manager 140, between a client computing device 102 and one or more secondary storage devices 108. Whereas the storage manager 140 controls the operation of the information management system 100, the media agent 144 generally provides a portal to secondary storage devices 108. For instance, other components in the system interact with the media agents 144 to gain access to data stored on the secondary storage devices 108, whether it be for the purposes of reading, writing, modifying, or deleting data. Moreover, as will be described further, media agents 144 can generate and store information relating to characteristics of the stored data and/or metadata, or can generate and store other types of information that generally provides insight into the contents of the secondary storage devices 108.
Media agents 144 can comprise separate nodes in the information management system 100 (e.g., nodes that are separate from the client computing devices 102, storage manager 140, and/or secondary storage devices 108). In general, a node within the information management system 100 can be a logically and/or physically separate component, and in some cases is a component that is individually addressable or otherwise identifiable. In addition, each media agent 144 may operate on a dedicated secondary storage computing device 106 in some cases, while in other embodiments a plurality of media agents 144 operate on the same secondary storage computing device 106.
A media agent 144 (and corresponding media agent database 152) may be considered to be “associated with” a particular secondary storage device 108 if that media agent 144 is capable of one or more of: routing and/or storing data to the particular secondary storage device 108, coordinating the routing and/or storing of data to the particular secondary storage device 108, retrieving data from the particular secondary storage device 108, coordinating the retrieval of data from a particular secondary storage device 108, and modifying and/or deleting data retrieved from the particular secondary storage device 108.
While media agent(s) 144 are generally associated with one or more secondary storage devices 108, one or more media agents 144 in certain embodiments are physically separate from the secondary storage devices 108. For instance, the media agents 144 may operate on secondary storage computing devices 106 having different housings or packages than the secondary storage devices 108. In one example, a media agent 144 operates on a first server computer and is in communication with a secondary storage device(s) 108 operating in a separate, rack-mounted RAID-based system.
Where the information management system 100 includes multiple media agents 144 (see, e.g.,
In operation, a media agent 144 associated with a particular secondary storage device 108 may instruct the secondary storage device 108 to perform an information management operation. For instance, a media agent 144 may instruct a tape library to use a robotic arm or other retrieval means to load or eject a certain storage media, and to subsequently archive, migrate, or retrieve data to or from that media, e.g., for the purpose of restoring the data to a client computing device 102. As another example, a secondary storage device 108 may include an array of hard disk drives or solid state drives organized in a RAID configuration, and the media agent 144 may forward a logical unit number (LUN) and other appropriate information to the array, which uses the received information to execute the desired storage operation. The media agent 144 may communicate with a secondary storage device 108 via a suitable communications link, such as a SCSI or Fiber Channel link.
As shown, each media agent 144 may maintain an associated media agent database 152. The media agent database 152 may be stored in a disk or other storage device (not shown) that is local to the secondary storage computing device 106 on which the media agent 144 operates. In other cases, the media agent database 152 is stored remotely from the secondary storage computing device 106.
The media agent database 152 can include, among other things, an index 153 (see, e.g.,
A media agent index 153 or other data structure associated with the particular media agent 144 may include information about the stored data. For instance, for each secondary copy 116, the index 153 may include metadata such as a list of the data objects (e.g., files/subdirectories, database objects, mailbox objects, etc.), a path to the secondary copy 116 on the corresponding secondary storage device 108, location information indicating where the data objects are stored in the secondary storage device 108, when the data objects were created or modified, etc. Thus, the index 153 includes metadata associated with the secondary copies 116 that is readily available for use without having to be first retrieved from the secondary storage device 108. In yet further embodiments, some or all of the information in index 153 may instead or additionally be stored along with the secondary copies of data in a secondary storage device 108. In some embodiments, the secondary storage devices 108 can include sufficient information to perform a “bare metal restore”, where the operating system of a failed client computing device 102 or other restore target is automatically rebuilt as part of a restore operation.
Because the index 153 maintained in the media agent database 152 may operate as a cache, it can also be referred to as “an index cache.” In such cases, information stored in the index cache 153 typically comprises data that reflects certain particulars about storage operations that have occurred relatively recently. After some triggering event, such as after a certain period of time elapses, or the index cache 153 reaches a particular size, the index cache 153 may be copied or migrated to a secondary storage device(s) 108. This information may need to be retrieved and uploaded back into the index cache 153 or otherwise restored to a media agent 144 to facilitate retrieval of data from the secondary storage device(s) 108. In some embodiments, the cached information may include format or containerization information related to archives or other files stored on the storage device(s) 108. In this manner, the index cache 153 allows for accelerated restores.
In some alternative embodiments the media agent 144 generally acts as a coordinator or facilitator of storage operations between client computing devices 102 and corresponding secondary storage devices 108, but does not actually write the data to the secondary storage device 108. For instance, the storage manager 140 (or the media agent 144) may instruct a client computing device 102 and secondary storage device 108 to communicate with one another directly. In such a case the client computing device 102 transmits the data directly or via one or more intermediary components to the secondary storage device 108 according to the received instructions, and vice versa. In some such cases, the media agent 144 may still receive, process, and/or maintain metadata related to the storage operations. Moreover, in these embodiments, the payload data can flow through the media agent 144 for the purposes of populating the index cache 153 maintained in the media agent database 152, but not for writing to the secondary storage device 108.
The media agent 144 and/or other components such as the storage manager 140 may in some cases incorporate additional functionality, such as data classification, content indexing, deduplication, encryption, compression, and the like. Further details regarding these and other functions are described below.
Distributed, Scalable Architecture
As described, certain functions of the information management system 100 can be distributed amongst various physical and/or logical components in the system. For instance, one or more of the storage manager 140, data agents 142, and media agents 144 may operate on computing devices that are physically separate from one another. This architecture can provide a number of benefits.
For instance, hardware and software design choices for each distributed component can be targeted to suit its particular function. The secondary computing devices 106 on which the media agents 144 operate can be tailored for interaction with associated secondary storage devices 108 and provide fast index cache operation, among other specific tasks. Similarly, the client computing device(s) 102 can be selected to effectively service the applications 110 thereon, in order to efficiently produce and store primary data 112.
Moreover, in some cases, one or more of the individual components in the information management system 100 can be distributed to multiple, separate computing devices. As one example, for large file systems where the amount of data stored in the management database 146 is relatively large, the database 146 may be migrated to or otherwise reside on a specialized database server (e.g., an SQL server) separate from a server that implements the other functions of the storage manager 140. This distributed configuration can provide added protection because the database 146 can be protected with standard database utilities (e.g., SQL log shipping or database replication) independent from other functions of the storage manager 140. The database 146 can be efficiently replicated to a remote site for use in the event of a disaster or other data loss at the primary site. Or the database 146 can be replicated to another computing device within the same site, such as to a higher performance machine in the event that a storage manager host device can no longer service the needs of a growing information management system 100.
The distributed architecture also provides both scalability and efficient component utilization.
Additional components can be added or subtracted based on the evolving needs of the information management system 100. For instance, depending on where bottlenecks are identified, administrators can add additional client computing devices 102, secondary storage computing devices 106 (and corresponding media agents 144), and/or secondary storage devices 108. Moreover, where multiple fungible components are available, load balancing can be implemented to dynamically address identified bottlenecks. As an example, the storage manager 140 may dynamically select which media agents 144 and/or secondary storage devices 108 to use for storage operations based on a processing load analysis of the media agents 144 and/or secondary storage devices 108, respectively.
Moreover, each client computing device 102 in some embodiments can communicate with, among other components, any of the media agents 144, e.g., as directed by the storage manager 140. And each media agent 144 may be able to communicate with, among other components, any of the secondary storage devices 108, e.g., as directed by the storage manager 140. Thus, operations can be routed to the secondary storage devices 108 in a dynamic and highly flexible manner, to provide load balancing, failover, and the like. Further examples of scalable systems capable of dynamic storage operations, and of systems capable of performing load balancing and fail over are provided in U.S. Pat. No. 7,246,207, which is incorporated by reference herein.
In alternative configurations, certain components are not distributed and may instead reside and execute on the same computing device. For example, in some embodiments, one or more data agents 142 and the storage manager 140 operate on the same client computing device 102. In another embodiment, one or more data agents 142 and one or more media agents 144 operate on a single computing device.
Exemplary Types of Information Management Operations
In order to protect and leverage stored data, the information management system 100 can be configured to perform a variety of information management operations. As will be described, these operations can generally include secondary copy and other data movement operations, processing and data manipulation operations, analysis, reporting, and management operations. The operations described herein may be performed on any type of computing device, e.g., between two computers connected via a LAN, to a mobile client telecommunications device connected to a server via a WLAN, to any manner of client computing device coupled to a cloud storage target, etc., without limitation.
Data Movement Operations
Data movement operations according to certain embodiments are generally operations that involve the copying or migration of data (e.g., payload data) between different locations in the information management system 100 in an original/native and/or one or more different formats. For example, data movement operations can include operations in which stored data is copied, migrated, or otherwise transferred from one or more first storage devices to one or more second storage devices, such as from primary storage device(s) 104 to secondary storage device(s) 108, from secondary storage device(s) 108 to different secondary storage device(s) 108, from secondary storage devices 108 to primary storage devices 104, or from primary storage device(s) 104 to different primary storage device(s) 104.
Data movement operations can include by way of example, backup operations, archive operations, information lifecycle management operations such as hierarchical storage management operations, replication operations (e.g., continuous data replication operations), snapshot operations, deduplication or single-instancing operations, auxiliary copy operations, and the like. As will be discussed, some of these operations involve the copying, migration or other movement of data, without actually creating multiple, distinct copies. Nonetheless, some or all of these operations are referred to as “copy” operations for simplicity.
Backup Operations
A backup operation creates a copy of a version of data (e.g., one or more files or other data units) in primary data 112 at a particular point in time. Each subsequent backup copy may be maintained independently of the first. Further, a backup copy in some embodiments is generally stored in a form that is different than the native format, e.g., a backup format. This can be in contrast to the version in primary data 112 from which the backup copy is derived, and which may instead be stored in a native format of the source application(s) 110. In various cases, backup copies can be stored in a format in which the data is compressed, encrypted, deduplicated, and/or otherwise modified from the original application format. For example, a backup copy may be stored in a backup format that facilitates compression and/or efficient long-term storage.
Backup copies can have relatively long retention periods as compared to primary data 112, and may be stored on media with slower retrieval times than primary data 112 and certain other types of secondary copies 116. On the other hand, backups may have relatively shorter retention periods than some other types of secondary copies 116, such as archive copies (described below). Backups may sometimes be stored at an offsite location.
Backup operations can include full backups, differential backups, incremental backups, “synthetic full” backups, and/or creating a “reference copy.” A full backup (or “standard full backup”) in some embodiments is generally a complete image of the data to be protected. However, because full backup copies can consume a relatively large amount of storage, it can be useful to use a full backup copy as a baseline and only store changes relative to the full backup copy for subsequent backup copies.
For instance, a differential backup operation (or cumulative incremental backup operation) tracks and stores changes that have occurred since the last full backup. Differential backups can grow quickly in size, but can provide relatively efficient restore times because a restore can be completed in some cases using only the full backup copy and the latest differential copy.
An incremental backup operation generally tracks and stores changes since the most recent backup copy of any type, which can greatly reduce storage utilization. In some cases, however, restore times can be relatively long in comparison to full or differential backups because completing a restore operation may involve accessing a full backup in addition to multiple incremental backups.
Synthetic full backups generally consolidate data without directly backing up data from the client computing device. A synthetic full backup is created from the most recent full backup (i.e., standard or synthetic) and subsequent incremental and/or differential backups. The resulting synthetic full backup is identical to what would have been created had the last backup for the subclient been a standard full backup. Unlike standard full, incremental, and differential backups, a synthetic full backup does not actually transfer data from a client computer to the backup media, because it operates as a backup consolidator. A synthetic full backup extracts the index data of each participating subclient. Using this index data and the previously backed up user data images, it builds new full backup images, one for each subclient. The new backup images consolidate the index and user data stored in the related incremental, differential, and previous full backups, in some embodiments creating an archive file at the subclient level.
Any of the above types of backup operations can be at the volume-level, file-level, or block-level. Volume level backup operations generally involve the copying of a data volume (e.g., a logical disk or partition) as a whole. In a file-level backup, the information management system 100 may generally track changes to individual files, and includes copies of files in the backup copy. In the case of a block-level backup, files are broken into constituent blocks, and changes are tracked at the block-level. Upon restore, the information management system 100 reassembles the blocks into files in a transparent fashion.
Far less data may actually be transferred and copied to the secondary storage devices 108 during a file-level copy than a volume-level copy. Likewise, a block-level copy may involve the transfer of less data than a file-level copy, resulting in faster execution times. However, restoring a relatively higher-granularity copy can result in longer restore times. For instance, when restoring a block-level copy, the process of locating constituent blocks can sometimes result in longer restore times as compared to file-level backups. Similar to backup operations, the other types of secondary copy operations described herein can also be implemented at either the volume-level, file-level, or block-level.
For example, in some embodiments, a reference copy may comprise copy(ies) of selected objects from backed up data, typically to help organize data by keeping contextual information from multiple sources together, and/or help retain specific data for a longer period of time, such as for legal hold needs. A reference copy generally maintains data integrity, and when the data is restored, it may be viewed in the same format as the source data. In some embodiments, a reference copy is based on a specialized client, individual subclient and associated information management policies (e.g., storage policy, retention policy, etc.) that are administered within information management system 100.
Archive Operations
Because backup operations generally involve maintaining a version of the copied data in primary data 112 and also maintaining backup copies in secondary storage device(s) 108, they can consume significant storage capacity. To help reduce storage consumption, an archive operation according to certain embodiments creates a secondary copy 116 by both copying and removing source data. Or, seen another way, archive operations can involve moving some or all of the source data to the archive destination. Thus, data satisfying criteria for removal (e.g., data of a threshold age or size) may be removed from source storage. The source data may be primary data 112 or a secondary copy 116, depending on the situation. As with backup copies, archive copies can be stored in a format in which the data is compressed, encrypted, deduplicated, and/or otherwise modified from the format of the original application or source copy. In addition, archive copies may be retained for relatively long periods of time (e.g., years) and, in some cases, are never deleted. Archive copies are generally retained for longer periods of time than backup copies, for example. In certain embodiments, archive copies may be made and kept for extended periods in order to meet compliance regulations.
Moreover, when primary data 112 is archived, in some cases the corresponding primary data 112 or a portion thereof is deleted when creating the archive copy. Thus, archiving can serve the purpose of freeing up space in the primary storage device(s) 104 and easing the demand on computational resources on client computing device 102. Similarly, when a secondary copy 116 is archived, the secondary copy 116 may be deleted, and an archive copy can therefore serve the purpose of freeing up space in secondary storage device(s) 108. In contrast, source copies often remain intact when creating backup copies. Examples of compatible data archiving operations are provided in U.S. Pat. No. 7,107,298, which is incorporated by reference herein.
Snapshot Operations
Snapshot operations can provide a relatively lightweight, efficient mechanism for protecting data. From an end-user viewpoint, a snapshot may be thought of as an “instant” image of the primary data 112 at a given point in time, and may include state and/or status information relative to an application that creates/manages the primary data 112. In one embodiment, a snapshot may generally capture the directory structure of an object in primary data 112 such as a file or volume or other data set at a particular moment in time and may also preserve file attributes and contents. A snapshot in some cases is created relatively quickly, e.g., substantially instantly, using a minimum amount of file space, but may still function as a conventional file system backup.
A “hardware snapshot” (or “hardware-based snapshot”) operation can be a snapshot operation where a target storage device (e.g., a primary storage device 104 or a secondary storage device 108) performs the snapshot operation in a self-contained fashion, substantially independently, using hardware, firmware and/or software operating on the storage device itself. For instance, the storage device may be capable of performing snapshot operations upon request, generally without intervention or oversight from any of the other components in the information management system 100. In this manner, hardware snapshots can off-load other components of information management system 100 from processing involved in snapshot creation and management.
A “software snapshot” (or “software-based snapshot”) operation, on the other hand, can be a snapshot operation in which one or more other components in information management system 100 (e.g., client computing devices 102, data agents 142, etc.) implement a software layer that manages the snapshot operation via interaction with the target storage device. For instance, the component executing the snapshot management software layer may derive a set of pointers and/or data that represents the snapshot. The snapshot management software layer may then transmit the same to the target storage device, along with appropriate instructions for writing the snapshot.
Some types of snapshots do not actually create another physical copy of all the data as it existed at the particular point in time, but may simply create pointers that are able to map files and directories to specific memory locations (e.g., to specific disk blocks) where the data resides, as it existed at the particular point in time. For example, a snapshot copy may include a set of pointers derived from the file system or from an application. In some other cases, the snapshot may be created at the block-level, such that creation of the snapshot occurs without awareness of the file system. Each pointer points to a respective stored data block, so that collectively, the set of pointers reflect the storage location and state of the data object (e.g., file(s) or volume(s) or data set(s)) at a particular point in time when the snapshot copy was created.
An initial snapshot may use only a small amount of disk space needed to record a mapping or other data structure representing or otherwise tracking the blocks that correspond to the current state of the file system. Additional disk space is usually required only when files and directories are modified later on. Furthermore, when files are modified, typically only the pointers which map to blocks are copied, not the blocks themselves. In some embodiments, for example in the case of “copy-on-write” snapshots, when a block changes in primary storage, the block is copied to secondary storage or cached in primary storage before the block is overwritten in primary storage, and the pointer to that block is changed to reflect the new location of that block. The snapshot mapping of file system data may also be updated to reflect the changed block(s) at that particular point in time. In some other cases, a snapshot includes a full physical copy of all or substantially all of the data represented by the snapshot. Further examples of snapshot operations are provided in U.S. Pat. No. 7,529,782, which is incorporated by reference herein.
A snapshot copy in many cases can be made quickly and without significantly impacting primary computing resources because large amounts of data need not be copied or moved. In some embodiments, a snapshot may exist as a virtual file system, parallel to the actual file system. Users in some cases gain read-only access to the record of files and directories of the snapshot. By electing to restore primary data 112 from a snapshot taken at a given point in time, users may also return the current file system to the state of the file system that existed when the snapshot was taken.
Replication Operations
Another type of secondary copy operation is a replication operation. Some types of secondary copies 116 are used to periodically capture images of primary data 112 at particular points in time (e.g., backups, archives, and snapshots). However, it can also be useful for recovery purposes to protect primary data 112 in a more continuous fashion, by replicating the primary data 112 substantially as changes occur. In some cases a replication copy can be a mirror copy, for instance, where changes made to primary data 112 are mirrored or substantially immediately copied to another location (e.g., to secondary storage device(s) 108). By copying each write operation to the replication copy, two storage systems are kept synchronized or substantially synchronized so that they are virtually identical at approximately the same time. Where entire disk volumes are mirrored, however, mirroring can require significant amount of storage space and utilizes a large amount of processing resources.
According to some embodiments storage operations are performed on replicated data that represents a recoverable state, or “known good state” of a particular application running on the source system. For instance, in certain embodiments, known good replication copies may be viewed as copies of primary data 112. This feature allows the system to directly access, copy, restore, backup or otherwise manipulate the replication copies as if the data were the “live” primary data 112. This can reduce access time, storage utilization, and impact on source applications 110, among other benefits. Based on known good state information, the information management system 100 can replicate sections of application data that represent a recoverable state rather than rote copying of blocks of data. Examples of compatible replication operations (e.g., continuous data replication) are provided in U.S. Pat. No. 7,617,262, which is incorporated by reference herein.
Deduplication/Single-Instancing Operations
Another type of data movement operation is deduplication or single-instance storage, which is useful to reduce the amount of non-primary data. For instance, some or all of the above-described secondary storage operations can involve deduplication in some fashion. New data is read, broken down into portions (e.g., sub-file level blocks, files, etc.) of a selected granularity, compared with blocks that are already in secondary storage, and only the new blocks are stored. Blocks that already exist are represented as pointers to the already stored data.
In order to streamline the comparison process, the information management system 100 may calculate and/or store signatures (e.g., hashes or cryptographically unique IDs) corresponding to the individual data blocks in a database and compare the signatures instead of comparing entire data blocks. In some cases, only a single instance of each element is stored, and deduplication operations may therefore be referred to interchangeably as “single-instancing” operations. Depending on the implementation, however, deduplication or single-instancing operations can store more than one instance of certain data blocks, but nonetheless significantly reduce data redundancy. Depending on the embodiment, deduplication blocks can be of fixed or variable length. Using variable length blocks can provide enhanced deduplication by responding to changes in the data stream, but can involve complex processing. In some cases, the information management system 100 utilizes a technique for dynamically aligning deduplication blocks (e.g., fixed-length blocks) based on changing content in the data stream, as described in U.S. Pat. No. 8,364,652, which is incorporated by reference herein.
The information management system 100 can perform deduplication in a variety of manners at a variety of locations in the information management system 100. For instance, in some embodiments, the information management system 100 implements “target-side” deduplication by deduplicating data (e.g., secondary copies 116) stored in the secondary storage devices 108. In some such cases, the media agents 144 are generally configured to manage the deduplication process. For instance, one or more of the media agents 144 maintain a corresponding deduplication database that stores deduplication information (e.g., datablock signatures). Examples of such a configuration are provided in U.S. Pat. Pub. No. 2012/0150826, which is incorporated by reference herein. Instead of or in combination with “target-side” deduplication, deduplication can also be performed on the “source-side” (or “client-side”), e.g., to reduce the amount of traffic between the media agents 144 and the client computing device(s) 102 and/or reduce redundant data stored in the primary storage devices 104. According to various implementations, one or more of the storage devices of the target-side and/or source-side of an operation can be cloud-based storage devices. Thus, the target-side and/or source-side deduplication can be cloud-based deduplication. In particular, as discussed previously, the storage manager 140 may communicate with other components within the information management system 100 via network protocols and cloud service provider APIs to facilitate cloud-based deduplication/single instancing. Examples of such deduplication techniques are provided in U.S. Pat. Pub. No. 2012/0150818, which is incorporated by reference herein. Some other compatible deduplication/single instancing techniques are described in U.S. Pat. Pub. Nos. 2006/0224846 and 2009/0319534, which are incorporated by reference herein.
Information Lifecycle Management and Hierarchical Storage Management Operations
In some embodiments, files and other data over their lifetime move from more expensive, quick access storage to less expensive, slower access storage. Operations associated with moving data through various tiers of storage are sometimes referred to as information lifecycle management (ILM) operations.
One type of ILM operation is a hierarchical storage management (HSM) operation. A HSM operation is generally an operation for automatically moving data between classes of storage devices, such as between high-cost and low-cost storage devices. For instance, an HSM operation may involve movement of data from primary storage devices 104 to secondary storage devices 108, or between tiers of secondary storage devices 108. With each tier, the storage devices may be progressively relatively cheaper, have relatively slower access/restore times, etc. For example, movement of data between tiers may occur as data becomes less important over time.
In some embodiments, an HSM operation is similar to an archive operation in that creating an HSM copy may (though not always) involve deleting some of the source data, e.g., according to one or more criteria related to the source data. For example, an HSM copy may include data from primary data 112 or a secondary copy 116 that is larger than a given size threshold or older than a given age threshold and that is stored in a backup format.
Often, and unlike some types of archive copies, HSM data that is removed or aged from the source is replaced by a logical reference pointer or stub. The reference pointer or stub can be stored in the primary storage device 104 (or other source storage device, such as a secondary storage device 108) to replace the deleted source data and to point to or otherwise indicate the new location in a secondary storage device 108.
According to one example, files are generally moved between higher and lower cost storage depending on how often the files are accessed. When a user requests access to the HSM data that has been removed or migrated, the information management system 100 uses the stub to locate the data and may make recovery of the data appear transparent, even though the HSM data may be stored at a location different from other source data. In this manner, the data appears to the user (e.g., in file system browsing windows and the like) as if it still resides in the source location (e.g., in a primary storage device 104). The stub may also include some metadata associated with the corresponding data, so that a file system and/or application can provide some information about the data object and/or a limited-functionality version (e.g., a preview) of the data object.
An HSM copy may be stored in a format other than the native application format (e.g., where the data is compressed, encrypted, deduplicated, and/or otherwise modified from the original native application format). In some cases, copies which involve the removal of data from source storage and the maintenance of stub or other logical reference information on source storage may be referred to generally as “on-line archive copies”. On the other hand, copies which involve the removal of data from source storage without the maintenance of stub or other logical reference information on source storage may be referred to as “off-line archive copies”. Examples of HSM and ILM techniques are provided in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.
Auxiliary Copy and Disaster Recovery Operations
An auxiliary copy is generally a copy operation in which a copy is created of an existing secondary copy 116. For instance, an initial secondary copy 116 may be generated using or otherwise be derived from primary data 112 (or other data residing in the secondary storage subsystem 118), whereas an auxiliary copy is generated from the initial secondary copy 116. Auxiliary copies can be used to create additional standby copies of data and may reside on different secondary storage devices 108 than the initial secondary copies 116. Thus, auxiliary copies can be used for recovery purposes if initial secondary copies 116 become unavailable. Exemplary compatible auxiliary copy techniques are described in further detail in U.S. Pat. No. 8,230,195, which is incorporated by reference herein.
The information management system 100 may also perform disaster recovery operations that make or retain disaster recovery copies, often as secondary, high-availability disk copies. The information management system 100 may create secondary disk copies and store the copies at disaster recovery locations using auxiliary copy or replication operations, such as continuous data replication technologies. Depending on the particular data protection goals, disaster recovery locations can be remote from the client computing devices 102 and primary storage devices 104, remote from some or all of the secondary storage devices 108, or both.
Data Analysis, Reporting, and Management Operations
Data analysis, reporting, and management operations can be different than data movement operations in that they do not necessarily involve the copying, migration or other transfer of data (e.g., primary data 112 or secondary copies 116) between different locations in the system. For instance, data analysis operations may involve processing (e.g., offline processing) or modification of already stored primary data 112 and/or secondary copies 116. However, in some embodiments data analysis operations are performed in conjunction with data movement operations. Some data analysis operations include content indexing operations and classification operations which can be useful in leveraging the data under management to provide enhanced search and other features. Other data analysis operations such as compression and encryption can provide data reduction and security benefits, respectively.
Classification Operations/Content Indexing
In some embodiments, the information management system 100 analyzes and indexes characteristics, content, and metadata associated with the primary data 112 and/or secondary copies 116. The content indexing can be used to identify files or other data objects having pre-defined content (e.g., user-defined keywords or phrases, other keywords/phrases that are not defined by a user, etc.), and/or metadata (e.g., email metadata such as “to”, “from”, “cc”, “bcc”, attachment name, received time, etc.).
The information management system 100 generally organizes and catalogues the results in a content index, which may be stored within the media agent database 152, for example. The content index can also include the storage locations of (or pointer references to) the indexed data in the primary data 112 or secondary copies 116, as appropriate. The results may also be stored, in the form of a content index database or otherwise, elsewhere in the information management system 100 (e.g., in the primary storage devices 104, or in the secondary storage device 108). Such index data provides the storage manager 140 or another component with an efficient mechanism for locating primary data 112 and/or secondary copies 116 of data objects that match particular criteria.
For instance, search criteria can be specified by a user through user interface 158 of the storage manager 140. In some cases, the information management system 100 analyzes data and/or metadata in secondary copies 116 to create an “off-line” content index, without significantly impacting the performance of the client computing devices 102. Depending on the embodiment, the system can also implement “on-line” content indexing, e.g., of primary data 112. Examples of compatible content indexing techniques are provided in U.S. Pat. No. 8,170,995, which is incorporated by reference herein.
One or more components can be configured to scan data and/or associated metadata for classification purposes to populate a database (or other data structure) of information, which can be referred to as a “data classification database” or a “metabase”. Depending on the embodiment, the data classification database(s) can be organized in a variety of different ways, including centralization, logical sub-divisions, and/or physical sub-divisions. For instance, one or more centralized data classification databases may be associated with different subsystems or tiers within the information management system 100. As an example, there may be a first centralized metabase associated with the primary storage subsystem 117 and a second centralized metabase associated with the secondary storage subsystem 118. In other cases, there may be one or more metabases associated with individual components, e.g., client computing devices 102 and/or media agents 144. In some embodiments, a data classification database (metabase) may reside as one or more data structures within management database 146, or may be otherwise associated with storage manager 140.
In some cases, the metabase(s) may be included in separate database(s) and/or on separate storage device(s) from primary data 112 and/or secondary copies 116, such that operations related to the metabase do not significantly impact performance on other components in the information management system 100. In other cases, the metabase(s) may be stored along with primary data 112 and/or secondary copies 116. Files or other data objects can be associated with identifiers (e.g., tag entries, etc.) in the media agent 144 (or other indices) to facilitate searches of stored data objects. Among a number of other benefits, the metabase can also allow efficient, automatic identification of files or other data objects to associate with secondary copy or other information management operations (e.g., in lieu of scanning an entire file system). Examples of compatible metabases and data classification operations are provided in U.S. Pat. Nos. 8,229,954 and 7,747,579, which are incorporated by reference herein.
Encryption Operations
The information management system 100 in some cases is configured to process data (e.g., files or other data objects, secondary copies 116, etc.), according to an appropriate encryption algorithm (e.g., Blowfish, Advanced Encryption Standard [AES], Triple Data Encryption Standard [3-DES], etc.) to limit access and provide data security in the information management system 100. The information management system 100 in some cases encrypts the data at the client level, such that the client computing devices 102 (e.g., the data agents 142) encrypt the data prior to forwarding the data to other components, e.g., before sending the data to media agents 144 during a secondary copy operation. In such cases, the client computing device 102 may maintain or have access to an encryption key or passphrase for decrypting the data upon restore. Encryption can also occur when creating copies of secondary copies, e.g., when creating auxiliary copies or archive copies. In yet further embodiments, the secondary storage devices 108 can implement built-in, high performance hardware encryption.
Management and Reporting Operations
Certain embodiments leverage the integrated, ubiquitous nature of the information management system 100 to provide useful system-wide management and reporting functions. Examples of some compatible management and reporting techniques are provided in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.
Operations management can generally include monitoring and managing the health and performance of information management system 100 by, without limitation, performing error tracking, generating granular storage/performance metrics (e.g., job success/failure information, deduplication efficiency, etc.), generating storage modeling and costing information, and the like. As an example, a storage manager 140 or other component in the information management system 100 may analyze traffic patterns and suggest and/or automatically route data via a particular route to minimize congestion. In some embodiments, the system can generate predictions relating to storage operations or storage operation information. Such predictions, which may be based on a trending analysis, may predict various network operations or resource usage, such as network traffic levels, storage media use, use of bandwidth of communication links, use of media agent components, etc. Further examples of traffic analysis, trend analysis, prediction generation, and the like are described in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.
In some configurations, a master storage manager 140 may track the status of storage operation cells in a hierarchy, such as the status of jobs, system components, system resources, and other items, by communicating with storage managers 140 (or other components) in the respective storage operation cells. Moreover, the master storage manager 140 may track the status of its associated storage operation cells and information management operations by receiving periodic status updates from the storage managers 140 (or other components) in the respective cells regarding jobs, system components, system resources, and other items. In some embodiments, a master storage manager 140 may store status information and other information regarding its associated storage operation cells and other system information in its index 150 (or other location).
The master storage manager 140 or other component may also determine whether certain storage-related criteria or other criteria are satisfied, and perform an action or trigger event (e.g., data migration) in response to the criteria being satisfied, such as where a storage threshold is met for a particular volume, or where inadequate protection exists for certain data. For instance, in some embodiments, data from one or more storage operation cells is used to dynamically and automatically mitigate recognized risks, and/or to advise users of risks or suggest actions to mitigate these risks. For example, an information management policy may specify certain requirements (e.g., that a storage device should maintain a certain amount of free space, that secondary copies should occur at a particular interval, that data should be aged and migrated to other storage after a particular period, that data on a secondary volume should always have a certain level of availability and be restorable within a given time period, that data on a secondary volume may be mirrored or otherwise migrated to a specified number of other volumes, etc.). If a risk condition or other criterion is triggered, the system may notify the user of these conditions and may suggest (or automatically implement) an action to mitigate or otherwise address the risk. For example, the system may indicate that data from a primary copy 112 should be migrated to a secondary storage device 108 to free space on the primary storage device 104. Examples of the use of risk factors and other triggering criteria are described in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.
In some embodiments, the system 100 may also determine whether a metric or other indication satisfies particular storage criteria and, if so, perform an action. For example, as previously described, a storage policy or other definition might indicate that a storage manager 140 should initiate a particular action if a storage metric or other indication drops below or otherwise fails to satisfy specified criteria such as a threshold of data protection. Examples of such metrics are described in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.
In some embodiments, risk factors may be quantified into certain measurable service or risk levels for ease of comprehension. For example, certain applications and associated data may be considered to be more important by an enterprise than other data and services. Financial compliance data, for example, may be of greater importance than marketing materials, etc. Network administrators may assign priority values or “weights” to certain data and/or applications, corresponding to the relative importance. The level of compliance of storage operations specified for these applications may also be assigned a certain value. Thus, the health, impact, and overall importance of a service may be determined, such as by measuring the compliance value and calculating the product of the priority value and the compliance value to determine the “service level” and comparing it to certain operational thresholds to determine whether it is acceptable. Further examples of the service level determination are provided in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.
The system 100 may additionally calculate data costing and data availability associated with information management operation cells according to an embodiment of the invention. For instance, data received from the cell may be used in conjunction with hardware-related information and other information about system elements to determine the cost of storage and/or the availability of particular data in the system. Exemplary information generated could include how fast a particular department is using up available storage space, how long data would take to recover over a particular system pathway from a particular secondary storage device, costs over time, etc. Moreover, in some embodiments, such information may be used to determine or predict the overall cost associated with the storage of certain information. The cost associated with hosting a certain application may be based, at least in part, on the type of media on which the data resides, for example. Storage devices may be assigned to a particular cost categories, for example. Further examples of costing techniques are described in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.
Any of the above types of information (e.g., information related to trending, predictions, job, cell or component status, risk, service level, costing, etc.) can generally be provided to users via the user interface 158 in a single, integrated view or console (not shown). The console may support a reporting capability that allows for the generation of a variety of reports, which may be tailored to a particular aspect of information management. Report types may include: scheduling, event management, media management and data aging. Available reports may also include backup history, data aging history, auxiliary copy history, job history, library and drive, media in library, restore history, and storage policy, etc., without limitation. Such reports may be specified and created at a certain point in time as a system analysis, forecasting, or provisioning tool. Integrated reports may also be generated that illustrate storage and performance metrics, risks and storage costing information. Moreover, users may create their own reports based on specific needs.
The integrated user interface 158 can include an option to show a “virtual view” of the system that graphically depicts the various components in the system using appropriate icons. As one example, the user interface 158 may provide a graphical depiction of one or more primary storage devices 104, the secondary storage devices 108, data agents 142 and/or media agents 144, and their relationship to one another in the information management system 100. The operations management functionality can facilitate planning and decision-making. For example, in some embodiments, a user may view the status of some or all jobs as well as the status of each component of the information management system 100. Users may then plan and make decisions based on this data. For instance, a user may view high-level information regarding storage operations for the information management system 100, such as job status, component status, resource status (e.g., communication pathways, etc.), and other information. The user may also drill down or use other means to obtain more detailed information regarding a particular component, job, or the like. Further examples of some reporting techniques and associated interfaces providing an integrated view of an information management system are provided in U.S. Pat. No. 7,343,453, which is incorporated by reference herein.
The information management system 100 can also be configured to perform system-wide e-discovery operations in some embodiments. In general, e-discovery operations provide a unified collection and search capability for data in the system, such as data stored in the secondary storage devices 108 (e.g., backups, archives, or other secondary copies 116). For example, the information management system 100 may construct and maintain a virtual repository for data stored in the information management system 100 that is integrated across source applications 110, different storage device types, etc. According to some embodiments, e-discovery utilizes other techniques described herein, such as data classification and/or content indexing.
Information Management Policies
As indicated previously, an information management policy 148 can include a data structure or other information source that specifies a set of parameters (e.g., criteria and rules) associated with secondary copy and/or other information management operations.
One type of information management policy 148 is a storage policy. According to certain embodiments, a storage policy generally comprises a data structure or other information source that defines (or includes information sufficient to determine) a set of preferences or other criteria for performing information management operations. Storage policies can include one or more of the following items: (1) what data will be associated with the storage policy; (2) a destination to which the data will be stored; (3) datapath information specifying how the data will be communicated to the destination; (4) the type of storage operation to be performed; and (5) retention information specifying how long the data will be retained at the destination (see, e.g.,
As an illustrative example, data associated with a storage policy can be logically organized into groups. In some cases, these logical groupings can be referred to as “sub-clients”. A sub-client may represent static or dynamic associations of portions of a data volume. Sub-clients may represent mutually exclusive portions. Thus, in certain embodiments, a portion of data may be given a label and the association is stored as a static entity in an index, database or other storage location. Sub-clients may also be used as an effective administrative scheme of organizing data according to data type, department within the enterprise, storage preferences, or the like. Depending on the configuration, sub-clients can correspond to files, folders, virtual machines, databases, etc. In one exemplary scenario, an administrator may find it preferable to separate e-mail data from financial data using two different sub-clients.
A storage policy can define where data is stored by specifying a target or destination storage device (or group of storage devices). For instance, where the secondary storage device 108 includes a group of disk libraries, the storage policy may specify a particular disk library for storing the sub-clients associated with the policy. As another example, where the secondary storage devices 108 include one or more tape libraries, the storage policy may specify a particular tape library for storing the sub-clients associated with the storage policy, and may also specify a drive pool and a tape pool defining a group of tape drives and a group of tapes, respectively, for use in storing the sub-client data. While information in the storage policy can be statically assigned in some cases, some or all of the information in the storage policy can also be dynamically determined based on criteria, which can be set forth in the storage policy. For instance, based on such criteria, a particular destination storage device(s) (or other parameter of the storage policy) may be determined based on characteristics associated with the data involved in a particular storage operation, device availability (e.g., availability of a secondary storage device 108 or a media agent 144), network status and conditions (e.g., identified bottlenecks), user credentials, and the like).
Datapath information can also be included in the storage policy. For instance, the storage policy may specify network pathways and components to utilize when moving the data to the destination storage device(s). In some embodiments, the storage policy specifies one or more media agents 144 for conveying data associated with the storage policy between the source (e.g., one or more host client computing devices 102) and destination (e.g., a particular target secondary storage device 108).
A storage policy can also specify the type(s) of operations associated with the storage policy, such as a backup, archive, snapshot, auxiliary copy, or the like. Retention information can specify how long the data will be kept, depending on organizational needs (e.g., a number of days, months, years, etc.)
Another type of information management policy 148 is a scheduling policy, which specifies when and how often to perform operations. Scheduling parameters may specify with what frequency (e.g., hourly, weekly, daily, event-based, etc.) or under what triggering conditions secondary copy or other information management operations will take place. Scheduling policies in some cases are associated with particular components, such as particular logical groupings of data associated with a storage policy (e.g., a sub-client), client computing device 102, and the like. In one configuration, a separate scheduling policy is maintained for particular logical groupings of data on a client computing device 102. The scheduling policy specifies that those logical groupings are to be moved to secondary storage devices 108 every hour according to storage policies associated with the respective sub-clients.
When adding a new client computing device 102, administrators can manually configure information management policies 148 and/or other settings, e.g., via the user interface 158. However, this can be an involved process resulting in delays, and it may be desirable to begin data protection operations quickly, without awaiting human intervention. Thus, in some embodiments, the information management system 100 automatically applies a default configuration to client computing device 102. As one example, when one or more data agent(s) 142 are installed on one or more client computing devices 102, the installation script may register the client computing device 102 with the storage manager 140, which in turn applies the default configuration to the new client computing device 102. In this manner, data protection operations can begin substantially immediately. The default configuration can include a default storage policy, for example, and can specify any appropriate information sufficient to begin data protection operations. This can include a type of data protection operation, scheduling information, a target secondary storage device 108, data path information (e.g., a particular media agent 144), and the like.
Other types of information management policies 148 are possible, including one or more audit (or security) policies. An audit policy is a set of preferences, rules and/or criteria that protect sensitive data in the information management system 100. For example, an audit policy may define “sensitive objects” as files or objects that contain particular keywords (e.g., “confidential,” or “privileged”) and/or are associated with particular keywords (e.g., in metadata) or particular flags (e.g., in metadata identifying a document or email as personal, confidential, etc.). An audit policy may further specify rules for handling sensitive objects. As an example, an audit policy may require that a reviewer approve the transfer of any sensitive objects to a cloud storage site, and that if approval is denied for a particular sensitive object, the sensitive object should be transferred to a local primary storage device 104 instead. To facilitate this approval, the audit policy may further specify how a secondary storage computing device 106 or other system component should notify a reviewer that a sensitive object is slated for transfer.
Another type of information management policy 148 is a provisioning policy. A provisioning policy can include a set of preferences, priorities, rules, and/or criteria that specify how client computing devices 102 (or groups thereof) may utilize system resources, such as available storage on cloud storage and/or network bandwidth. A provisioning policy specifies, for example, data quotas for particular client computing devices 102 (e.g., a number of gigabytes that can be stored monthly, quarterly or annually). The storage manager 140 or other components may enforce the provisioning policy. For instance, the media agents 144 may enforce the policy when transferring data to secondary storage devices 108. If a client computing device 102 exceeds a quota, a budget for the client computing device 102 (or associated department) is adjusted accordingly or an alert may trigger.
While the above types of information management policies 148 have been described as separate policies, one or more of these can be generally combined into a single information management policy 148. For instance, a storage policy may also include or otherwise be associated with one or more scheduling, audit, or provisioning policies or operational parameters thereof. Moreover, while storage policies are typically associated with moving and storing data, other policies may be associated with other types of information management operations. The following is a non-exhaustive list of items the information management policies 148 may specify:
Policies can additionally specify or depend on a variety of historical or current criteria that may be used to determine which rules to apply to a particular data object, system component, or information management operation, such as:
As indicated by the dashed box, the second media agent 144B and the tape library 108B are “off-site”, and may therefore be remotely located from the other components in the information management system 100 (e.g., in a different city, office building, etc.). Indeed, “off-site” may refer to a magnetic tape located in storage, which must be manually retrieved and loaded into a tape drive to be read. In this manner, information stored on the tape library 108B may provide protection in the event of a disaster or other failure.
The file system sub-client and its associated primary data 112A in certain embodiments generally comprise information generated by the file system and/or operating system of the client computing device 102, and can include, for example, file system data (e.g., regular files, file tables, mount points, etc.), operating system data (e.g., registries, event logs, etc.), and the like. The e-mail sub-client, on the other hand, and its associated primary data 112B, include data generated by an e-mail application operating on the client computing device 102, and can include mailbox information, folder information, emails, attachments, associated database information, and the like. As described above, the sub-clients can be logical containers, and the data included in the corresponding primary data 112A, 112B may or may not be stored contiguously.
The exemplary storage policy 148A includes backup copy preferences (or rule set) 160, disaster recovery copy preferences rule set 162, and compliance copy preferences or rule set 164. The backup copy rule set 160 specifies that it is associated with a file system sub-client 166 and an email sub-client 168. Each of these sub-clients 166, 168 are associated with the particular client computing device 102. The backup copy rule set 160 further specifies that the backup operation will be written to the disk library 108A, and designates a particular media agent 144A to convey the data to the disk library 108A. Finally, the backup copy rule set 160 specifies that backup copies created according to the rule set 160 are scheduled to be generated on an hourly basis and to be retained for 30 days. In some other embodiments, scheduling information is not included in the storage policy 148A, and is instead specified by a separate scheduling policy.
The disaster recovery copy rule set 162 is associated with the same two sub-clients 166, 168. However, the disaster recovery copy rule set 162 is associated with the tape library 108B, unlike the backup copy rule set 160. Moreover, the disaster recovery copy rule set 162 specifies that a different media agent, namely 144B, will be used to convey the data to the tape library 108B. As indicated, disaster recovery copies created according to the rule set 162 will be retained for 60 days, and will be generated on a daily basis. Disaster recovery copies generated according to the disaster recovery copy rule set 162 can provide protection in the event of a disaster or other catastrophic data loss that would affect the backup copy 116A maintained on the disk library 108A.
The compliance copy rule set 164 is only associated with the email sub-client 168, and not the file system sub-client 166. Compliance copies generated according to the compliance copy rule set 164 will therefore not include primary data 112A from the file system sub-client 166. For instance, the organization may be under an obligation to store and maintain copies of email data for a particular period of time (e.g., 10 years) to comply with state or federal regulations, while similar regulations do not apply to the file system data. The compliance copy rule set 164 is associated with the same tape library 108B and media agent 144B as the disaster recovery copy rule set 162, although a different storage device or media agent could be used in other embodiments. Finally, the compliance copy rule set 164 specifies that copies generated under the compliance copy rule set 164 will be retained for 10 years, and will be generated on a quarterly basis.
At step 1, the storage manager 140 initiates a backup operation according to the backup copy rule set 160. For instance, a scheduling service running on the storage manager 140 accesses scheduling information from the backup copy rule set 160 or a separate scheduling policy associated with the client computing device 102, and initiates a backup copy operation on an hourly basis. Thus, at the scheduled time slot the storage manager 140 sends instructions to the client computing device 102 (i.e., to both data agent 142A and data agent 142B) to begin the backup operation.
At step 2, the file system data agent 142A and the email data agent 142B operating on the client computing device 102 respond to the instructions received from the storage manager 140 by accessing and processing the primary data 112A, 112B involved in the copy operation, which can be found in primary storage device 104. Because the operation is a backup copy operation, the data agent(s) 142A, 142B may format the data into a backup format or otherwise process the data.
At step 3, the client computing device 102 communicates the retrieved, processed data to the first media agent 144A, as directed by the storage manager 140, according to the backup copy rule set 160. In some other embodiments, the information management system 100 may implement a load-balancing, availability-based, or other appropriate algorithm to select from the available set of media agents 144A, 144B. Regardless of the manner the media agent 144A is selected, the storage manager 140 may further keep a record in the storage manager database 146 of the association between the selected media agent 144A and the client computing device 102 and/or between the selected media agent 144A and the backup copy 116A.
The target media agent 144A receives the data from the client computing device 102, and at step 4 conveys the data to the disk library 108A to create the backup copy 116A, again at the direction of the storage manager 140 and according to the backup copy rule set 160. The secondary storage device 108A can be selected in other ways. For instance, the media agent 144A may have a dedicated association with a particular secondary storage device(s), or the storage manager 140 or media agent 144A may select from a plurality of secondary storage devices, e.g., according to availability, using one of the techniques described in U.S. Pat. No. 7,246,207, which is incorporated by reference herein.
The media agent 144A can also update its index 153 to include data and/or metadata related to the backup copy 116A, such as information indicating where the backup copy 116A resides on the disk library 108A, data and metadata for cache retrieval, etc. The storage manager 140 may similarly update its index 150 to include information relating to the storage operation, such as information relating to the type of storage operation, a physical location associated with one or more copies created by the storage operation, the time the storage operation was performed, status information relating to the storage operation, the components involved in the storage operation, and the like. In some cases, the storage manager 140 may update its index 150 to include some or all of the information stored in the index 153 of the media agent 144A. After the 30 day retention period expires, the storage manager 140 instructs the media agent 144A to delete the backup copy 116A from the disk library 108A. Indexes 150 and/or 153 are updated accordingly.
At step 5, the storage manager 140 initiates the creation of a disaster recovery copy 116B according to the disaster recovery copy rule set 162.
At step 6, illustratively based on the instructions received from the storage manager 140 at step 5, the specified media agent 144B retrieves the most recent backup copy 116A from the disk library 108A.
At step 7, again at the direction of the storage manager 140 and as specified in the disaster recovery copy rule set 162, the media agent 144B uses the retrieved data to create a disaster recovery copy 116B on the tape library 108B. In some cases, the disaster recovery copy 116B is a direct, mirror copy of the backup copy 116A, and remains in the backup format. In other embodiments, the disaster recovery copy 116B may be generated in some other manner, such as by using the primary data 112A, 112B from the primary storage device 104 as source data. The disaster recovery copy operation is initiated once a day and the disaster recovery copies 116B are deleted after 60 days; indexes are updated accordingly when/after each information management operation is executed/completed.
At step 8, the storage manager 140 initiates the creation of a compliance copy 116C, according to the compliance copy rule set 164. For instance, the storage manager 140 instructs the media agent 144B to create the compliance copy 116C on the tape library 108B at step 9, as specified in the compliance copy rule set 164. In the example, the compliance copy 116C is generated using the disaster recovery copy 116B. In other embodiments, the compliance copy 116C is instead generated using either the primary data 112B corresponding to the email sub-client or using the backup copy 116A from the disk library 108A as source data. As specified, in the illustrated example, compliance copies 116C are created quarterly, and are deleted after ten years, and indexes are kept up-to-date accordingly.
While not shown in
In other cases, a media agent may be selected for use in the restore operation based on a load balancing algorithm, an availability based algorithm, or other criteria. The selected media agent 144A retrieves the data from the disk library 108A. For instance, the media agent 144A may access its index 153 to identify a location of the backup copy 116A on the disk library 108A, or may access location information residing on the disk 108A itself.
When the backup copy 116A was recently created or accessed, the media agent 144A accesses a cached version of the backup copy 116A residing in the index 153, without having to access the disk library 108A for some or all of the data. Once it has retrieved the backup copy 116A, the media agent 144A communicates the data to the source client computing device 102. Upon receipt, the file system data agent 142A and the email data agent 142B may unpackage (e.g., restore from a backup format to the native application format) the data in the backup copy 116A and restore the unpackaged data to the primary storage device 104.
Exemplary Applications of Storage Policies
The storage manager 140 may permit a user to specify aspects of the storage policy 148A. For example, the storage policy can be modified to include information governance policies to define how data should be managed in order to comply with a certain regulation or business objective. The various policies may be stored, for example, in the management database 146. An information governance policy may comprise a classification policy, which is described herein. An information governance policy may align with one or more compliance tasks that are imposed by regulations or business requirements. Examples of information governance policies might include a Sarbanes-Oxley policy, a HIPAA policy, an electronic discovery (E-Discovery) policy, and so on.
Information governance policies allow administrators to obtain different perspectives on all of an organization's online and offline data, without the need for a dedicated data silo created solely for each different viewpoint. As described previously, the data storage systems herein build a centralized index that reflects the contents of a distributed data set that spans numerous clients and storage devices, including both primary and secondary copies, and online and offline copies. An organization may apply multiple information governance policies in a top-down manner over that unified data set and indexing schema in order to permit an organization to view and manipulate the single data set through different lenses, each of which is adapted to a particular compliance or business goal. Thus, for example, by applying an E-discovery policy and a Sarbanes-Oxley policy, two different groups of users in an organization can conduct two very different analyses of the same underlying physical set of data copies, which may be distributed throughout the organization and information management system.
A classification policy defines a taxonomy of classification terms or tags relevant to a compliance task and/or business objective. A classification policy may also associate a defined tag with a classification rule. A classification rule defines a particular combination of criteria, such as users who have created, accessed or modified a document or data object; file or application types; content or metadata keywords; clients or storage locations; dates of data creation and/or access; review status or other status within a workflow (e.g., reviewed or un-reviewed); modification times or types of modifications; and/or any other data attributes in any combination, without limitation. A classification rule may also be defined using other classification tags in the taxonomy. The various criteria used to define a classification rule may be combined in any suitable fashion, for example, via Boolean operators, to define a complex classification rule. As an example, an E-discovery classification policy might define a classification tag “privileged” that is associated with documents or data objects that (1) were created or modified by legal department staff, or (2) were sent to or received from outside counsel via email, or (3) contain one of the following keywords: “privileged” or “attorney” or “counsel”, or other like terms.
One specific type of classification tag, which may be added to an index at the time of indexing, is an entity tag. An entity tag may be, for example, any content that matches a defined data mask format. Examples of entity tags might include, e.g., social security numbers (e.g., any numerical content matching the formatting mask XXX-XX-XXXX), credit card numbers (e.g., content having a 13-16 digit string of numbers), SKU numbers, product numbers, etc.
A user may define a classification policy by indicating criteria, parameters or descriptors of the policy via a graphical user interface, such as a form or page with fields to be filled in, pull-down menus or entries allowing one or more of several options to be selected, buttons, sliders, hypertext links or other known user interface tools for receiving user input, etc. For example, a user may define certain entity tags, such as a particular product number or project ID code that is relevant in the organization. In some implementations, the classification policy can be implemented using cloud-based techniques. For example, the storage devices may be cloud storage devices, and the storage manager 140 may execute cloud service provider API over a network to classify data stored on cloud storage devices.
Exemplary Secondary Copy Formatting
The formatting and structure of secondary copies 116 can vary, depending on the embodiment. In some cases, secondary copies 116 are formatted as a series of logical data units or “chunks” (e.g., 512 MB, 1 GB, 2 GB, 4 GB, or 8 GB chunks). This can facilitate efficient communication and writing to secondary storage devices 108, e.g., according to resource availability. For example, a single secondary copy 116 may be written on a chunk-by-chunk basis to a single secondary storage device 108 or across multiple secondary storage devices 108. In some cases, users can select different chunk sizes, e.g., to improve throughput to tape storage devices.
Generally, each chunk can include a header and a payload. The payload can include files (or other data units) or subsets thereof included in the chunk, whereas the chunk header generally includes metadata relating to the chunk, some or all of which may be derived from the payload. For example, during a secondary copy operation, the media agent 144, storage manager 140, or other component may divide the associated files into chunks and generate headers for each chunk by processing the constituent files. The headers can include a variety of information such as file identifier(s), volume(s), offset(s), or other information associated with the payload data items, a chunk sequence number, etc. Importantly, in addition to being stored with the secondary copy 116 on the secondary storage device 108, the chunk headers can also be stored to the index 153 of the associated media agent(s) 144 and/or the index 150. This is useful in some cases for providing faster processing of secondary copies 116 during restores or other operations. In some cases, once a chunk is successfully transferred to a secondary storage device 108, the secondary storage device 108 returns an indication of receipt, e.g., to the media agent 144 and/or storage manager 140, which may update their respective indexes 153, 150 accordingly. During restore, chunks may be processed (e.g., by the media agent 144) according to the information in the chunk header to reassemble the files.
Data can also be communicated within the information management system 100 in data channels that connect the client computing devices 102 to the secondary storage devices 108. These data channels can be referred to as “data streams”, and multiple data streams can be employed to parallelize an information management operation, improving data transfer rate, among providing other advantages. Example data formatting techniques including techniques involving data streaming, chunking, and the use of other data structures in creating copies (e.g., secondary copies) are described in U.S. Pat. Nos. 7,315,923 and 8,156,086, and 8,578,120, each of which is incorporated by reference herein.
Referring to
As an example, the data structures 180 illustrated in
If the operating system of the secondary storage computing device 106 on which the media agent 144 operates supports sparse files, then when the media agent 144 creates container files 190/191/193, it can create them as sparse files. A sparse file is type of file that may include empty space (e.g., a sparse file may have real data within it, such as at the beginning of the file and/or at the end of the file, but may also have empty space in it that is not storing actual data, such as a contiguous range of bytes all having a value of zero). Having the container files 190/191/193 be sparse files allows the media agent 144 to free up space in the container files 190/191/193 when blocks of data in the container files 190/191/193 no longer need to be stored on the storage devices. In some examples, the media agent 144 creates a new container file 190/191/193 when a container file 190/191/193 either includes 100 blocks of data or when the size of the container file 190 exceeds 50 MB. In other examples, the media agent 144 creates a new container file 190/191/193 when a container file 190/191/193 satisfies other criteria (e.g., it contains from approximately 100 to approximately 1000 blocks or when its size exceeds approximately 50 MB to 1 GB).
In some cases, a file on which a storage operation is performed may comprise a large number of data blocks. For example, a 100 MB file may comprise 400 data blocks of size 256 KB. If such a file is to be stored, its data blocks may span more than one container file, or even more than one chunk folder. As another example, a database file of 20 GB may comprise over 40,000 data blocks of size 512 KB. If such a database file is to be stored, its data blocks will likely span multiple container files, multiple chunk folders, and potentially multiple volume folders. Restoring such files may require accessing multiple container files, chunk folders, and/or volume folders to obtain the requisite data blocks.
System Overview
The systems and methods described with respect to
While the embodiments are described herein with respect to incremental backups, this is not meant to be limiting. The VM backup techniques disclosed herein may be used with differential backups, auxiliary copy operations, and/or the like. Furthermore, the techniques disclosed herein may not be limited to VM backups. For example, the techniques disclosed herein can be applied to the backup of any large file that may be backed up in chunks, such as a hard disk, a database, etc.
Exemplary Information Management System for Implementing Virtual Machine (VM) Backup Using a Change Block Bitmap File
Moreover, depending on the embodiment, the system 200 of
The term virtualization in the computing arts can refer to the creation of a virtual instance of an entity (e.g., a hardware platform, operating system, storage device or network resource, etc.) that behaves like a physical instance. For instance, a virtual machine can be a software representation of a physical machine. Enterprises may use virtualization for a variety of purposes, such as to reduce the number of physical servers or other computers by instantiating multiple virtual machines on a single physical host computer. In this manner, virtualization can be used to centralize administrative tasks while improving scalability and workloads, and can be an important tool for maximizing hardware utilization. Using virtualization techniques, many (e.g., hundreds or thousands) of virtual machines can be instantiated on a single host device. The host device can contain significant amounts of memory and computing power in order to execute the virtual machines, which can be referred to as “clients” or “guests.” For example, the host device may include a hypervisor that is used to execute the virtual machines. Although each virtual client can be logically viewed as a stand-alone device, in actuality the virtual client machines can share underlying hardware with the other virtual machines residing on the host.
Often, VMs are backed up so that the VMs can be restored to a previous point in time in the event of data corruption or the like. The backups may be full backups (e.g., all of the data of the VM is backed up) or the backups may be incremental backups (e.g., only the data of the VM that changed since the last backup is backed up). Incremental backups may be useful in that a reduced amount of memory is needed to store a restorable backup. Generally, for incremental backups, to determine the data of the VM that changed since the last backup, the system runs a check, such as a cyclic redundancy check (CRC), on each sector in a virtual hard disk associated with the VM. The CRC may indicate whether data in the respective sector has changed (e.g., the CRC may be based on the data in the sector as of the last backup, and a change in the data in the sector would result in the CRC failing). If the data in the sector has changed, the sector data is included in the incremental backup.
Performing the CRC check may involve performing a read operation on each sector in the virtual hard disk in addition to the actual CRC comparison. Thus, even though an incremental backup may include a subset of all of the data stored in the virtual hard disk, the entire virtual hard disk is still accessed to determine what data to include in the backup. In some cases, these read operations and/or CRC comparisons are more resource intensive than the actual transmission of data to the secondary storage devices, such as the secondary storage devices 208. Accordingly, while the incremental backups may reduce memory consumption, the incremental backups may not reduce processor usage or latency and the VM may suffer a performance penalty.
Accordingly, the system 200 may address these and other challenges by implementing a VM backup procedure that reduces a number of read operations on the virtual hard disk of the VM and/or that eliminates or reduces the CRC comparisons. For example, the driver 228 of the hypervisor 227 may be located within the I/O stack of the hypervisor 227. The driver 228 may be a computing module that monitors the I/O operations generated by one or more VMs 225 that are run by the hypervisor 227. In an embodiment, the VMs 225 can each write data to a virtual hard disk that virtualizes a physical hard disk. The data written to the virtual hard disk can be stored in a virtual hard disk file. Each virtual hard disk file may be accessible by one VM 225 at a time. However, the virtual hard disk files may be transferrable such that the virtual hard disk file can be accessed by a first VM 225 and later (after the first VM 225 closes the virtual hard disk file) accessed by a second VM 225. The first and second VMs 225 can be run by the same hypervisor 227 or can be run by different hypervisors 227.
When the driver 228 intercepts a command issued by a VM 225 to open a virtual hard disk file, the driver 228 may begin monitoring write operations from the VM 225 to the virtual hard disk file. As a VM 225 generates a write operation to modify data in a sector of the virtual hard disk of the VM 225, the driver 228 may intercept the write operation and identify the sector that is being modified. The sector may correspond to a particular offset in the virtual hard disk file. The VM 225 may include a change block bitmap file that includes a unique bit entry associated with each extent (e.g., where one extent includes several sectors, such as 100 sectors) in the virtual hard disk. The change block bitmap file may be stored in parallel with the virtual hard disk file in the volume of the VM 225. Once the driver 228 has identified the sector that is being modified, the driver 228 may locate the bit entry in the change block bitmap file that corresponds with an extent that includes the identified sector and change the bit entry such that it indicates that the extent has been modified (e.g., by changing the bit entry from a logical 0 to a logical 1).
The driver 228 may continue modifying the change block bitmap file until the storage manager 240 instructs the client 202 and/or the media agent 244 (e.g., based on a policy defined by a user) to begin an incremental backup. As part of the incremental backup process, the VM data agent 242 accesses the change block bitmap file to identify the extents that have been modified. For each extent that has been modified as indicated by the change block bitmap file (e.g., each extent associated with a bit entry of logical 1 instead of logical 0), the VM data agent 242 reads the data corresponding to the respective extent in the virtual hard disk file and includes the data in the incremental backup. Once each appropriate extent has been accessed, the VM data agent 242 may transmit the incremental backup to the media agent 244 for storage in the secondary storage devices 208.
In an embodiment, a new change block bitmap file is created after each incremental backup occurs. Thus, each change block bitmap file may correspond with a time period (e.g., a time from when the change block bitmap file was created to a time when the incremental backup occurred). In this manner, a history of change block bitmap files may be stored such that the system 200 can identify what portions of the virtual hard disk changed during any given period of time.
In some embodiments, as the driver 228 intercepts write operations from the VM 225, the driver 228 selectively updates the change block bitmap file. For example, the driver 228 may intercept a write operation that indicates a first sector in the virtual hard disk is being modified. However, the first sector may have also been updated at a previous time and the change may be reflected in the change block bitmap file. Because the change block bitmap file indicates that a change occurred, not the actual data itself, it may not be necessary for the driver 228 to update the change block bitmap file.
Various hypervisors 227 may be able to run the same VM 225 at different times. For example, a first hypervisor 227 can run the VM 225 for a first period of time, and the device 228 of the first hypervisor 227 may update the change block bitmap file as described herein. At some point after the first period, the first hypervisor 227 may close the VM 225 and the VM 225 may be migrated to a second hypervisor 227 located on another client 202. Migration may occur because new hardware (e.g., new clients 202) was installed in the system 200, too many VMs 225 may be run by the same hypervisor 227, and/or the like. Migration may involve copying the entire volume of the VM 225 and transmitting the entire volume to the client 202 that includes the second hypervisor 227. Because the volume includes the virtual hard disk file and the change block bitmap file, both files may be transferred with the VM 225. The second hypervisor 227 can then start the VM 225 and continue to update the change block bitmap file, starting where the first hypervisor 227 left off. In some embodiments, the VM 225, when first initiated by the second hypervisor 227, sends a command to open the virtual hard disk file. This command may inform the driver 228 of the second hypervisor 227 that the virtual hard disk file exists and I/O operations to and/or from the virtual hard disk file should be monitored. In this manner, the second hypervisor 227 can continue to update the change block bitmap file and the change block bitmap file may be available to any hypervisor 227 that can run the VM 225.
In some cases, the second hypervisor 227 may not have a driver 228. Thus, the VM 225 may write to the virtual hard disk file without any corresponding updates to the change block bitmap file. If the VM 225 is migrated back to the first hypervisor 227 or to a third hypervisor 227, the respective hypervisor 227 may recognize that the virtual hard disk file was updated and the change block bitmap file was not (e.g., based on a timestamp that indicates the virtual hard disk file was last modified at a time later than the change block bitmap file). In such a situation, the respective hypervisor 227 may invalidate all changes to the change block bitmap file (e.g., wipe the change block bitmap file clean) and start over. The storage manager 240 may instruct the client 202 and/or the media agent 244 to begin a full backup of the VM 225 before a new change block bitmap file is created and updated to account for any changes made to the VM 225 since the change block bitmap file was last updated. The system 200 (e.g., the storage manager 240) may send instructions to disable change tracking using the change block bitmap file before the full backup occurs, and send instructions to re-enable the change tracking after the full backup occurs.
In some implementations, the embodiments disclosed herein can be integrated with a volume snapshot service (VSS) provider. For instance, the storage manager 240 may direct the VM data agent 242 and/or a selected media agent 244 to perform a snapshot operation using a VSS provider. The driver 228 may be configured to intercept VSS freeze and thaw events to control when to pause and resume tracking changes to the virtual hard disk file. For example, prior to providing instructions to perform the snapshot operation (e.g., before calling the VSS framework), the storage manager 240 instructs the driver 228 to prepare to start tracking changes to the virtual hard disk file using the change block bit map file. The VSS provider may then call the driver 228 and instruct the driver 228 to start tracking changes to the virtual hard disk file during a preset window of time (e.g., 10 seconds) before the snapshot is taken. The VSS provider and/or the storage manager 240 may instruct the driver 228 to stop tracking changes if the snapshot operation fails. The snapshot taken by the VSS provider may occur at the beginning of the backup operation (e.g., before data transfer begins). Thus, the VSS provider may instruct the driver 228 to begin tracking changes at the beginning of the backup operation. The driver 228 may generate a token that may include a time stamp indicating a time when the tracking began. The token can be stored locally on the client computing device 202 and/or in the data store 204. The token can be retrieved by the VM data agent 242 during subsequent incremental backup operations and passed to the driver 228 to identify changes that have occurred in the virtual hard disk file since the last backup. For example, upon receiving the token, the driver 228 may return a list of file offsets (which can be translated into virtual hard disk extents) that have changed since the time indicated by the time stamp in the token. Alternatively, the driver 228 may return a bitmap (such as the change block bitmap file) that includes data that can be used to identify the file offsets and/or extents.
In an embodiment, the VM 225 may write data to the virtual hard disk file 302, and the driver 228 intercepts these write operations. For example, when writing data to the virtual hard disk file 302, the I/O stack 328 may receive information from the VM 225 to perform a translation between a virtual location in the virtual hard disk file 302 (e.g., an offset in the virtual hard disk file 302) and a physical location in the local hard disk 306 to determine where to store the data in the local hard disk 306. The driver 228 may intercept these write commands when received by the I/O stack 328. The driver 228 may then perform the functions as described herein.
In an embodiment, the values in the bit entries 401-411 indicate whether any sector in the corresponding extent has been changed or has not been changed since the last backup. For example, a logical 1 may indicate that the extent has changed and a logical 0 may indicate that the extent has not changed.
Although not shown, the VM 225 may include a plurality of change block bitmap files 304. For example, each change block bitmap file 304 may correspond with a different period of time (e.g., a first change block bitmap file 304 may correspond with a period of time between a first incremental backup and a second incremental backup, a second change block bitmap file 304 may correspond with a period of time between a second incremental backup and a third incremental backup, etc.).
Exemplary Flow Diagrams for Implementing VM Backup Using Change Block Bitmap Files
At block 502, the system 200 receives an open operation that indicates a virtual hard disk file of a VM is accessed. The open operation may be generated by the VM when a hypervisor brings up the VM. The virtual hard disk file may be stored in a volume of the VM.
At block 504, the system 200 begins tracking the virtual hard disk file. For example, tracking may entail tracking I/O operations sent to and/or received from the virtual hard disk file. The tracking may occur by a driver of the hypervisor that is located with the I/O stack of the hypervisor.
At block 506, the system 200 receives a write operation from the VM that indicates that a first sector of the virtual hard disk file is modified. The write operation may be received by intercepting a command generated by the VM for the purpose of storing data in the virtual hard disk file. The command may be intercepted by the driver that is tracking the virtual hard disk file as the command passes through the I/O stack of the hypervisor.
At block 508, the system 200 modifies a change block bitmap file stored in the VM such that a location in the change block bitmap file that corresponds with the first sector indicates that the first sector is modified. For example, the change block bitmap file may include various entries associated with various extents in the virtual hard disk file, where each extent includes several sectors. The first sector may correspond to a first extent. Thus, the entry associated with the first extent may be modified to include a value that indicates that a change has occurred. In some embodiments, a logical 1 value indicates that a change has occurred and a logical 0 value indicates that a change has not occurred.
At block 602, the system 200 may initiate a backup operation. For instance, the storage manager 240 may, based on a storage policy, instruct a data agent such as the VM data agent 242 and/or a selected media agent 244 to perform a backup of a VM hard disk file. In response, the VM data agent 242 retrieves a change block bitmap file stored in a VM. For example, a data agent of the system 200 may retrieve the change block bitmap file, where the change block bitmap file is stored in a volume of the VM. In some embodiments, at block 602, the driver 228, VM data agent 242, or other appropriate entity first determines whether or not there exists a change block bitmap file associated with the virtual hard disk file. If so, the client computing device 202 loads the change block bit map file into memory. The driver 228 may additionally validate the virtual hard disk file against the change block bitmap file. For instance, the driver 228 can compare a time stamp included in the header of the change block bitmap file with a timestamp associated with the virtual hard disk file. If the time stamp of the change block bitmap file is older than the one associated with the virtual hard disk, the driver 228 may discard or wipe clean the change block bit map file because the changes were not validated. And, since the changes were not validated, the VM data agent 242 may revert to performing a full backup instead of an incremental backup. In the meantime, the system 200 may disable change tracking using the change block bitmap file, and re-enable the change tracking after the full backup. Re-enabling the change tracking may include creating a new change block bitmap file to track changes to the virtual hard disk file between the time of the full backup and the time of the next full or incremental backup.
In the event that no change block bit map file exists, the virtual machine data agent 242 may perform a full backup instead of an incremental. The driver 228 may create the change block bit map file at this time, or at or around the time the full backup operation completes, and then begin to track changes to the virtual hard disk file using the change block bit map file, as described above with respect to
In some embodiments, the initiated backup operation may be a snapshot operation. As discussed above, the storage manager 240 may direct the VM data agent 242 and/or a selected media agent 244 to perform a snapshot operation using a VSS provider. The driver 228 may be configured to intercept VSS freeze and thaw events to control when to pause and resume tracking changes to the virtual hard disk file. For example, prior to providing instructions to perform the snapshot operation (e.g., before calling the VSS framework), the storage manager 240 may instruct the driver 228 to prepare to start tracking changes to the virtual hard disk file using the change block bit map file. The VSS provider may then call the driver 228 and instruct the driver 228 to start tracking changes to the virtual hard disk file during a preset window of time (e.g., 10 seconds) before the snapshot is taken. The VSS provider and/or the storage manager 240 may instruct the driver 228 to stop tracking changes if the snapshot operation fails.
At block 604, the system 200 identifies one or more extents in the VM that have changed based on the retrieved change block bitmap file. For example, the data agent may parse the change block bitmap file to identify entries that indicate a corresponding extent in the virtual hard disk file has been modified.
At block 606, the system 200 reads, for each extent in the VM that changed, values for the respective extent stored in a virtual hard disk file. For example, the data agent may read values for each sector in each extent in the VM that changed. In some cases, not every sector in each extent may have updated data. However, the data in such sectors may nonetheless be included in the incremental backup.
At block 608, the system 200 stores the read values in a secondary storage device. In an embodiment, the read values are included as part of an incremental backup and the data agent transmits the incremental backup from the client 202 to the media agent 244 directly or indirectly via the storage manager 240. The media agent 244 then stores the incremental backup in the secondary storage device, such as the secondary storage device 208.
Example Embodiments
One aspect of the disclosure provides a system configured to backup a virtual machine. The system comprises a client device comprising computer hardware, where the client device includes: a virtual machine (VM) executed by a hypervisor, where the VM comprises a virtual hard disk file and a change block bitmap file, where the virtual hard disk file stores data associated with a virtual hard disk; a driver module under control of the hypervisor, where the driver module is configured to: intercept a first write operation generated by the VM to store data in a first sector, determine an identity of the first sector based on the intercepted write operation, determine an entry in the change block bitmap file that corresponds with the first sector, and modify the entry in the change block bitmap file to indicate that data in the first sector has changed; and a data agent configured to gather data for use in performance of an incremental backup of the VM based on the change block bitmap file in response to an instruction from a storage manager, where the incremental backup comprises the data in the first sector.
The system of the preceding paragraph can have any sub-combination of the following features: where the hypervisor comprises an I/O stack, and where the I/O stack comprises the driver module; where the data agent is further configured to: parse the change block bitmap file, identify each entry in the change block bitmap file that indicates that data in a sector associated with the respective entry has changed, for each identified entry, determine an associated sector and read data from the associated sector in the virtual hard disk file, and for each identified entry, include the read data in the incremental backup; where the driver is further configured to modify the entry in the change block bitmap file from a logical 0 to a logical 1 to indicate that data in the first sector has changed; where the virtual hard disk file and the change block bitmap file are stored in a volume of the VM; where the driver is further configured to: intercept an open operation generated by the VM to open the virtual hard disk file, and begin monitoring the virtual hard disk file in response to intercepting the open operation; where the change block bitmap file is associated with a first period of time; where the driver is further configured to generate a second change block bitmap file associated with a second period of time after the first period of time and store the second change block bitmap file in the VM; where the driver is configured to generate the second change block bitmap file after the data agent performs the incremental backup based on the change block bitmap file; and where the data agent is further configured to gather data for use in performance of a second incremental backup at a time after the incremental backup based on the second change block bitmap file.
Another aspect of the disclosure provides a method of backing up a virtual machine. The method comprises intercepting, by a driver under the control of a hypervisor which executes on a client computing device, a first write operation generated by a virtual machine (VM) to store data in a first sector of a virtual hard disk, where the VM is executed by the hypervisor, wherein the VM comprises a virtual hard disk file and a change block bitmap file, and where the virtual hard disk file stores data associated with the virtual hard disk; and, with the client computing device, determining an identity of the first sector based on the intercepted write operation, determining an entry in the change block bitmap file that corresponds with the first sector, and modifying the entry in the change block bitmap file to indicate that data in the first sector has changed.
The method of the preceding paragraph can have any sub-combination of the following features: where the method further comprises receiving an instruction from a storage manager to begin a backup of the VM and gathering data for use in performance of an incremental backup of the VM based on the change block bitmap file in response to the received instruction, where the incremental backup comprises the data in the first sector; where the method further comprises parsing the change block bitmap file, identifying each entry in the change block bitmap file that indicates that data in a sector associated with the respective entry has changed, for each identified entry, determining an associated sector and read data from the associated sector in the virtual hard disk file, and for each identified entry, including the read data in the incremental backup; where the hypervisor comprises an I/O stack, and wherein the I/O stack comprises the driver module; where the method further comprises modifying the entry in the change block bitmap file from a logical 0 to a logical 1 to indicate that data in the first sector has changed; where the virtual hard disk file and the change block bitmap file are stored in a volume of the VM; where the method further comprises intercepting an open operation generated by the VM to open the virtual hard disk file, and begin monitoring the virtual hard disk file in response to intercepting the open operation; where the change block bitmap file is associated with a first period of time; where the method further comprises generating a second change block bitmap file associated with a second period of time after the first period of time and store the second change block bitmap file in the VM, where the second change block bitmap file is generated after a first incremental backup based on the change block bitmap file is performed; where the method further comprises gathering data for use in performance of a second incremental backup at a time after the first incremental backup based on the second change block bitmap file; and where the driver forms a part of the hypervisor.
Terminology
Conditional language, such as, among others, “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular embodiment.
Unless the context clearly requires otherwise, throughout the description and the claims, the words “comprise,” “comprising,” and the like are to be construed in an inclusive sense, as opposed to an exclusive or exhaustive sense; that is to say, in the sense of “including, but not limited to.” As used herein, the terms “connected,” “coupled,” or any variant thereof means any connection or coupling, either direct or indirect, between two or more elements; the coupling or connection between the elements can be physical, logical, or a combination thereof. Additionally, the words “herein,” “above,” “below,” and words of similar import, when used in this application, refer to this application as a whole and not to any particular portions of this application. Where the context permits, words in the above Detailed Description using the singular or plural number may also include the plural or singular number respectively. The word “or” in reference to a list of two or more items, covers all of the following interpretations of the word: any one of the items in the list, all of the items in the list, and any combination of the items in the list. Likewise the term “and/or” in reference to a list of two or more items, covers all of the following interpretations of the word: any one of the items in the list, all of the items in the list, and any combination of the items in the list.
Depending on the embodiment, certain operations, acts, events, or functions of any of the algorithms described herein can be performed in a different sequence, can be added, merged, or left out altogether (e.g., not all are necessary for the practice of the algorithms). Moreover, in certain embodiments, operations, acts, functions, or events can be performed concurrently, e.g., through multi-threaded processing, interrupt processing, or multiple processors or processor cores or on other parallel architectures, rather than sequentially.
Systems and modules described herein may comprise software, firmware, hardware, or any combination(s) of software, firmware, or hardware suitable for the purposes described herein. Software and other modules may reside and execute on servers, workstations, personal computers, computerized tablets, PDAs, and other computing devices suitable for the purposes described herein. Software and other modules may be accessible via local memory, via a network, via a browser, or via other means suitable for the purposes described herein. Data structures described herein may comprise computer files, variables, programming arrays, programming structures, or any electronic information storage schemes or methods, or any combinations thereof, suitable for the purposes described herein. User interface elements described herein may comprise elements from graphical user interfaces, interactive voice response, command line interfaces, and other suitable interfaces.
Further, the processing of the various components of the illustrated systems can be distributed across multiple machines, networks, and other computing resources. In addition, two or more components of a system can be combined into fewer components. Various components of the illustrated systems can be implemented in one or more virtual machines, rather than in dedicated computer hardware systems and/or computing devices. Likewise, the data repositories shown can represent physical and/or logical data storage, including, for example, storage area networks or other distributed storage systems. Moreover, in some embodiments the connections between the components shown represent possible paths of data flow, rather than actual connections between hardware. While some examples of possible connections are shown, any of the subset of the components shown can communicate with any other subset of components in various implementations.
Embodiments are also described above with reference to flow chart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products. Each block of the flow chart illustrations and/or block diagrams, and combinations of blocks in the flow chart illustrations and/or block diagrams, may be implemented by computer program instructions. Such instructions may be provided to a processor of a general purpose computer, special purpose computer, specially-equipped computer (e.g., comprising a high-performance database server, a graphics subsystem, etc.) or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor(s) of the computer or other programmable data processing apparatus, create means for implementing the acts specified in the flow chart and/or block diagram block or blocks.
These computer program instructions may also be stored in a non-transitory computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the acts specified in the flow chart and/or block diagram block or blocks. The computer program instructions may also be loaded onto a computing device or other programmable data processing apparatus to cause a series of operations to be performed on the computing device or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the acts specified in the flow chart and/or block diagram block or blocks.
Any patents and applications and other references noted above, including any that may be listed in accompanying filing papers, are incorporated herein by reference. Aspects of the invention can be modified, if necessary, to employ the systems, functions, and concepts of the various references described above to provide yet further implementations of the invention.
These and other changes can be made to the invention in light of the above Detailed Description. While the above description describes certain examples of the invention, and describes the best mode contemplated, no matter how detailed the above appears in text, the invention can be practiced in many ways. Details of the system may vary considerably in its specific implementation, while still being encompassed by the invention disclosed herein. As noted above, particular terminology used when describing certain features or aspects of the invention should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the invention with which that terminology is associated. In general, the terms used in the following claims should not be construed to limit the invention to the specific examples disclosed in the specification, unless the above Detailed Description section explicitly defines such terms. Accordingly, the actual scope of the invention encompasses not only the disclosed examples, but also all equivalent ways of practicing or implementing the invention under the claims.
To reduce the number of claims, certain aspects of the invention are presented below in certain claim forms, but the applicant contemplates the various aspects of the invention in any number of claim forms. For example, while only one aspect of the invention is recited as a means-plus-function claim under 35 U.S.C sec. 112(f) (AIA), other aspects may likewise be embodied as a means-plus-function claim, or in other forms, such as being embodied in a computer-readable medium. Any claims intended to be treated under 35 U.S.C. § 112(f) will begin with the words “means for”, but use of the term “for” in any other context is not intended to invoke treatment under 35 U.S.C. § 112(f). Accordingly, the applicant reserves the right to pursue additional claims after filing this application, in either this application or in a continuing application.
This application is a continuation of U.S. patent application Ser. No. 16/667,746, entitled “VIRTUAL MACHINE CHANGE BLOCK TRACKING” and filed on Oct. 29, 2019, which is a continuation of U.S. patent application Ser. No. 15/979,215, entitled “VIRTUAL MACHINE CHANGE BLOCK TRACKING” and filed on May 14, 2018, which is a continuation of U.S. patent application Ser. No. 15/394,556, entitled “VIRTUAL MACHINE CHANGE BLOCK TRACKING” and filed on Dec. 29, 2016, which is a continuation of U.S. patent application Ser. No. 14/549,365, entitled “VIRTUAL MACHINE CHANGE BLOCK TRACKING” and filed on Nov. 20, 2014, which are hereby incorporated by reference herein in their entireties. Any and all applications for which a foreign or domestic priority claim is identified in the Application Data Sheet as filed with the present application are hereby incorporated by reference under 37 CFR 1.57.
| Number | Name | Date | Kind |
|---|---|---|---|
| 4084231 | Capozzi et al. | Apr 1978 | A |
| 4267568 | Dechant et al. | May 1981 | A |
| 4283787 | Chambers | Aug 1981 | A |
| 4417321 | Chang et al. | Nov 1983 | A |
| 4641274 | Swank | Feb 1987 | A |
| 4654819 | Stiffler et al. | Mar 1987 | A |
| 4686620 | Ng | Aug 1987 | A |
| 4912637 | Sheedy et al. | Mar 1990 | A |
| 4995035 | Cole et al. | Feb 1991 | A |
| 5005122 | Griffin et al. | Apr 1991 | A |
| 5093912 | Dong et al. | Mar 1992 | A |
| 5133065 | Cheffetz et al. | Jul 1992 | A |
| 5193154 | Kitajima et al. | Mar 1993 | A |
| 5212772 | Masters | May 1993 | A |
| 5226157 | Nakano et al. | Jul 1993 | A |
| 5239647 | Anglin et al. | Aug 1993 | A |
| 5241668 | Eastridge et al. | Aug 1993 | A |
| 5241670 | Eastridge et al. | Aug 1993 | A |
| 5276860 | Fortier et al. | Jan 1994 | A |
| 5276867 | Kenley et al. | Jan 1994 | A |
| 5287500 | Stoppani, Jr. | Feb 1994 | A |
| 5301286 | Rajani | Apr 1994 | A |
| 5321816 | Rogan et al. | Jun 1994 | A |
| 5333315 | Saether et al. | Jul 1994 | A |
| 5347653 | Flynn et al. | Sep 1994 | A |
| 5410700 | Fecteau et al. | Apr 1995 | A |
| 5420996 | Aoyagi | May 1995 | A |
| 5448724 | Hayashi | Sep 1995 | A |
| 5454099 | Myers et al. | Sep 1995 | A |
| 5491810 | Allen | Feb 1996 | A |
| 5495607 | Pisello et al. | Feb 1996 | A |
| 5504873 | Martin et al. | Apr 1996 | A |
| 5544345 | Carpenter et al. | Aug 1996 | A |
| 5544347 | Yanai et al. | Aug 1996 | A |
| 5559957 | Balk | Sep 1996 | A |
| 5559991 | Kanfi | Sep 1996 | A |
| 5594901 | Andoh | Jan 1997 | A |
| 5619644 | Crockett et al. | Apr 1997 | A |
| 5638509 | Dunphy et al. | Jun 1997 | A |
| 5642496 | Kanfi | Jun 1997 | A |
| 5664204 | Wang | Sep 1997 | A |
| 5673381 | Huai et al. | Sep 1997 | A |
| 5699361 | Ding et al. | Dec 1997 | A |
| 5729743 | Squibb | Mar 1998 | A |
| 5751997 | Kullick et al. | May 1998 | A |
| 5758359 | Saxon | May 1998 | A |
| 5761677 | Senator et al. | Jun 1998 | A |
| 5764972 | Crouse et al. | Jun 1998 | A |
| 5778395 | Whiting et al. | Jul 1998 | A |
| 5812398 | Nielsen | Sep 1998 | A |
| 5813009 | Johnson et al. | Sep 1998 | A |
| 5813017 | Morris | Sep 1998 | A |
| 5875478 | Blumenau | Feb 1999 | A |
| 5887134 | Ebrahim | Mar 1999 | A |
| 5901327 | Ofek | May 1999 | A |
| 5924102 | Perks | Jul 1999 | A |
| 5950205 | Aviani, Jr. | Sep 1999 | A |
| 5974563 | Beeler, Jr. | Oct 1999 | A |
| 6021415 | Cannon et al. | Feb 2000 | A |
| 6026414 | Anglin | Feb 2000 | A |
| 6052735 | Ulrich et al. | Apr 2000 | A |
| 6076148 | Kedem | Jun 2000 | A |
| 6094416 | Ying | Jul 2000 | A |
| 6101585 | Brown et al. | Aug 2000 | A |
| 6131095 | Low et al. | Oct 2000 | A |
| 6131190 | Sidwell | Oct 2000 | A |
| 6148412 | Cannon et al. | Nov 2000 | A |
| 6154787 | Urevig et al. | Nov 2000 | A |
| 6161111 | Mutalik et al. | Dec 2000 | A |
| 6167402 | Yeager | Dec 2000 | A |
| 6212512 | Barney et al. | Apr 2001 | B1 |
| 6260069 | Anglin | Jul 2001 | B1 |
| 6269431 | Dunham | Jul 2001 | B1 |
| 6275953 | Vahalia et al. | Aug 2001 | B1 |
| 6301592 | Aoyama et al. | Oct 2001 | B1 |
| 6324581 | Xu et al. | Nov 2001 | B1 |
| 6328766 | Long | Dec 2001 | B1 |
| 6330570 | Crighton | Dec 2001 | B1 |
| 6330642 | Carteau | Dec 2001 | B1 |
| 6343324 | Hubis et al. | Jan 2002 | B1 |
| RE37601 | Eastridge et al. | Mar 2002 | E |
| 6356801 | Goodman et al. | Mar 2002 | B1 |
| 6389432 | Pothapragada et al. | May 2002 | B1 |
| 6397242 | Devine et al. | May 2002 | B1 |
| 6418478 | Ignatius et al. | Jul 2002 | B1 |
| 6421711 | Blumenau et al. | Jul 2002 | B1 |
| 6487561 | Ofek et al. | Nov 2002 | B1 |
| 6519679 | Devireddy et al. | Feb 2003 | B2 |
| 6538669 | Lagueux, Jr. | Mar 2003 | B1 |
| 6542972 | Ignatius et al. | Apr 2003 | B2 |
| 6564228 | O'Connor | May 2003 | B1 |
| 6581076 | Ching et al. | Jun 2003 | B1 |
| 6658436 | Oshinsky et al. | Dec 2003 | B2 |
| 6658526 | Nguyen et al. | Dec 2003 | B2 |
| 6721767 | De Meno et al. | Apr 2004 | B2 |
| 6760723 | Oshinsky et al. | Jul 2004 | B2 |
| 6772290 | Bromley et al. | Aug 2004 | B1 |
| 6820214 | Cabrera et al. | Nov 2004 | B1 |
| 7003641 | Prahlad et al. | Feb 2006 | B2 |
| 7035880 | Crescenti et al. | Apr 2006 | B1 |
| 7076270 | Jaggers et al. | Jul 2006 | B2 |
| 7107298 | Prahlad et al. | Sep 2006 | B2 |
| 7130970 | Devassy et al. | Oct 2006 | B2 |
| 7162496 | Amarendran et al. | Jan 2007 | B2 |
| 7174433 | Kottomtharayil et al. | Feb 2007 | B2 |
| 7209972 | Ignatius et al. | Apr 2007 | B1 |
| 7219162 | Donker et al. | May 2007 | B2 |
| 7246207 | Kottomtharayil | Jul 2007 | B2 |
| 7315923 | Retnamma et al. | Jan 2008 | B2 |
| 7315924 | Prahlad et al. | Jan 2008 | B2 |
| 7324543 | Wassew et al. | Jan 2008 | B2 |
| 7343356 | Prahlad et al. | Mar 2008 | B2 |
| 7343453 | Prahlad et al. | Mar 2008 | B2 |
| 7346751 | Prahlad et al. | Mar 2008 | B2 |
| 7356679 | Le | Apr 2008 | B1 |
| 7376895 | Tsao | May 2008 | B2 |
| 7380072 | Kottomtharayil et al. | May 2008 | B2 |
| 7386744 | Barr et al. | Jun 2008 | B2 |
| 7389311 | Crescenti et al. | Jun 2008 | B1 |
| 7395282 | Crescenti | Jul 2008 | B1 |
| 7401154 | Ignatius et al. | Jul 2008 | B2 |
| 7409509 | Devassy et al. | Aug 2008 | B2 |
| 7440982 | Lu et al. | Oct 2008 | B2 |
| 7447692 | Oshinsky et al. | Nov 2008 | B2 |
| 7448079 | Tremain | Nov 2008 | B2 |
| 7454569 | Kavuri et al. | Nov 2008 | B2 |
| 7475282 | Tormasov et al. | Jan 2009 | B2 |
| 7484054 | Kottomtharayil et al. | Jan 2009 | B2 |
| 7484208 | Nelson | Jan 2009 | B1 |
| 7490207 | Amarendran et al. | Feb 2009 | B2 |
| 7500053 | Kavuri et al. | Mar 2009 | B1 |
| 7502820 | Manders et al. | Mar 2009 | B2 |
| 7529782 | Prahlad et al. | May 2009 | B2 |
| 7536291 | Vijayan Retnamma et al. | May 2009 | B1 |
| 7543125 | Gokhale | Jun 2009 | B2 |
| 7546324 | Prahlad et al. | Jun 2009 | B2 |
| 7552279 | Gandler | Jun 2009 | B1 |
| 7581077 | Ignatius et al. | Aug 2009 | B2 |
| 7603386 | Amarendran et al. | Oct 2009 | B2 |
| 7606844 | Kottomtharayil | Oct 2009 | B2 |
| 7613748 | Brockway et al. | Nov 2009 | B2 |
| 7613752 | Prahlad et al. | Nov 2009 | B2 |
| 7617253 | Prahlad et al. | Nov 2009 | B2 |
| 7617262 | Prahlad et al. | Nov 2009 | B2 |
| 7620710 | Kottomtharayil et al. | Nov 2009 | B2 |
| 7631351 | Erofeev | Dec 2009 | B2 |
| 7636743 | Erofeev | Dec 2009 | B2 |
| 7640406 | Hagerstrom et al. | Dec 2009 | B1 |
| 7651593 | Prahlad et al. | Jan 2010 | B2 |
| 7657550 | Prahlad et al. | Feb 2010 | B2 |
| 7660807 | Prahlad et al. | Feb 2010 | B2 |
| 7661028 | Erofeev | Feb 2010 | B2 |
| 7668884 | Prahlad et al. | Feb 2010 | B2 |
| 7685177 | Hagerstrom et al. | Mar 2010 | B1 |
| 7694070 | Mogi et al. | Apr 2010 | B2 |
| 7716171 | Kryger | May 2010 | B2 |
| 7721138 | Lyadvinsky et al. | May 2010 | B1 |
| 7725671 | Prahlad et al. | May 2010 | B2 |
| 7725893 | Jaeckel et al. | May 2010 | B2 |
| 7730035 | Berger et al. | Jun 2010 | B2 |
| 7734669 | Kottomtharayil et al. | Jun 2010 | B2 |
| 7739459 | Kottomtharayil et al. | Jun 2010 | B2 |
| 7747579 | Prahlad et al. | Jun 2010 | B2 |
| 7756835 | Pugh | Jul 2010 | B2 |
| 7756964 | Madison, Jr. et al. | Jul 2010 | B2 |
| 7757043 | Kavuri et al. | Jul 2010 | B2 |
| 7765167 | Prahlad et al. | Jul 2010 | B2 |
| 7769961 | Kottomtharayil et al. | Aug 2010 | B2 |
| 7778984 | Zhang et al. | Aug 2010 | B2 |
| 7792789 | Prahlad et al. | Sep 2010 | B2 |
| 7793307 | Gokhale et al. | Sep 2010 | B2 |
| 7801864 | Prahlad et al. | Sep 2010 | B2 |
| 7802067 | Prahlad et al. | Sep 2010 | B2 |
| 7809914 | Kottomtharayil et al. | Oct 2010 | B2 |
| 7822967 | Fung | Oct 2010 | B2 |
| 7823145 | Le et al. | Oct 2010 | B1 |
| 7831789 | Per et al. | Nov 2010 | B1 |
| 7840537 | Gokhale | Nov 2010 | B2 |
| 7861234 | Lolo | Dec 2010 | B1 |
| 7882077 | Gokhale et al. | Feb 2011 | B2 |
| 7890467 | Watanable et al. | Feb 2011 | B2 |
| 7899788 | Chandhok et al. | Mar 2011 | B2 |
| 7917617 | Ponnapur | Mar 2011 | B1 |
| 7925850 | Waldspurger et al. | Apr 2011 | B1 |
| 7937421 | Mikesell et al. | May 2011 | B2 |
| 7937612 | Lyadvinsky et al. | May 2011 | B1 |
| 8001277 | Mega et al. | Aug 2011 | B2 |
| 8037016 | Odulinski et al. | Oct 2011 | B2 |
| 8037028 | Prahlad et al. | Oct 2011 | B2 |
| 8037032 | Pershin et al. | Oct 2011 | B2 |
| 8046550 | Feathergill | Oct 2011 | B2 |
| 8055745 | Atluri | Nov 2011 | B2 |
| 8060476 | Afonso et al. | Nov 2011 | B1 |
| 8069271 | Brunet et al. | Nov 2011 | B2 |
| 8099391 | Monckton | Jan 2012 | B1 |
| 8117492 | Searls et al. | Feb 2012 | B1 |
| 8135930 | Mattox et al. | Mar 2012 | B1 |
| 8140786 | Bunte | Mar 2012 | B2 |
| 8156086 | Lu et al. | Apr 2012 | B2 |
| 8156301 | Khandelwal et al. | Apr 2012 | B1 |
| 8170995 | Prahlad et al. | May 2012 | B2 |
| 8180735 | Ansari et al. | May 2012 | B2 |
| 8185893 | Hyser et al. | May 2012 | B2 |
| 8191063 | Shingai et al. | May 2012 | B2 |
| 8200637 | Stringham | Jun 2012 | B1 |
| 8200638 | Zheng et al. | Jun 2012 | B1 |
| 8209680 | Le et al. | Jun 2012 | B1 |
| 8219524 | Gokhale | Jul 2012 | B2 |
| 8219653 | Keagy et al. | Jul 2012 | B1 |
| 8219769 | Wilk | Jul 2012 | B1 |
| 8225133 | Lyadvinsky et al. | Jul 2012 | B1 |
| 8229896 | Narayanan | Jul 2012 | B1 |
| 8229954 | Kottomtharayil et al. | Jul 2012 | B2 |
| 8230195 | Amarendran et al. | Jul 2012 | B2 |
| 8230256 | Raut | Jul 2012 | B1 |
| 8285681 | Prahlad et al. | Oct 2012 | B2 |
| 8307177 | Prahlad et al. | Nov 2012 | B2 |
| 8307187 | Chawla et al. | Nov 2012 | B2 |
| 8315992 | Gipp et al. | Nov 2012 | B1 |
| 8364652 | Vijayan et al. | Jan 2013 | B2 |
| 8370542 | Lu et al. | Feb 2013 | B2 |
| 8387045 | Yasutaka et al. | Feb 2013 | B2 |
| 8396838 | Brockway | Mar 2013 | B2 |
| 8407190 | Prahlad | Mar 2013 | B2 |
| 8433679 | Crescenti | Apr 2013 | B2 |
| 8434131 | Varadharajan | Apr 2013 | B2 |
| 8438347 | Tawri et al. | May 2013 | B1 |
| 8453145 | Naik | May 2013 | B1 |
| 8458419 | Basler et al. | Jun 2013 | B2 |
| 8473594 | Astete et al. | Jun 2013 | B2 |
| 8489676 | Chaplin et al. | Jul 2013 | B1 |
| 8560788 | Sreedharan et al. | Oct 2013 | B1 |
| 8577845 | Nguyen et al. | Nov 2013 | B2 |
| 8578120 | Attarde et al. | Nov 2013 | B2 |
| 8578126 | Gaonkar et al. | Nov 2013 | B1 |
| 8606911 | Raleigh et al. | Dec 2013 | B2 |
| 8612439 | Prahlad et al. | Dec 2013 | B2 |
| 8615489 | Pershin et al. | Dec 2013 | B2 |
| 8620870 | Dwarampudi et al. | Dec 2013 | B2 |
| 8621460 | Evans et al. | Dec 2013 | B2 |
| 8635429 | Naftel et al. | Jan 2014 | B1 |
| 8667171 | Guo et al. | Mar 2014 | B2 |
| 8677085 | Vaghani et al. | Mar 2014 | B2 |
| 8719286 | Xing et al. | May 2014 | B1 |
| 8751857 | Frenkel et al. | Jun 2014 | B2 |
| 8776043 | Thimsen et al. | Jul 2014 | B1 |
| 8799431 | Pabari | Aug 2014 | B2 |
| 8831202 | Abidogun et al. | Sep 2014 | B1 |
| 8844015 | Pendergrass et al. | Sep 2014 | B2 |
| 8850146 | Majumdar | Sep 2014 | B1 |
| 8904081 | Kulkarni | Dec 2014 | B1 |
| 8924967 | Nelson | Dec 2014 | B2 |
| 8930543 | Ashok et al. | Jan 2015 | B2 |
| 8938481 | Kumarasamy et al. | Jan 2015 | B2 |
| 8938643 | Karmarkar et al. | Jan 2015 | B1 |
| 8954446 | Vijayan Retnamma et al. | Feb 2015 | B2 |
| 8954796 | Cohen et al. | Feb 2015 | B1 |
| 8959509 | Sobel et al. | Feb 2015 | B1 |
| 8966318 | Shah | Feb 2015 | B1 |
| 9020895 | Rajashekar | Apr 2015 | B1 |
| 9020900 | Vijayan Retnamma et al. | Apr 2015 | B2 |
| 9021459 | Qu | Apr 2015 | B1 |
| 9026498 | Kumarasamy | May 2015 | B2 |
| 9069587 | Agarwal et al. | Jun 2015 | B2 |
| 9098457 | Towstopiat et al. | Aug 2015 | B2 |
| 9098495 | Gokhale | Aug 2015 | B2 |
| 9116633 | Sancheti et al. | Aug 2015 | B2 |
| 9124633 | Eizadi et al. | Sep 2015 | B1 |
| 9141529 | Klein et al. | Sep 2015 | B2 |
| 9146755 | Lassonde et al. | Sep 2015 | B2 |
| 9213706 | Long et al. | Dec 2015 | B2 |
| 9223596 | Araujo | Dec 2015 | B1 |
| 9223597 | Deshpande et al. | Dec 2015 | B2 |
| 9235474 | Petri et al. | Jan 2016 | B1 |
| 9235582 | Madiraju Varadaraju et al. | Jan 2016 | B1 |
| 9239687 | Vijayan et al. | Jan 2016 | B2 |
| 9239762 | Gunda et al. | Jan 2016 | B1 |
| 9246996 | Brooker | Jan 2016 | B1 |
| 9268602 | Prahlad et al. | Feb 2016 | B2 |
| 9280378 | Shah | Mar 2016 | B2 |
| 9286086 | Deshpande et al. | Mar 2016 | B2 |
| 9286110 | Mitkar et al. | Mar 2016 | B2 |
| 9292350 | Pendharkar et al. | Mar 2016 | B1 |
| 9298715 | Kumarasamy et al. | Mar 2016 | B2 |
| 9311121 | Deshpande et al. | Apr 2016 | B2 |
| 9311248 | Wagner | Apr 2016 | B2 |
| 9311313 | Le et al. | Apr 2016 | B2 |
| 9354927 | Hiltgen et al. | May 2016 | B2 |
| 9397944 | Hobbs et al. | Jul 2016 | B1 |
| 9405763 | Prahlad et al. | Aug 2016 | B2 |
| 9417968 | Dornemann et al. | Aug 2016 | B2 |
| 9424136 | Teater et al. | Aug 2016 | B1 |
| 9436555 | Dornemann et al. | Sep 2016 | B2 |
| 9451023 | Sancheti | Sep 2016 | B2 |
| 9461881 | Kumarasamy | Oct 2016 | B2 |
| 9471441 | Lyadvinsky et al. | Oct 2016 | B1 |
| 9477683 | Ghosh | Oct 2016 | B2 |
| 9489244 | Mitkar et al. | Nov 2016 | B2 |
| 9495370 | Chatterjee et al. | Nov 2016 | B1 |
| 9495404 | Kumarasamy et al. | Nov 2016 | B2 |
| 9535798 | Liguori | Jan 2017 | B1 |
| 9575789 | Rangari et al. | Feb 2017 | B1 |
| 9575991 | Ghosh | Feb 2017 | B2 |
| 9588847 | Natanzon et al. | Mar 2017 | B1 |
| 9594636 | Mortensen et al. | Mar 2017 | B2 |
| 9606745 | Satoyama et al. | Mar 2017 | B2 |
| 9612966 | Joshi et al. | Apr 2017 | B2 |
| 9613064 | Chou et al. | Apr 2017 | B1 |
| 9632882 | Kumarasamy et al. | Apr 2017 | B2 |
| 9633033 | Vijayan et al. | Apr 2017 | B2 |
| 9639274 | Maranna et al. | May 2017 | B2 |
| 9639426 | Pawar et al. | May 2017 | B2 |
| 9639428 | Boda et al. | May 2017 | B1 |
| 9652283 | Mitkar et al. | May 2017 | B2 |
| 9665386 | Bayapuneni et al. | May 2017 | B2 |
| 9684535 | Deshpande et al. | Jun 2017 | B2 |
| 9684567 | Derk et al. | Jun 2017 | B2 |
| 9703584 | Kottomtharayil et al. | Jul 2017 | B2 |
| 9710465 | Dornemann et al. | Jul 2017 | B2 |
| 9740702 | Pawar et al. | Aug 2017 | B2 |
| 9740723 | Prahlad et al. | Aug 2017 | B2 |
| 9760398 | Pai | Sep 2017 | B1 |
| 9760448 | Per et al. | Sep 2017 | B1 |
| 9766825 | Bhagi et al. | Sep 2017 | B2 |
| 9766989 | Mitkar et al. | Sep 2017 | B2 |
| 9792075 | Banerjee et al. | Oct 2017 | B1 |
| 9823977 | Dornemann et al. | Nov 2017 | B2 |
| 9852026 | Mitkar et al. | Dec 2017 | B2 |
| 9928001 | Dornemann et al. | Mar 2018 | B2 |
| 9939981 | White et al. | Apr 2018 | B2 |
| 9965316 | Deshpande et al. | May 2018 | B2 |
| 9977687 | Kottomtharayil et al. | May 2018 | B2 |
| 9983936 | Dornemann et al. | May 2018 | B2 |
| 9996287 | Dornemann et al. | Jun 2018 | B2 |
| 9996429 | Kumar | Jun 2018 | B1 |
| 9996534 | Dornemann et al. | Jun 2018 | B2 |
| 10048889 | Dornemann et al. | Aug 2018 | B2 |
| 10061658 | Long et al. | Aug 2018 | B2 |
| 10075459 | Suryanarayanan | Sep 2018 | B1 |
| 10108652 | Kumarasamy et al. | Oct 2018 | B2 |
| 10114705 | Kumar et al. | Oct 2018 | B1 |
| 10152251 | Sancheti et al. | Dec 2018 | B2 |
| 10162528 | Sancheti et al. | Dec 2018 | B2 |
| 10162873 | Desphande et al. | Dec 2018 | B2 |
| 10210048 | Sancheti | Feb 2019 | B2 |
| 10225964 | Smith | Mar 2019 | B2 |
| 10228962 | Dornemann et al. | Mar 2019 | B2 |
| 10241871 | Cheng | Mar 2019 | B1 |
| 10387073 | Bhagi et al. | Aug 2019 | B2 |
| 10417102 | Sanakkayala et al. | Sep 2019 | B2 |
| 10437505 | Dornemann et al. | Oct 2019 | B2 |
| 10452303 | Dornemann et al. | Oct 2019 | B2 |
| 10474483 | Kottomtharayil et al. | Nov 2019 | B2 |
| 10474542 | Mitkar et al. | Nov 2019 | B2 |
| 10474548 | Sanakkayala et al. | Nov 2019 | B2 |
| 10481984 | Semyonov et al. | Nov 2019 | B1 |
| 10496547 | Naenko | Dec 2019 | B1 |
| 10565067 | Dornemann | Feb 2020 | B2 |
| 10567067 | Kumagai | Feb 2020 | B2 |
| 10572468 | Dornemann et al. | Feb 2020 | B2 |
| 10592350 | Dornemann | Mar 2020 | B2 |
| 10650057 | Pawar et al. | May 2020 | B2 |
| 10678758 | Dornemann | Jun 2020 | B2 |
| 10684883 | Deshpande et al. | Jun 2020 | B2 |
| 10733143 | Pawar et al. | Aug 2020 | B2 |
| 10747630 | Sanakkayala et al. | Aug 2020 | B2 |
| 10768971 | Dornemann et al. | Sep 2020 | B2 |
| 10776209 | Pawar et al. | Sep 2020 | B2 |
| 10877851 | Mitkar et al. | Dec 2020 | B2 |
| 10877928 | Nagrale et al. | Dec 2020 | B2 |
| 10896053 | Kottomtharayil et al. | Jan 2021 | B2 |
| 10896100 | Mitkar et al. | Jan 2021 | B2 |
| 10983875 | Mitkar et al. | Apr 2021 | B2 |
| 11010011 | Varadharajan et al. | May 2021 | B2 |
| 11249864 | Bhagi et al. | Feb 2022 | B2 |
| 11422709 | Dornemann et al. | Aug 2022 | B2 |
| 20020069369 | Tremain | Jun 2002 | A1 |
| 20020095609 | Tokunaga | Jul 2002 | A1 |
| 20020194511 | Swoboda | Dec 2002 | A1 |
| 20030031127 | Saleh et al. | Feb 2003 | A1 |
| 20030126494 | Strasser | Jul 2003 | A1 |
| 20030204597 | Arakawa et al. | Oct 2003 | A1 |
| 20040030668 | Pawlowski et al. | Feb 2004 | A1 |
| 20040030822 | Rajan et al. | Feb 2004 | A1 |
| 20040230899 | Pagnano et al. | Nov 2004 | A1 |
| 20050060356 | Saika | Mar 2005 | A1 |
| 20050080970 | Jeyasingh et al. | Apr 2005 | A1 |
| 20050198303 | Knauerhase et al. | Sep 2005 | A1 |
| 20050216788 | Mani-Meitav et al. | Sep 2005 | A1 |
| 20050262097 | Sim-Tang | Nov 2005 | A1 |
| 20060058994 | Ravi et al. | Mar 2006 | A1 |
| 20060064555 | Prahlad et al. | Mar 2006 | A1 |
| 20060101189 | Chandrasekaran et al. | May 2006 | A1 |
| 20060155712 | Prahlad et al. | Jul 2006 | A1 |
| 20060184935 | Abels et al. | Aug 2006 | A1 |
| 20060195715 | Herington | Aug 2006 | A1 |
| 20060224846 | Amarendran | Oct 2006 | A1 |
| 20060225065 | Chandhok et al. | Oct 2006 | A1 |
| 20060230136 | Ma | Oct 2006 | A1 |
| 20060259908 | Bayer | Nov 2006 | A1 |
| 20070027999 | Allen et al. | Feb 2007 | A1 |
| 20070043870 | Ninose | Feb 2007 | A1 |
| 20070100792 | Lent et al. | May 2007 | A1 |
| 20070198802 | Kavuri | Aug 2007 | A1 |
| 20070203938 | Prahlad et al. | Aug 2007 | A1 |
| 20070208918 | Harbin et al. | Sep 2007 | A1 |
| 20070220319 | Desai et al. | Sep 2007 | A1 |
| 20070234302 | Suzuki et al. | Oct 2007 | A1 |
| 20070239804 | Armstrong et al. | Oct 2007 | A1 |
| 20070260831 | Michael et al. | Nov 2007 | A1 |
| 20070266056 | Stacey et al. | Nov 2007 | A1 |
| 20070288536 | Sen et al. | Dec 2007 | A1 |
| 20070300220 | Seliger | Dec 2007 | A1 |
| 20080007765 | Ogata et al. | Jan 2008 | A1 |
| 20080059704 | Kavuri | Mar 2008 | A1 |
| 20080071841 | Okada et al. | Mar 2008 | A1 |
| 20080091655 | Gokhale | Apr 2008 | A1 |
| 20080126833 | Callaway et al. | May 2008 | A1 |
| 20080134177 | Fitzgerald et al. | Jun 2008 | A1 |
| 20080189468 | Schmidt et al. | Aug 2008 | A1 |
| 20080195639 | Freeman et al. | Aug 2008 | A1 |
| 20080228771 | Prahlad et al. | Sep 2008 | A1 |
| 20080228833 | Kano | Sep 2008 | A1 |
| 20080229037 | Bunte | Sep 2008 | A1 |
| 20080235479 | Scales et al. | Sep 2008 | A1 |
| 20080243855 | Prahlad | Oct 2008 | A1 |
| 20080243947 | Kaneda | Oct 2008 | A1 |
| 20080244028 | Le et al. | Oct 2008 | A1 |
| 20080244068 | Iyoda et al. | Oct 2008 | A1 |
| 20080244177 | Crescenti et al. | Oct 2008 | A1 |
| 20080250407 | Dadhia et al. | Oct 2008 | A1 |
| 20080270564 | Rangegowda et al. | Oct 2008 | A1 |
| 20080275924 | Fries | Nov 2008 | A1 |
| 20080282253 | Huizenga | Nov 2008 | A1 |
| 20080313371 | Kedem et al. | Dec 2008 | A1 |
| 20080320319 | Muller | Dec 2008 | A1 |
| 20090006733 | Gold et al. | Jan 2009 | A1 |
| 20090037680 | Colbert et al. | Feb 2009 | A1 |
| 20090113109 | Nelson et al. | Apr 2009 | A1 |
| 20090144416 | Chatley et al. | Jun 2009 | A1 |
| 20090157882 | Kashyap | Jun 2009 | A1 |
| 20090210427 | Eidler et al. | Aug 2009 | A1 |
| 20090210458 | Glover et al. | Aug 2009 | A1 |
| 20090210527 | Kawato | Aug 2009 | A1 |
| 20090216816 | Basler et al. | Aug 2009 | A1 |
| 20090222496 | Liu et al. | Sep 2009 | A1 |
| 20090228669 | Siesarev et al. | Sep 2009 | A1 |
| 20090240904 | Austruy et al. | Sep 2009 | A1 |
| 20090248762 | Prahlad et al. | Oct 2009 | A1 |
| 20090249005 | Bender et al. | Oct 2009 | A1 |
| 20090282404 | Khandekar et al. | Nov 2009 | A1 |
| 20090287665 | Prahlad | Nov 2009 | A1 |
| 20090300023 | Vaghani | Dec 2009 | A1 |
| 20090300057 | Friedman | Dec 2009 | A1 |
| 20090307166 | Routray et al. | Dec 2009 | A1 |
| 20090313260 | Mimatsu | Dec 2009 | A1 |
| 20090313447 | Nguyen et al. | Dec 2009 | A1 |
| 20090313503 | Atluri et al. | Dec 2009 | A1 |
| 20090319534 | Gokhale | Dec 2009 | A1 |
| 20090319585 | Gokhale | Dec 2009 | A1 |
| 20090320029 | Kottomtharayil | Dec 2009 | A1 |
| 20090320137 | White et al. | Dec 2009 | A1 |
| 20090327477 | Madison, Jr. et al. | Dec 2009 | A1 |
| 20100011178 | Feathergill | Jan 2010 | A1 |
| 20100017647 | Callaway et al. | Jan 2010 | A1 |
| 20100030984 | Erickson | Feb 2010 | A1 |
| 20100049929 | Nagarkar et al. | Feb 2010 | A1 |
| 20100049930 | Pershin | Feb 2010 | A1 |
| 20100070466 | Prahlad et al. | Mar 2010 | A1 |
| 20100070474 | Lad | Mar 2010 | A1 |
| 20100070725 | Prahlad et al. | Mar 2010 | A1 |
| 20100070726 | Ngo et al. | Mar 2010 | A1 |
| 20100077165 | Lu | Mar 2010 | A1 |
| 20100082672 | Kottomtharayil | Apr 2010 | A1 |
| 20100094948 | Ganesh et al. | Apr 2010 | A1 |
| 20100106691 | Preslan et al. | Apr 2010 | A1 |
| 20100107158 | Chen et al. | Apr 2010 | A1 |
| 20100107172 | Calinescu et al. | Apr 2010 | A1 |
| 20100161919 | Dodgson et al. | Jun 2010 | A1 |
| 20100186014 | Vaghani et al. | Jul 2010 | A1 |
| 20100211829 | Ziskind et al. | Aug 2010 | A1 |
| 20100228913 | Czezatke et al. | Sep 2010 | A1 |
| 20100242096 | Varadharajan et al. | Sep 2010 | A1 |
| 20100257523 | Frank | Oct 2010 | A1 |
| 20100262585 | Rosikiewicz et al. | Oct 2010 | A1 |
| 20100262586 | Rosikiewicz et al. | Oct 2010 | A1 |
| 20100262794 | De Beer et al. | Oct 2010 | A1 |
| 20100280999 | Atluri et al. | Nov 2010 | A1 |
| 20100299309 | Maki et al. | Nov 2010 | A1 |
| 20100299666 | Agbaria et al. | Nov 2010 | A1 |
| 20100306173 | Frank | Dec 2010 | A1 |
| 20100306486 | Balasubramanian et al. | Dec 2010 | A1 |
| 20100325471 | Mishra et al. | Dec 2010 | A1 |
| 20100325727 | Neystad et al. | Dec 2010 | A1 |
| 20100332401 | Prahlad | Dec 2010 | A1 |
| 20100332454 | Prahlad et al. | Dec 2010 | A1 |
| 20100332456 | Prahlad et al. | Dec 2010 | A1 |
| 20100332479 | Prahlad | Dec 2010 | A1 |
| 20100332629 | Cotugno et al. | Dec 2010 | A1 |
| 20100332818 | Prahlad | Dec 2010 | A1 |
| 20100333100 | Miyazaki et al. | Dec 2010 | A1 |
| 20100333116 | Prahlad | Dec 2010 | A1 |
| 20110004586 | Cherryholmes et al. | Jan 2011 | A1 |
| 20110010515 | Ranade | Jan 2011 | A1 |
| 20110016467 | Kane | Jan 2011 | A1 |
| 20110022811 | Kirihata et al. | Jan 2011 | A1 |
| 20110022812 | Van Der Linden et al. | Jan 2011 | A1 |
| 20110023114 | Diab et al. | Jan 2011 | A1 |
| 20110035620 | Elyashev et al. | Feb 2011 | A1 |
| 20110047541 | Yamaguchi et al. | Feb 2011 | A1 |
| 20110061045 | Phillips | Mar 2011 | A1 |
| 20110072430 | Mani | Mar 2011 | A1 |
| 20110087632 | Subramanian et al. | Apr 2011 | A1 |
| 20110107025 | Urkude et al. | May 2011 | A1 |
| 20110107331 | Evans et al. | May 2011 | A1 |
| 20110138069 | Momchilov et al. | Jun 2011 | A1 |
| 20110161299 | Prahlad | Jun 2011 | A1 |
| 20110179414 | Goggin et al. | Jul 2011 | A1 |
| 20110185355 | Chawla et al. | Jul 2011 | A1 |
| 20110191559 | Li et al. | Aug 2011 | A1 |
| 20110202728 | Nichols et al. | Aug 2011 | A1 |
| 20110202734 | Dhakras et al. | Aug 2011 | A1 |
| 20110208928 | Chandra et al. | Aug 2011 | A1 |
| 20110213754 | Bindal | Sep 2011 | A1 |
| 20110219144 | Amit et al. | Sep 2011 | A1 |
| 20110225277 | Freimuth et al. | Sep 2011 | A1 |
| 20110239013 | Muller | Sep 2011 | A1 |
| 20110246430 | Prahlad et al. | Oct 2011 | A1 |
| 20110252208 | Ali et al. | Oct 2011 | A1 |
| 20110264786 | Kedem et al. | Oct 2011 | A1 |
| 20120002951 | Reisman | Jan 2012 | A1 |
| 20120016840 | Lin et al. | Jan 2012 | A1 |
| 20120017027 | Baskakov et al. | Jan 2012 | A1 |
| 20120017043 | Aizman et al. | Jan 2012 | A1 |
| 20120017114 | Timashev et al. | Jan 2012 | A1 |
| 20120054736 | Arcese et al. | Mar 2012 | A1 |
| 20120072685 | Otani | Mar 2012 | A1 |
| 20120079221 | Sivasubramanian et al. | Mar 2012 | A1 |
| 20120084262 | Dwarampudi et al. | Apr 2012 | A1 |
| 20120084769 | Adi et al. | Apr 2012 | A1 |
| 20120096149 | Sunkara et al. | Apr 2012 | A1 |
| 20120110328 | Pate et al. | May 2012 | A1 |
| 20120131295 | Nakajima | May 2012 | A1 |
| 20120131578 | Ciano et al. | May 2012 | A1 |
| 20120136832 | Sadhwani | May 2012 | A1 |
| 20120150815 | Parfumi | Jun 2012 | A1 |
| 20120150818 | Vijayan Retnamma et al. | Jun 2012 | A1 |
| 20120150826 | Vijayan Retnamma et al. | Jun 2012 | A1 |
| 20120151084 | Stathopoulos et al. | Jun 2012 | A1 |
| 20120159232 | Shimada et al. | Jun 2012 | A1 |
| 20120167083 | Suit | Jun 2012 | A1 |
| 20120209812 | Bezbaruah | Aug 2012 | A1 |
| 20120215911 | Raleigh et al. | Aug 2012 | A1 |
| 20120221843 | Bak et al. | Aug 2012 | A1 |
| 20120233285 | Suzuki | Sep 2012 | A1 |
| 20120254119 | Kumarasamy et al. | Oct 2012 | A1 |
| 20120254364 | Vijayan | Oct 2012 | A1 |
| 20120254824 | Bansold | Oct 2012 | A1 |
| 20120278287 | Wilk | Nov 2012 | A1 |
| 20120278571 | Fleming et al. | Nov 2012 | A1 |
| 20120278799 | Starks et al. | Nov 2012 | A1 |
| 20120290802 | Wade et al. | Nov 2012 | A1 |
| 20120324183 | Chiruvolu et al. | Dec 2012 | A1 |
| 20120331248 | Kono et al. | Dec 2012 | A1 |
| 20130024641 | Talagala et al. | Jan 2013 | A1 |
| 20130024722 | Kotagiri | Jan 2013 | A1 |
| 20130036418 | Yadappanavar et al. | Feb 2013 | A1 |
| 20130042234 | Deluca et al. | Feb 2013 | A1 |
| 20130054533 | Hao et al. | Feb 2013 | A1 |
| 20130061014 | Prahlad et al. | Mar 2013 | A1 |
| 20130074181 | Singh | Mar 2013 | A1 |
| 20130080841 | Reddy et al. | Mar 2013 | A1 |
| 20130086580 | Simonsen et al. | Apr 2013 | A1 |
| 20130111262 | Taylor et al. | May 2013 | A1 |
| 20130117744 | Klein et al. | May 2013 | A1 |
| 20130167145 | Krishnamurthy et al. | Jun 2013 | A1 |
| 20130173771 | Ditto et al. | Jul 2013 | A1 |
| 20130198828 | Pendergrass et al. | Aug 2013 | A1 |
| 20130204849 | Chacko | Aug 2013 | A1 |
| 20130219069 | Yellapragada | Aug 2013 | A1 |
| 20130227558 | Du et al. | Aug 2013 | A1 |
| 20130232215 | Gupta et al. | Sep 2013 | A1 |
| 20130232480 | Winterfeldt et al. | Sep 2013 | A1 |
| 20130238562 | Kumarasamy | Sep 2013 | A1 |
| 20130262390 | Kumarasamy et al. | Oct 2013 | A1 |
| 20130262638 | Kumarasamy et al. | Oct 2013 | A1 |
| 20130262801 | Sancheti et al. | Oct 2013 | A1 |
| 20130268931 | O'Hare et al. | Oct 2013 | A1 |
| 20130275375 | Nickolov et al. | Oct 2013 | A1 |
| 20130290267 | Dwarampudi et al. | Oct 2013 | A1 |
| 20130311429 | Agetsuma | Nov 2013 | A1 |
| 20130326260 | Wei et al. | Dec 2013 | A1 |
| 20130346709 | Wang | Dec 2013 | A1 |
| 20140006858 | Helfman et al. | Jan 2014 | A1 |
| 20140007097 | Chin et al. | Jan 2014 | A1 |
| 20140007181 | Sarin et al. | Jan 2014 | A1 |
| 20140052892 | Klein et al. | Feb 2014 | A1 |
| 20140059380 | Krishnan | Feb 2014 | A1 |
| 20140067363 | Ogren et al. | Mar 2014 | A1 |
| 20140075440 | Prahlad et al. | Mar 2014 | A1 |
| 20140089266 | Une et al. | Mar 2014 | A1 |
| 20140095816 | Hsu et al. | Apr 2014 | A1 |
| 20140115285 | Arcese et al. | Apr 2014 | A1 |
| 20140136803 | Qin | May 2014 | A1 |
| 20140156684 | Zaslavsky et al. | Jun 2014 | A1 |
| 20140181038 | Pawar et al. | Jun 2014 | A1 |
| 20140181044 | Pawar et al. | Jun 2014 | A1 |
| 20140181046 | Pawar et al. | Jun 2014 | A1 |
| 20140188803 | James et al. | Jul 2014 | A1 |
| 20140196038 | Kottomtharayil et al. | Jul 2014 | A1 |
| 20140196039 | Kottomtharayil et al. | Jul 2014 | A1 |
| 20140201151 | Kumarasamy et al. | Jul 2014 | A1 |
| 20140201157 | Pawar et al. | Jul 2014 | A1 |
| 20140201162 | Kumarasamy et al. | Jul 2014 | A1 |
| 20140201170 | Vijayan et al. | Jul 2014 | A1 |
| 20140237537 | Manmohan et al. | Aug 2014 | A1 |
| 20140244610 | Raman et al. | Aug 2014 | A1 |
| 20140259015 | Chigusa et al. | Sep 2014 | A1 |
| 20140278530 | Bruce et al. | Sep 2014 | A1 |
| 20140282514 | Carson et al. | Sep 2014 | A1 |
| 20140330874 | Novak et al. | Nov 2014 | A1 |
| 20140337295 | Haselton et al. | Nov 2014 | A1 |
| 20140344323 | Pelavin et al. | Nov 2014 | A1 |
| 20140372384 | Long et al. | Dec 2014 | A1 |
| 20150058382 | St. Laurent | Feb 2015 | A1 |
| 20150067393 | Madani et al. | Mar 2015 | A1 |
| 20150074536 | Varadharajan et al. | Mar 2015 | A1 |
| 20150106557 | Yu et al. | Apr 2015 | A1 |
| 20150120928 | Gummaraju et al. | Apr 2015 | A1 |
| 20150121122 | Towstopiat et al. | Apr 2015 | A1 |
| 20150134607 | Magdon-Ismail et al. | May 2015 | A1 |
| 20150142745 | Tekade et al. | May 2015 | A1 |
| 20150160884 | Scales et al. | Jun 2015 | A1 |
| 20150161015 | Kumarasamy et al. | Jun 2015 | A1 |
| 20150163172 | Mudigonda et al. | Jun 2015 | A1 |
| 20150212895 | Pawar et al. | Jul 2015 | A1 |
| 20150227438 | Jaquette | Aug 2015 | A1 |
| 20150227602 | Ramu | Aug 2015 | A1 |
| 20150242283 | Simoncelli et al. | Aug 2015 | A1 |
| 20150248333 | Aravot | Sep 2015 | A1 |
| 20150293817 | Subramanian et al. | Oct 2015 | A1 |
| 20150317216 | Hsu et al. | Nov 2015 | A1 |
| 20150324217 | Shilmover et al. | Nov 2015 | A1 |
| 20150347165 | Lipchuk et al. | Dec 2015 | A1 |
| 20150347430 | Ghosh | Dec 2015 | A1 |
| 20150363413 | Ghosh | Dec 2015 | A1 |
| 20150370652 | He et al. | Dec 2015 | A1 |
| 20150378758 | Duggan et al. | Dec 2015 | A1 |
| 20150378771 | Tarasuk-Levin | Dec 2015 | A1 |
| 20150378833 | Misra et al. | Dec 2015 | A1 |
| 20150378849 | Liu et al. | Dec 2015 | A1 |
| 20150381711 | Singh et al. | Dec 2015 | A1 |
| 20160019317 | Pawar et al. | Jan 2016 | A1 |
| 20160070623 | Derk | Mar 2016 | A1 |
| 20160092467 | Lee et al. | Mar 2016 | A1 |
| 20160127307 | Jain et al. | May 2016 | A1 |
| 20160154709 | Mitkar et al. | Jun 2016 | A1 |
| 20160170844 | Long et al. | Jun 2016 | A1 |
| 20160188413 | Abali et al. | Jun 2016 | A1 |
| 20160202916 | Cui et al. | Jul 2016 | A1 |
| 20160283335 | Yao et al. | Sep 2016 | A1 |
| 20160306706 | Pawar et al. | Oct 2016 | A1 |
| 20160308722 | Kumarasamy et al. | Oct 2016 | A1 |
| 20160335007 | Ryu et al. | Nov 2016 | A1 |
| 20160350391 | Vijayan et al. | Dec 2016 | A1 |
| 20170090972 | Ryu et al. | Mar 2017 | A1 |
| 20170123939 | Maheshwari et al. | May 2017 | A1 |
| 20170168903 | Dornemann et al. | Jun 2017 | A1 |
| 20170185488 | Kumarasamy et al. | Jun 2017 | A1 |
| 20170192866 | Vijayan et al. | Jul 2017 | A1 |
| 20170193003 | Vijayan et al. | Jul 2017 | A1 |
| 20170235647 | Kilaru et al. | Aug 2017 | A1 |
| 20170242871 | Kilaru et al. | Aug 2017 | A1 |
| 20170249220 | Kumarasamy et al. | Aug 2017 | A1 |
| 20170262204 | Dornemann et al. | Sep 2017 | A1 |
| 20170264589 | Hunt et al. | Sep 2017 | A1 |
| 20170286230 | Zamir | Oct 2017 | A1 |
| 20170371547 | Fruchtman et al. | Dec 2017 | A1 |
| 20180089031 | Dornemann et al. | Mar 2018 | A1 |
| 20180113623 | Sancheti | Apr 2018 | A1 |
| 20180143880 | Dornemann | May 2018 | A1 |
| 20180181598 | Pawar et al. | Jun 2018 | A1 |
| 20180246756 | Abali et al. | Aug 2018 | A1 |
| 20180253192 | Varadharajan et al. | Sep 2018 | A1 |
| 20180276022 | Mitkar et al. | Sep 2018 | A1 |
| 20180276083 | Mitkar et al. | Sep 2018 | A1 |
| 20180276084 | Mitkar et al. | Sep 2018 | A1 |
| 20180276085 | Mitkar et al. | Sep 2018 | A1 |
| 20180284986 | Bhagi | Oct 2018 | A1 |
| 20180285202 | Bhagi et al. | Oct 2018 | A1 |
| 20180285353 | Rao et al. | Oct 2018 | A1 |
| 20180329636 | Dornemann et al. | Nov 2018 | A1 |
| 20190012339 | Kumarasamy et al. | Jan 2019 | A1 |
| 20190026187 | Gulam et al. | Jan 2019 | A1 |
| 20190065069 | Sancheti et al. | Feb 2019 | A1 |
| 20190090305 | Hunter et al. | Mar 2019 | A1 |
| 20190340088 | Sanakkayala et al. | Nov 2019 | A1 |
| 20190347120 | Kottamtharayil et al. | Nov 2019 | A1 |
| 20190369901 | Dornemann et al. | Dec 2019 | A1 |
| 20200034252 | Mitkar et al. | Jan 2020 | A1 |
| 20200142782 | Dornemann | May 2020 | A1 |
| 20200142783 | Dornemann | May 2020 | A1 |
| 20200174894 | Dornemann | Jun 2020 | A1 |
| 20200174895 | Dornemann | Jun 2020 | A1 |
| 20200183728 | Deshpande et al. | Jun 2020 | A1 |
| 20200241908 | Dornemann et al. | Jul 2020 | A1 |
| 20200265024 | Pawar et al. | Aug 2020 | A1 |
| 20200327163 | Pawar et al. | Oct 2020 | A1 |
| 20200334113 | Sanakkayala et al. | Oct 2020 | A1 |
| 20200334201 | Pawar et al. | Oct 2020 | A1 |
| 20210089337 | Kottomtharayil et al. | Mar 2021 | A1 |
| 20210096893 | Kottomtharayil et al. | Apr 2021 | A1 |
| 20210103556 | Nagrale et al. | Apr 2021 | A1 |
| 20210117294 | Mitkar et al. | Apr 2021 | A1 |
| 20210240308 | Varadharajan et al. | Aug 2021 | A1 |
| 20210255937 | Mitkar et al. | Aug 2021 | A1 |
| Number | Date | Country |
|---|---|---|
| 2004227949 | Oct 2004 | AU |
| 2498174 | Mar 2004 | CA |
| 69415115 | Aug 1999 | DE |
| 60020978 | Apr 2006 | DE |
| 0259912 | Mar 1988 | EP |
| 0405926 | Jan 1991 | EP |
| 0467546 | Jan 1992 | EP |
| 0541281 | May 1993 | EP |
| 0774715 | May 1997 | EP |
| 0809184 | Nov 1997 | EP |
| 0817040 | Jan 1998 | EP |
| 0899662 | Mar 1999 | EP |
| 0981090 | Feb 2000 | EP |
| 1384135 | Jan 2004 | EP |
| 2447361 | Sep 2008 | GB |
| 4198050 | Dec 2008 | JP |
| 4267443 | May 2009 | JP |
| WO 9513580 | May 1995 | WO |
| WO 9912098 | Mar 1999 | WO |
| 2004023317 | Mar 2004 | WO |
| WO 2006052872 | May 2006 | WO |
| Entry |
|---|
| U.S. Appl. No. 16/262,753, filed Jan. 30, 2019, Dornemann et al. |
| Armstead et al., “Implementation of a Campus-wide Distributed Mass Storage Service: The Dream vs. Reality,” IEEE, Sep. 11-14, 1995, pp. 190-199. |
| Arneson, “Mass Storage Archiving in Network Environments,” Digest of Papers, Ninth IEEE Symposium on Mass Storage Systems, Oct. 31, 1988-Nov. 3, 1988, pp. 45-50, Monterey, CA. |
| Brandon, J., “Virtualization Shakes Up Backup Strategy,” <http://www.computerworld.com>, Feb. 21, 2008, 3 pages. |
| Cabrera et al., “ADSM: A Multi-Platform, Scalable, Backup and Archive Mass Storage System,” Digest of Papers, Compcon '95, Proceedings of the 40th IEEE Computer Society International Conference, Mar. 5, 1995-Mar. 9, 1995, pp. 420-427, San Francisco, CA. |
| Celesti, et al., “Improving Virtual Machine Migration in Federated Cloud Environments”, 2010, pp. 61-67. |
| Chan, et al., “An Approach to High Availability for Cloud Servers with Snapshot Mechanism,” 2012, pp. 1-6. |
| Chen et al., “When Virtual Is Better Than Real”, IEEE 2001, pp. 133-138. |
| Chervenak, et al., “Protecting File Systems—A Survey of Backup Techniques,” 1998, pp. 17-31. |
| Chiappetta, Marco, “ESA Enthusiast System Architecture,” <http://hothardware.com/Articles/NVIDIA-ESA-Enthusiast-System-Architecture/>, Nov. 5, 2007, 2 pages. |
| CommVault Systems, Inc., “A CommVault White Paper: VMware Consolidated Backup (VCB) Certification Information Kit,” 2007, 23 pages. |
| CommVault Systems, Inc., “CommVault Solutions—VMware,” <http://www.commvault.com/solutions/vmware/>, accessed Apr. 30, 2014, 1 page. |
| CommVault Systems, Inc., “Enhanced Protection and Manageability of Virtual Servers,” Partner Solution Brief, 2008, 6 pages. |
| Cully, et al., “Remus: High Availability via Asynchronous Virtual Machine Replication”, 2008, pp. 161-174. |
| Data Protection for Large Vmware and Vblock Environments Using EMC Avamar Applied Technology, Nov. 2010, EMC Corporation, 26 pages. |
| Davis, D., “3 VMware Consolidated Backup (VCB) Utilities You Should Know,” Petri IT Knowlegebase, <http://www.petri.co.il/vmware-consolidated-backup-utilities.htm>, Nov. 16, 2007, 3 pages. |
| Davis, D., “Understanding VMware VMX Configuration Files,” Petri IT Knowledgebase, <http://www.petri.co.il/virtual_vmware_vmx_configuration_files.htm>, Nov. 16, 2007, 3 pages. |
| Davis, D., “VMware Server & Workstation Disk Files Explained,” Petri IT Knowledgebase, <http://www.petri.co.il/virtual_vmware_files_explained.htm>, May 3, 2008, 3 pages. |
| Davis, D., “VMware Versions Compared,” Petri IT Knowledgebase, <http://www.petri.co.il/virtual_vmware_versions_compared.htm>, Nov. 16, 2007, 3 pages. |
| Deng, et al., “Fast Saving and Restoring Virtual Machines with Page Compression”, 2011, pp. 150-157. |
| Eitel, “Backup and Storage Management in Distributed Heterogeneous Environments,” IEEE, Jun. 12-16, 1994, pp. 124-126. |
| Eldos Callback File System product information from https://www.eldos.com/clients/104-345.php retrieved on Dec. 30, 2016 in 2 pages. |
| Eldos Usermode filesystem for your Windows applications—Callback File System® (CBFS®)—Create and manage virtual filesystems and disks from your Windows applications retrieved from https://eldos.com/cbfs on Dec. 30, 2016 in 4 pages. |
| Fraser, et al., “Safe Hardware Access With the Xen Virtual Machine Monitor”, 1st Workshop on Operating System and Architectural Support for the demand IT Infrastructure (OASIS), 2004, pp. 1-10. |
| Gait, “The Optical File Cabinet: A Random-Access File System for Write-Once Optical Disks,” IEEE Computer, vol. 21, No. 6, pp. 11-22 (Jun. 1988) (see in particular figure 5 in p. 15 and recitation in claim 5). |
| Galan et al. “Service Specification in Cloud Environments Based on Extension to Oper Standards” COMSWARE Jun. 16-19, 09 Dublin, Ireland ACM. |
| Gibson, et al., “Implementing Preinstallation Environment Media for Use in User Support,” 2007, pp. 129-130. |
| Granger, et al., “Survivable Storage Systems”, 2001, pp. 184-195. |
| Gupta, et al., “GPFS-SNC: An enterprise storage framework for virtual-machine clouds”, 2011, pp. 1-10. |
| Haselhorst, et al., “Efficient Storage Synchronization for Live Migration in Cloud Infrastructures”, 2011, pp. 511-518. |
| Hirofuchio, Takahiro et al., “A live storage migration mechanism over wan and its performance evaluation,” 2009, pp. 67-74. |
| Hirofuchi, et al., “Enabling Instantaneous Relocation of Virtual Machines with a Lightweight VMM Extension”, 2010, pp. 73-83. |
| Hu, et al., “Virtual Machine based Hot-spare Fault-tolerant System”, 2009, pp. 429-432. |
| Hu, Wenjin et al., “A Quantitative Study of Virtual Machine Live Migration,” 2013, pp. 1-10. |
| Huff, “Data Set Usage Sequence Number,” IBM Technical Disclosure Bulletin, vol. 24, No. 5, Oct. 1981 New York, US, pp. 2404-2406. |
| Ibrahim, Shadi et al., “CLOUDLET: Towards MapReduce Implementation on Virtual Machines,” 2009, pp. 65-66. |
| Ismail et al., Architecture of Scalable Backup Service for Private Cloud, IEEE 2013, pp. 174-179. |
| Jander, “Launching Storage-Area Net,” Data Communications, US, McGraw Hill, NY, vol. 27, No. 4 (Mar. 21, 1998), pp. 64-72. |
| Javaraiah, et al., “Backup for Cloud and Disaster Recovery for Consumers and SMBs,” 2008, pp. 1-3. |
| Jhawar et al., “Fault Tolerance Management in Cloud Computing: A System-Level Perspective”, IEEE Systems Journal 7.2, 2013, pp. 288-297. |
| Jo, et al., “Efficient Live Migration of Virtual Machines Using Shared Storage”, 2013, pp. 1-10. |
| Kashyap “RLC—A Reliable approach to Fast and Efficient Live Migration of Virtual Machines in the Clouds” IEEE 2014 IEEE Computer Society. |
| Kim, et al., “Availability Modeling and Analysis of a Virtualized System,” 2009, pp. 365-371. |
| Kuo, et al., “A Hybrid Cloud Storage Architecture for Service Operational High Availability”, 2013, pp. 487-492. |
| Li et al. “Comparing Containers versus Virtual Machines for Achieving High Availability” 2015 IEEE. |
| Liang, et al., “A virtual disk environment for providing file system recovery”, 2006, pp. 589-599. |
| Lu et al.. “Virtual Machine Memory Access Tracing with Hypervisor Exclusive Cache”, Usenix Annual Technical Conference, 2007, pp. 29-43. |
| Mao, et al., “Read-Performance Optimization for Deduplication-Based Storage Systems in the Cloud”, 2014, pp. 1-22. |
| Microsoft Corporation, “How NTFS Works,” Windows Server TechCenter, <http://technet2.mircrosoft.com/windowsserver/en/library/8cc5891d-bf8e-4164-862d- dac5418c5948 . . . >, updated Mar. 28, 2003, internet accessed Mar. 26, 2008, 26 pages. |
| Migrate a Virtual Machine with Storage vMotion in the vSphere Client. http://pubs.vmware.com/vsphere-51/advanced/print/jsp?topic=/com.vmware.vsphere.vcent . . . Retrieved Aug. 12, 2014; 2 pages. |
| Nance et al., “Virtual Machine Introspection: Observation or Interference?”, 2008 IEEE. |
| Ng, Chun-Ho et al., “Live Deduplication Storage of Virtual Machine Images in an Open-Source Cloud,” 2011, pp. 80-99. |
| Nicolae, Bogdan et al., “A Hybrid Local Storage Transfer Scheme for Live Migration of 1/0 Intensive Workloads,” 2012, pp. 85-96. |
| Reingold, B. et al., “Cloud Computing: The Intersection of Massive Scalability, Data Security and Privacy (Part I),” LegalWorks, a Thomson Business, Jun. 2009, 5 pages. |
| Reingold, B. et al., “Cloud Computing: Industry and Government Developments (Part II),” LegalWorks, Sep. 2009, 5 pages. |
| Reingold, B. et al., “Cloud Computing: Whose Law Governs the Cloud? (Part III),” LegalWorks, Jan.-Feb. 2010, 6 pages. |
| Rosenblum et al., “The Design and Implementation of a Log-Structured File System,” Operating Systems Review SIGOPS, vol. 25, No. 5, New York, US, pp. 1-15 (May 1991). |
| Sanbarrow.com, “Disktype-table,” <http://sanbarrow.com/vmdk/disktypes.html>, internet accessed on Apr. 30, 2014, 4 pages. |
| Sanbarrow.com, “Files Used by a VM,” <http://sanbarrow.com/vmx/vmx-files-used-by-a-vm.html>, internet accessed on Apr. 30, 2014, 1 page. |
| Sanbarrow.com, “Monolithic Versus Split Disks,” <http://sanbarrow.com/vmdk/monolithicversusspllit.html>, internet accessed on Jul. 14, 2008, 2 pages. |
| Somasundaram et al., Information Storage and Management. 2009, pp. 251-281. |
| Tran, et al., “Efficient Cooperative Backup with Decentralized Trust Management”, 2012, pp. 1-25. |
| Travostino, et al., “Seamless live migration of virtual machines over the MAN/WAN”, 2006, pp. 901-907. |
| Tudoran, Radu et al., “Adaptive File Management for Scientific Workflows on the Azure Cloud,” 2013, pp. 273-281. |
| Vaghani, “Virtual Machine File System”, 2010, pp. 57-70. |
| VMware, Inc., “VMware Solution Exchange (VSX)” <http://www.vmware.com/appliances/learn/ovf.html>, 2014, 3 pages. |
| VMware, Inc., “OVF, Open Virtual Machine Format Specification, version 0.9,” White Paper, <http://www.vmware.com>, Sep. 7, 2007, 50 pages. |
| VMware, Inc., “The Open Virtual Machine Format Whitepaper for OVF Specification, version 0.9,” White Paper, <http://www.vmware.com>, 2007, 16 pages. |
| VMware, Inc., “Understanding VMware Consolidated Backup,” White Paper, <http://www.vmware.com>, accessed Apr. 30, 2014, 11 pages. |
| VMware, Inc., “Using VMware Infrastructure for Backup and Restore,” Best Practices, <http://www.vmware.com>, accessed Apr. 30, 2014, 20 pages. |
| VMware, Inc., “Virtual Disk API Programming Guide,” <http://www.vmware.com>, Revision 20080411, 2008, 44 pages. |
| VMware, Inc., “Virtual Disk Format 1.1,” VMware Technical Note, <http://www.vmware.com>, Revision 20071113, Version 1.1, 2007, 18 pages. |
| VMware, Inc., “Virtualized iSCSI SANS: Flexible, Scalable Enterprise Storage for Virtual Infrastructures,” White Paper, <http://www.vmware.com>, Mar. 2008, 13 pages. |
| VMware, Inc., “VMware Consolidated Backup,” Product Datasheet, <http://www.vmware.com>, 2009, 2 pages. |
| VMware, Inc., “VMware Consolidated Backup, Improvements in Version 3.5,” Information Guide, <http://www.vmware.com>, accessed Apr. 30, 2014, 11 pages. |
| VMware, Inc., “VMware ESX 3.5,” Product Datasheet, <http://www.vmware.com>, 2008, 4 pages. |
| VMware, Inc., “VMware GSX Server 3.2, Disk Types: Virtual and Physical,” <http://www.vmware.com/support/gsx3/doc/disks_types_gsx.html>, 2008, 2 pages. |
| VMware, Inc., “VMware OVF Tool,” Technical Note, <http://www.vmware.com>, 2007, 4 pages. |
| VMware, Inc., “VMware Workstation 5.0, Snapshots in a Process Tree,” <http://www.vmware.com/support/ws5/doc/ws_preserve_sshot_tree.html>, accessed Apr. 30, 2014, 1 page. |
| VMware, Inc., “VMware Workstation 5.0, Snapshots in a Linear Process,” <http:/www.vmware.com/support/ws5/doc/ws_preserve_sshot_linear.html>, internet accessed on 2014, 1 page. |
| VMware, Inc., “VMware Workstation 5.5, What Files Make Up a Virtual Machine?” <http://www.vmware.com/support/ws55/doc/ws_learning_files_in_a_vm.html>, 2014, 2 pages. |
| VMware Storage VMotion—Non-Disruptive Live Migration for Virtual Machine Storage Disk Files. Copyright 2009 VMware, Inc.; 2 pages. |
| Vrable, et al., “Cumulus: Filesystem Backup to the Cloud”, 2009, pp. 1-28. |
| VSphere Storage vMotion: Storage Management & Virtual Machine Migration.|http://www.vmware.com/products /vsphere/features/storage-vmotion Retrieved Aug. 12, 2014; 6 pages. |
| Wikipedia, “Cloud computing,” <http://en.wikipedia.org/wiki/Cloud-computing>, 2009, 11 pages. |
| Wikipedia, “Cluster (file system),” <http://en.wikipedia.org/wiki/Cluster_%28file_system%29>, Sep. 2, 2008, 1 page. |
| Wikipedia, “Cylinder-head-sector,” <http://en.wikipedia.org/wiki/Cylinder-head-sector>, Jan. 4, 2009, 6 pages. |
| Wikipedia, “File Allocation Table,” <http://en.wikipedia.org/wiki/File_Allocation_Table>, Dec. 3, 2008, 12 pages. |
| Wikipedia, “Logical Disk Manager,” <http://en.wikipedia.org/wiki/Logical_Disk_Manager>, Nov. 16, 2007, 3 pages. |
| Wikipedia, “Logical Volume Management,” <http://en.wikipedia.org/wiki/Logical_volume_management>, Oct. 27, 2008, 3 pages. |
| Wikipedia, “Storage Area Network,” <http://en.wikipedia.org/wiki/Storage_area_network>, Dec. 5, 2008, 5 pages. |
| Wikipedia, “Virtualization,” <http://en.wikipedia.org/wiki/Virtualization>, Apr. 29, 2014, 7 pages. |
| Wood, et al., “Disaster Recovery as a Cloud Service: Economic Benefits & Deployment Challenges”, 2010, pp. 1-7. |
| Yang, et al., “Toward Reliable Data Delivery for Highly Dynamic Mobile Ad Hoc Networks,” 2012, pp. 111-124. |
| Yang, et al., “TRAP-Array: A Disk Array Architecture Providing Timely Recovery to Any Point-in-time,” 2006, pp. 1-12. |
| Yoshida et al., “Orthros: A High-Reliability Operating System with Transmigration of Processes,” 2013, pp. 318-327. |
| Zhao, et al., “Adaptive Distributed Load Balancing Algorithm based on Live Migration of Virtual Machines in Cloud”, 2009, pp. 170-175. |
| Zhao, et al., Supporting Application-Tailored Grid File System Sessions with WSRF-Based Services, Advanced Computing and Information Systems Laboratory (ACIS), pp. 24-33, dated Aug. 2005. |
| International Search Report and Written Opinion for PCT/US2011/054374, dated May 2, 2012, 7 pages. |
| International Preliminary Report on Patentability and Written Opinion for PCT/US2011/054374, dated Apr. 2, 2013, 9 pages. |
| Case No. 1:20-cv-00524-MN, Order Dismissing with Prejudice DDE-1-20-cv-00524-101, filed Aug. 31, 2021, in 1 page. |
| Case No. 1:20-cv-00524-MN, Answer_DDE-1-20-cv-00524-45, filed Feb. 16, 2021, in 25 pages. |
| Case No. 1:20-cv-00525-CFC-CJB, Joint Appendix of Exhibits 1-6, filed Jan. 13, 2022, in 224 pages. |
| Case No. 20-525-MN-CJB, Farnan Letter DDE-1-20-cv-00525-111, filed Oct. 6, 2021, in 2 pages. |
| Case No. 20-525-MN-CJB, Farnan Letter Exibit A DDE-1-20-cv-00525-111-1, filed Oct. 6, 2021, in 7 pages. |
| Case No. 20-525-MN-CJB, Joint Claim Construction Brief DDE-1-20-cv-00525-107, filed Oct. 1, 2021, in 79 pages. |
| Case No. 1:20-cv-00525-MN, First Amended Answer DDE-1-20-cv-00525-95, filed Jul. 23, 2021, in 38 pages. |
| Case No. 1:20-cv-00525-MN, Order DDE-1-20-cv-00525-38_DDE-1-20-cv-00524-42, filed Feb. 10, 2021, in 4 pages. |
| PTAB-IPR2021-00609—Exhibit 1005—US9639428 (Boda), Issue Date May 2, 2017, in 12 pages. |
| PTAB-IPR2021-00609—Exhibit 1006—US20150212895A1 (Pawar), Publication Date Jul. 30, 2015, in 60 pages. |
| PTAB-IPR2021-00609—Exhibit 1007—US9665386 (Bayapuneni), Issue Date May 30, 2017, in 18 pages. |
| PTAB-IPR2021-00609—Exhibit 1014—Virtual Volumes and the SDDC—Virtual Blocks, Internet Archives on Sep. 29, 2015, in 4 pages. |
| PTAB-IPR2021-00609—Exhibit 1020—Assignment Docket—Vaghani, Nov. 11, 2011, in 1 page. |
| PTAB-IPR2021-00609—Exhibit 1024—CommVault v. Rubrik Complaint, filed on Apr. 21, 2020, in 29 pages. |
| PTAB-IPR2021-00673—('723) Sur-Reply FINAL, filed Aug. 16, 2021, in 7 pages. |
| PTAB-IPR2021-00673—673 674 Termination Order, Sep. 1, 2021, in 4 pages. |
| PTAB-IPR2021-00673—Exhibit 1004—esxRangerProfessionalUserManual v.3.1, 2006 in 102 pages. |
| PTAB-IPR2021-00673—Exhibit 1005—VC_Users_Manual_11_NoRestriction, Copyright 1998-2004, in 466 pages. |
| PTAB-IPR2021-00673—Exhibit 1006—US8635429—Naftel, Issue Date Jan. 21, 2014, in 12 pages. |
| PTAB-IPR2021-00673—Exhibit 1009—US8209680—Le, Issue Date Jun. 26, 2012, in 55 pages. |
| PTAB-IPR2021-00673—Exhibit 1010—Virtual Machine Monitors Current Technology and Future Trends, May 2005 in 9 pages. |
| PTAB-IPR2021-00673—Exhibit 1011—Virtualization Overview, Copyright 2005, 11 pages. |
| PTAB-IPR2021-00673—Exhibit 1017—US20060259908A1—Bayer, Publication Date Nov. 16, 2006, in 8 pages. |
| PTAB-IPR2021-00673—Exhibit 1020—US8191063—Shingai, May 29, 2012, in 18 pages. |
| PTAB-IPR2021-00673—Exhibit 1022—US8458419—Basler, Issue Date Jun. 4, 2013, in 14 pages. |
| PTAB-IPR2021-00673—Exhibit 1025—D.Hall_Internet Archive Affidavit & Ex. A (source html view), dated Jan. 27, 2021, in 94 pages. |
| PTAB-IPR2021-00673—Exhibit 1027—How to cheat at configuring VMware ESX server (excerpted), 2007, in 16 pages. |
| PTAB-IPR2021-00673—Exhibit 1029—Hall-Ellis Declaration, dated Feb. 15, 2021, in 55 pages. |
| PTAB-IPR2021-00673—Exhibit 1033—ZDNet_ Reviews _ ZDNet, printed on Jan. 15,02021, in 33 pages. |
| PTAB-IPR2021-00673—Exhibit 1034—Understanding VMware Consolidated Backup, 2007, 11 pages. |
| PTAB-IPR2021-00673—Exhibit 1035—techtarget.com news links—May 2007, May 20, 2007, in 39 pages. |
| PTAB-IPR2021-00673—Exhibit 1041—InfoWorld—May 1, 2006, May 1, 2006, in 15 pages. |
| PTAB-IPR2021-00673—Exhibit 1043—InfoWorld—Feb. 5, 2007, Feb. 5, 2007, in 22 pages. |
| PTAB-IPR2021-00673—Exhibit 1045—InformationWeek—Aug. 14, 2006, Aug. 14, 2006, in 17 pages. |
| PTAB-IPR2021-00673—Exhibit 1046—esxRanger Ably Backs Up VMs, May 2, 2007 in 6 pages. |
| PTAB-IPR2021-00673—Exhibit 1054—redp3939—Server Consolidation with VMware ESX Server, Jan. 12, 2005 in 159 pages. |
| PTAB-IPR2021-00673—Exhibit 1056—Apr. 21, 2020 [1] Complaint, filed Apr. 21, 2020, in 300 pages. |
| PTAB-IPR2021-00673—Exhibit 1057—Feb. 17, 2021 (0046) Scheduling Order, filed Feb. 17, 2021, in 15 pages. |
| PTAB-IPR2021-00673—Exhibit 1058—Novell Netware 5.0-5.1 Network Administration (Doering), 2001, in 40 pages. |
| PTAB-IPR2021-00673—Patent Owner Mandatory Notices, filed Apr. 7, 2021, 6 pages. |
| PTAB-IPR2021-00674—Exhibit 1003—US9740723 file history, Issue Date Aug. 22, 2017, in 594 pages. |
| PTAB-IPR2021-00674—Exhibit 1011—HTTP The Definitive Guide excerpts (Gourley), 2002, in 77 pages. |
| PTAB-IPR2021-00674—Exhibit 1014—Rob's Guide to Using VMWare excerpts (Bastiaansen), Sep. 2005, in 178 pages. |
| PTAB-IPR2021-00674—Exhibit 1016—US7716171 (Kryger), Issue Date May 11, 2010, in 18 pages. |
| PTAB-IPR2021-00674—Exhibit 1019—Commvault v. Rubrik Complaint, Filed Apr. 21, 2020, in 29 pages. |
| PTAB-IPR2021-00674—Exhibit 1020—Commvault v. Rubrik Scheduling Order, Filed Feb. 17, 2021, in 15 pages. |
| PTAB-IPR2021-00674—Exhibit 2003—Shea, retrieved Jun. 10, 2021, in 5 pages. |
| PTAB-IPR2021-00674—Exhibit IPR2021-00674 Joint Request to Seal Settlement Agreement, dated Aug. 31, 2021, in 4 pages. |
| PTAB-IPR2021-00674—Joint Motion to Terminate, Filed Aug. 31, 2021, in 7 pages. |
| PTAB-IPR2021-00674—Termination Order, filed Sep. 1, 2021, in 4 pages. |
| Case No. 1:20-cv-00524-MN, Oral Order DDE-1-20-cv-00524-86_DDE-1-20-cv-00525-87, filed Jun. 29, 2021, in 1 page. |
| Case No. 1:20-cv-00525-CFC-CJB, Joint Appendix of Exhibits 1-6, filed Jan. 13, 2022, in 2 pages. |
| Case No. 20-525-MN-CJB, Joint Claim Construction Statement DDE-1-20-cv-00525-119, filed Oct. 29, 2021, in 12 pages. |
| PTAB-IPR2021-00609—Exhibit 1004—US8677085 (Vaghani), Issue Date Mar. 18, 2014, in 44 pages. |
| PTAB-IPR2021-00609—Exhibit 1017—US8621460 (Evans), Issue Date Dec. 31, 2013, in 39 pages. |
| PTAB-IPR2021-00609—Exhibit 1022—MS Computer Dictionary Backup labeled, 2002 in 3 pages. |
| PTAB-IPR2021-00609—Joint Motion to Terminate. Filed Aug. 31, 2021, in 7 pages. |
| PTAB-IPR2021-00673—Exhibit 1002—Declaration_Jagadish_EXSRanger, filed Mar. 16, 2021, in 191 pages. |
| PTAB-IPR2021-00673—Exhibit 1036—ITPro 2007 Issue 5 (excerpted), Sep.-Oct. 2007 in 11 pages. |
| PTAB-IPR2021-00673—Exhibit 1051—Distributed_File_System_Virtualization, Jan. 2006, pp. 45-56, in 12 pages. |
| PTAB-IPR2021-00673—Exhibit 1055—Server Consolidation with VMware ESX Server _ Index Page, Jan. 12, 2005, in 2 pages. |
| PTAB-IPR2021-00673—Exhibit 2003 VM Backup Guide 3.0.1, updated Feb. 21, 2008, in 78 pages. |
| PTAB-IPR2021-00674—Exhibit 1004—Virtual Machine Monitors Current Technology and Future Trends, May 2005, in 9 pages. |
| PTAB-IPR2021-00674—Exhibit 1009—60920847 (Le Provisional), Filed Mar. 29, 2007, in 70 pages. |
| PTAB-IPR2021-00674—Exhibit 1017—RFC2609, Jun. 1999, in 33 pages. |
| PTAB-IPR2021-00674—Exhibit 1018—MS Dictionary excerpt, 2002, in 3 pages. |
| PTAB-IPR2021-00674—Response to Notice Ranking Petitions FINAL, filed Jul. 8, 2021, in 7 pages. |
| Case No. 1:20-cv-00524-MN, Order_DDE-1-20-cv-00525-38_DDE-1-20-cv-00524-42, filed Feb. 10, 2021, in 4 pages. |
| Case No. 1:20-cv-00525-MN-CJB, Oral Order DDE-1-20-cv-00524-78_DDE-1-20-cv-00525-77, dated May 24, 2021, in 1 page. |
| Case No. 120-cv-00525-MN—Stipulation of Dismissal, filed Jan. 27, 2022, in 2 pages. |
| Case No. 1:20-cv-00525-MN, Oral Order DDE-1-20-cv-00524-86_DDE-1-20-cv-00525-87, filed Jun. 29, 2021, in 1 page. |
| PTAB-IPR2021-00609—('048) POPR Final, filed Jun. 16, 2021, in 28 pages. |
| PTAB-IPR2021-00609—Mar. 10, 2021 IPR Petition—pty, Mar. 10, 2021, in 89 pages. |
| PTAB-IPR2021-00609—Exhibit 1002—Sandeep Expert Declaration, dated Mar. 10, 2021, in 176 pages. |
| PTAB-IPR2021-00609—Exhibit 1009—Virtualization Essentials—First Edition (2012)—Excerpted, 2012, in 106 pages. |
| PTAB-IPR2021-00609—Exhibit 1011—Virtualization Overview, 2005, in 11 pages. |
| PTAB-IPR2021-00609—Exhibit 1015—NEC White Paper-VMWare vSphere Virtual Volumes (2015), Internet Archives Dec. 4, 2015 in 13 pages. |
| PTAB-IPR2021-00609—Exhibit 1019—Assignment—Vaghani to VMWare, Feb. 8, 2012, in 8 pages. |
| PTAB-IPR2021-00609—Exhibit 1025—CommVault v. Cohesity Complaint, filed on Apr. 21, 2020, in 28 pages. |
| PTAB-IPR2021-00609—Exhibit 2001—Prosecution History_Part1, Issue Date Feb. 19, 2019, in 300 pages, Part 1 of 2. |
| PTAB-IPR2021-00609—Exhibit 2001—Prosecution History_Part2, Issue Date Feb. 19, 2019, in 265 pages, Part 2 of 2. |
| PTAB-IPR2021-00609—Exhibit 3001—RE_ IPR2021-00535, 2021-00589, 2021-00590, 2021-00609, 2021-00673, 2021-00674, 2021-00675, dated Aug. 30, 2021, in 2 pages. |
| PTAB-IPR2021-00609—Joint Request to Seal Settlement Agreement, filed Aug. 31, 2021, in 4 pages. |
| PTAB-IPR2021-00673—('723) POPR Final, filed Jun. 30, 2021, in 70 pages. |
| PTAB-IPR2021-00673—Exhibit 1001—U.S. Pat. No. 9,740,723, Issue Date Aug. 22, 2017, in 51 pages. |
| PTAB-IPR2021-00673—Exhibit 1003—FH 9740723, Issue Date Aug. 22, 2017, in 594 pages. |
| PTAB-IPR2021-00673—Exhibit 1008—US20060224846A1—Amarendran, Oct. 5, 2006, in 15 pages. |
| PTAB-IPR2021-00673—Exhibit 1012—Let's Get Virtual A Look at Today's Virtual Server, May 14, 2007 in 42 pages. |
| PTAB-IPR2021-00673—Exhibit 1013—U.S. Pat. No. 8,135,930—Mattox, Issue Date Mar. 13, 2012, in 19 pages. |
| PTAB-IPR2021-00673—Exhibit 1016—US20080091655A1—Gokhale, Publication Date Apr. 17, 2008, in 14 pages. |
| PTAB-IPR2021-00673—Exhibit 1021—US8959509B1—Sobel, Issue Date Feb. 17, 2015, in 9 pages. |
| PTAB-IPR2021-00673—Exhibit 1024—esxRangerProfessionalUserManual, 2006, in 103 pages. |
| PTAB-IPR2021-00673—Exhibit 1026—Scripting VMware (excerpted) (GMU), 2006, in 19 pages. |
| PTAB-IPR2021-00673—Exhibit 1030—B. Dowell declaration, dated Oct. 15, 2020, in 3 pages. |
| PTAB-IPR2021-00673—Exhibit 1038—InfoWorld—Mar. 6, 2006, Mar. 6, 2006, in 18 pages. |
| PTAB-IPR2021-00673—Exhibit 1039—InfoWorld—Apr. 10, 2006, Apr. 10, 2006, in 18 pages. |
| PTAB-IPR2021-00673—Exhibit 1040—InfoWorld—Apr. 17, 2006, Apr. 17, 2006, in 4 pages. |
| PTAB-IPR2021-00673—Exhibit 1047—Businesswire—Vizioncore Inc. Releases First Enterprise-Class Hot Backup and Recovery Solution for VMware Infrastructure 3, Aug. 31, 2006, in 2 pages. |
| PTAB-IPR2021-00673—Exhibit 1049—Dell Power Solutions—Aug. 2007 (excerpted), Aug. 2007, in 21 pages. |
| PTAB-IPR2021-00673—Exhibit 1052—Distributed File System Virtualization article abstract, 2006, in 12 pages. |
| PTAB-IPR2021-00673—Exhibit 1053—Cluster Computing _ vol. 9, issue 1, Jan. 2006, in 5 pages. |
| PTAB-IPR2021-00673—Exhibit 1059—US20060064555A1 (Prahlad 555), Publication Date Mar. 23, 2006, in 33 pages. |
| PTAB-IPR2021-00673—Exhibit 2001 Jones Declaration, filed Jun. 30, 2021, in 35 pages. |
| PTAB-IPR2021-00673—Exhibit 2002 VM Backup Guide 3.0.1, updated Nov. 21, 2007, 74 pages. |
| PTAB-IPR2021-00673—Joint Motion to Terminate, filed Aug. 31, 2021, in 7 pages. |
| PTAB-IPR2021-00673—Joint Request to Seal Settlement Agreement, filed Aug. 31, 2021, in 4 pages. |
| PTAB-IPR2021-00674—Mar. 31, 2021 723 Petition, filed Mar. 31, 2021, in 87 pages. |
| PTAB-IPR2021-00674—Exhibit 1001—U.S. Pat. No. 9,740,723, Issue Date Aug. 22, 2017, in 51 pages. |
| PTAB-IPR2021-00674—Exhibit 1002—Jagadish Declaration, dated Mar. 31, 2021, in 200 pages. |
| PTAB-IPR2021-00674—Exhibit 1007—U.S. Pat. No. 8,458,419—Basler, Issue Date Jun. 4, 2013, in 14 pages. |
| PTAB-IPR2021-00674—Exhibit 1008—US20080244028A1 (Le), Publication Date Oct. 2, 2008, in 22 pages. |
| PTAB-IPR2021-00674—Exhibit 1010—Discovery Systems in Ubiquitous Computing (Edwards), 2006, in 8 pages. |
| PTAB-IPR2021-00674—Exhibit 1013—Scripting VMware excerpts (Muller), 2006, in 66 pages. |
| PTAB-IPR2021-00674—Exhibit 1015—Carrier, 2005 in 94 pages. |
| PTAB-IPR2021-00674—Exhibit 1022—Hall-Ellis Declaration, dated Mar. 30, 2021, in 291 pages. |
| PTAB-IPR2021-00674—Exhibit 1024—Rob's Guide—Amazon review (Jan. 4, 2007), retrieved Jan. 4, 2007, in 5 pages. |
| PTAB-IPR2021-00674—Exhibit 3001, dated Aug. 30, 2021, in 2 pages. |
| Arneson, David A., “Development of Omniserver,” Control Data Corporation, Tenth IEEE Symposium on Mass Storage Systems, May 1990, ‘Crisis in Mass Storage’ Digest of Papers, pp. 88-93, Monterey, CA. |
| Case No. 1:20-cv-00524-MN, Complaint_DDE-1-20-cv-00524-1, filed on Apr. 21, 2020 in 28 pages. |
| Case No. 1:20-cv-00524-MN, First_Amended_Answer_DDE-1-20-cv-00524-96, filed Jul. 23, 2021, in 41 pages. |
| Case No. 1:20-cv-00524-MN, Stipulation DDE-1-20-cv-00524-93, filed Jul. 14, 2021, in 3 pages. |
| Case No. 1:20-cv-00525-CFC-CJB, Joint Claim Construction Brief On Remaining Disputed Terms, filed Jan. 13, 2022, in 54 pages. |
| Case No. 1-20-cv-00524-MN, Amended_Complaint_DDE-1-20-cv-00524-13, filed Jul. 27, 2020, in 30 pages. |
| Case No. 1-20-cv-00525-38-MN, Amended Complaint DDE-1-20-cv-00525-15, filed Jul. 27, 2020, in 30 pages. |
| Case No. 1:20-cv-00525-MN, Joint Claim Construction Brief Exhibits DDE-1-20-cv-00525-107-1, filed Oct. 1, 2021 in 488 pages in 7 parts. |
| Commvault Systems, Inc. v. Cohesity Inc., Civil Action No. 1:20-cv-00525, U.S. District Court, District of Delaware, Complaint filed on Apr. 21, 2020. |
| PTAB-IPR2021-00609—Exhibit 1001—U.S. Appl. No. 10/210,048, Issue Date Feb. 19, 2019, in 49 pages. |
| PTAB-IPR2021-00609—Exhibit 1003—U.S. Pat. No. 9,354,927 (Hiltgen), Issue Date May 31, 2016, in 35 pages. |
| PTAB-IPR2021-00609—Exhibit 1008—Popek and Golberg, Jul. 1974, in 10 pages. |
| PTAB-IPR2021-00609—Exhibit 1010—Virtual Machine Monitors Current Technology and Future Trends, May 2005, in 9 pages. |
| PTAB-IPR2021-00609—Exhibit 1012—Let's Get Virtual A Look at Today's Virtual Server, May 14, 2007, in 42 pages. |
| PTAB-IPR2021-00609—Exhibit 1013—Virtual Volumes, Jul. 22, 2016, in 2 pages. |
| PTAB-IPR2021-00609—Exhibit 1016—EMC Storage and Virtual Volumes, Sep. 16, 2015 in 5 pages. |
| PTAB-IPR2021-00609—Exhibit 1018—U.S. Pat. No. 7,725,671 (Prahlad), Issue Date May 25, 2010, in 48 pages. |
| PTAB-IPR2021-00609—Exhibit 1021—Dive into the VMware ESX Server hypervisor—IBM Developer, Sep. 23, 2011, in 8 pages. |
| PTAB-IPR2021-00609—Exhibit 1023—Jul. 7, 2014_VMware vSphere Blog, Jun. 30, 2014, 4 pages. |
| PTAB-IPR2021-00609—Exhibit 1026—Feb. 17, 2021 (0046) Scheduling Order, filed on Feb. 17, 2021, in 15 pages. |
| PTAB-IPR2021-00609—Exhibit 2002—Jones Declaration, dated Jun. 16, 2021, in 38 pages. |
| PTAB-IPR2021-00609—Termination Order, Sep. 1, 2021, in 4 pages. |
| PTAB-IPR2021-00673—Mar. 17, 2021_Petition_723, filed Mar. 17, 2021, in 98 pages. |
| PTAB-IPR2021-00673—723 patent IPR—Reply to POPR, filed Aug. 9, 2021, in 6 pages. |
| PTAB-IPR2021-00673—Exhibit 1007—US20070288536A1—Sen, Issue Date Dec. 13, 2007, in 12 pages. |
| PTAB-IPR2021-00673—Exhibit 1014—U.S. Pat. No. 8,060,476—Afonso, Issue Date Nov. 15, 2011, in 46 pages. |
| PTAB-IPR2021-00673—Exhibit 1015—U.S. Pat. No. 7,823,145—Le 145, Issue Date Oct. 26, 2010, in 24 pages. |
| PTAB-IPR2021-00673—Exhibit 1018—U.S. Pat. No. 8,037,016—Odulinski, Issue Date Oct. 11, 2011, in 20 pages. |
| PTAB-IPR2021-00673—Exhibit 1019—U.S. Pat. No. 7,925,850—Waldspurger, Issue Date Apr. 12, 2011, in 23 pages. |
| PTAB-IPR2021-00673—Exhibit 1023—D. Hall_Internet Archive Affidavit & Ex. A, dated Jan. 20, 2021, in 106 pages. |
| PTAB-IPR2021-00673—Exhibit 1028—Robs Guide to Using VMware (excerpted), Sep. 2005 in 28 pages. |
| PTAB-IPR2021-00673—Exhibit 1031—Vizioncore esxEssentials Review ZDNet, Aug. 21, 2007, in 12 pages. |
| PTAB-IPR2021-00673—Exhibit 1032—ZDNet Search on_ howorth—p. 6 _, printed on Jan. 15, 2021, ZDNet 3 pages. |
| PTAB-IPR2021-00673—Exhibit 1037—InfoWorld—Feb. 13, 2006, Feb. 13, 2006, in 17 pages. |
| PTAB-IPR2021-00673—Exhibit 1042—InfoWorld—Sep. 25, 2006, Sep. 25, 2006, in 19 pages. |
| PTAB-IPR2021-00673—Exhibit 1044—InfoWorld—Feb. 12, 2007, Feb. 12, 2007, in 20 pages. |
| PTAB-IPR2021-00673—Exhibit 1048—Vizioncore Offers Advice to Help Users Understand VCB for VMwar, Jan. 23, 2007 in 3 pages. |
| PTAB-IPR2021-00673—Exhibit 1050—communities-vmware-t5-VI-VMware-ESX-3-5-Discussions, Jun. 28, 2007, in 2 pages. |
| PTAB-IPR2021-00673—Exhibit 1060—Carrier Book, 2005, in 94 pages. |
| PTAB-IPR2021-00673—Exhibit 3001 RE_ IPR2021-00535, 2021-00589, 2021-00590, 2021-00609, 2021-00673, 2021-00674, 2021-00675, Aug. 30, 2021, in 2 pages. |
| PTAB-IPR2021-00674—('723) POPR Final, filed Jul. 8, 2021, in 70 pages. |
| PTAB-IPR2021-00674—Mar. 31, 2021 Explanation for Two Petitions, filed Mar. 31, 2021, in 9 pages. |
| PTAB-IPR2021-00674—Exhibit 1005—Virtualization Overview, 2005, 11 pages. |
| PTAB-IPR2021-00674—Exhibit 1006—Let's Get Virtual_Final Stamped, May 14, 2007, in 42 pages. |
| PTAB-IPR2021-00674—Exhibit 1012—VCB White Paper (Wayback Mar. 21, 2007), retrieved Mar. 21, 2007, Copyright Date 1998-2006, in 6 pages. |
| PTAB-IPR2021-00674—Exhibit 1021—Duncan Affidavit, Dated Mar. 3, 2021, in 16 pages. |
| PTAB-IPR2021-00674—Exhibit 1023—Digital_Data_Integrity_2007_Appendix_A_UMCP, 2007,, in 24 pages. |
| PTAB-IPR2021-00674—Exhibit 2001—esxRanger, 2006, in 102 pages. |
| PTAB-IPR2021-00674—Exhibit 2002—Want, 1995, in 31 pages. |
| PTAB-IPR2021-00674—Exhibit 2004—Jones Declaration, Dated Jul. 8, 2021, in 36 pages. |
| Number | Date | Country | |
|---|---|---|---|
| 20220404984 A1 | Dec 2022 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16667746 | Oct 2019 | US |
| Child | 17855611 | US | |
| Parent | 15979215 | May 2018 | US |
| Child | 16667746 | US | |
| Parent | 15394556 | Dec 2016 | US |
| Child | 15979215 | US | |
| Parent | 14549365 | Nov 2014 | US |
| Child | 15394556 | US |
