This is a continuation application for patent entitled to a filing date and claiming the benefit of earlier-filed U.S. Pat. No. 11,444,849, issued Sep. 13, 2022, herein incorporated by reference in its entirety, which is a continuation of U.S. Pat. No. 10,999,157, issued May 4, 2021, which is a continuation of U.S. Pat. No. 10,164,841, issued Dec. 25, 2018.
Embodiments described herein relate to storage systems, and more particularly, to techniques for generating a read-only GUI for a storage system via a cloud-based assist service.
As computer memory storage and data bandwidth increase, so does the amount and complexity of data that businesses daily manage. Large-scale distributed storage systems, such as data centers, typically run many business operations. A distributed storage system may be coupled to client computers interconnected by one or more networks. To manage and store ever increasing amounts of data, storage systems tend to grow in size and complexity over time. Due to the expanding nature of data and increasing complexity of storage systems, managing storage environments can be a difficult and complex task.
Various embodiments of systems and methods for using cloud-assist logic to generate a read-only GUI of the status of a storage system.
In one embodiment, a storage system may comprise one or more storage subsystems (e.g., storage arrays), and the storage system may be coupled to a cloud-assist service. The storage subsystems may be configured to generate log data and phone home the log data on a periodic basis to the cloud-assist service. The cloud-assist service may be configured to save the log data and then accept a login from a customer or administrator to generate a read-only GUI which allows the user to view the status of the storage subsystem as if they were directly connected to the storage subsystem. The read-only GUI allows the user to view the status of the storage subsystem even if the storage subsystem is offline, malfunctioning, or otherwise unavailable.
The first storage subsystem may be configured to generate a local GUI to allow users to view the status of the first storage subsystem when directly connected to the first storage subsystem. In one embodiment, configuration and performance data used to present the GUI locally on the first storage subsystem for a local administrator may be sent to the cloud-assist service. In one embodiment, the cloud-assist service may be configured to create the read-only GUI by simulating the responses for configuration and performance data which the first storage subsystem would normally generate for the local GUI. The cloud-assist service may simulate the responses using the configuration and performance data received as log data from the first storage subsystem.
In one embodiment, if an administrator of the first storage subsystem is off-site, instead of logging in through their organization's firewall to the first storage subsystem, the administrator can login to the cloud-assist service to view the read-only GUI showing the status of the first storage subsystem. The read-only GUI may have the same appearance the administrator is accustomed to seeing when they login to the local GUI of the first storage subsystem. The read-only GUI may also recreate previous points in time if the administrator desires to see a historical view of the status of the first storage subsystem.
These and other embodiments will become apparent upon consideration of the following description and accompanying drawings.
While the methods and mechanisms described herein are susceptible to various modifications and alternative forms, specific embodiments are shown by way of example in the drawings and are herein described in detail. It should be understood, however, that drawings and detailed description thereto are not intended to limit the methods and mechanisms to the particular form disclosed, but on the contrary, are intended to cover all modifications, equivalents and alternatives apparent to those skilled in the art once the disclosure is fully appreciated.
In the following description, numerous specific details are set forth to provide a thorough understanding of the methods and mechanisms presented herein. However, one having ordinary skill in the art should recognize that the various embodiments may be practiced without these specific details. In some instances, well-known structures, components, signals, computer program instructions, and techniques have not been shown in detail to avoid obscuring the approaches described herein. It will be appreciated that for simplicity and clarity of illustration, elements shown in the figures have not necessarily been drawn to scale. For example, the dimensions of some of the elements may be exaggerated relative to other elements.
This specification includes references to “one embodiment”. The appearance of the phrase “in one embodiment” in different contexts does not necessarily refer to the same embodiment. Particular features, structures, or characteristics may be combined in any suitable manner consistent with this disclosure. Furthermore, as used throughout this application, the word “may” is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include”, “including”, and “includes” mean including, but not limited to.
Terminology. The following paragraphs provide definitions and/or context for terms found in this disclosure (including the appended claims):
“Comprising.” This term is open-ended. As used in the appended claims, this term does not foreclose additional structure or steps. Consider a claim that recites: “A system comprising a first storage subsystem . . . ” Such a claim does not foreclose the system from including additional components (e.g., a network, a server, a display device).
“Configured To.” Various units, circuits, or other components may be described or claimed as “configured to” perform a task or tasks. In such contexts, “configured to” is used to connote structure by indicating that the units/circuits/components include structure (e.g., circuitry) that performs the task or tasks during operation. As such, the unit/circuit/component can be said to be configured to perform the task even when the specified unit/circuit/component is not currently operational (e.g., is not on). The units/circuits/components used with the “configured to” language include hardware—for example, circuits, memory storing program instructions executable to implement the operation, etc. Reciting that a unit/circuit/component is “configured to” perform one or more tasks is expressly intended not to invoke 35 U.S.C. § 112, paragraph (f), for that unit/circuit/component. Additionally, “configured to” can include generic structure (e.g., generic circuitry) that is manipulated by software and/or firmware (e.g., an FPGA or a general-purpose processor executing software) to operate in a manner that is capable of performing the task(s) at issue. “Configured to” may also include adapting a manufacturing process (e.g., a semiconductor fabrication facility) to fabricate devices (e.g., integrated circuits) that are adapted to implement or perform one or more tasks.
“Based On.” As used herein, this term is used to describe one or more factors that affect a determination. This term does not foreclose additional factors that may affect a determination. That is, a determination may be solely based on those factors or based, at least in part, on those factors. Consider the phrase “determine A based on B.” While B may be a factor that affects the determination of A, such a phrase does not foreclose the determination of A from also being based on C. In other instances, A may be determined based solely on B.
Referring now to
In various embodiments, storage system 105 may include any number of storage controllers and any number of storage devices. Storage system 105 may be any type of storage system depending on the embodiment. For example, in one embodiment, storage system 105 may be a storage array. The storage array may utilize different types of storage device technology, depending on the embodiment. For example, in one embodiment, the storage array may utilize flash (or solid-state) storage devices and may be an all-flash storage array. In other embodiments, the storage array may utilize other types of storage device technology. It is noted that storage system 105 may also be referred to as a storage subsystem.
In various embodiments, cloud assist logic 110 may include program instructions which when executed by a processor are configured to generate a read-only GUI of the status of storage system 105. Cloud assist logic 110 may be configured to execute on a server, computer, or other computing device to perform the functions described herein. In some embodiments, cloud assist logic 110 may include hardware and/or control logic configured to perform the functions and tasks described herein. For example, cloud assist logic 110 may be implemented using any combination of dedicated hardware (e.g., application specific integrated circuit (ASIC)), configurable hardware (e.g., field programmable gate array (FPGA)), and/or software (e.g., program instructions) executing on one or more processors. It is noted that cloud assist logic 110 may also be referred to as cloud-based logic 110 or cloud assist service 110.
In one embodiment, cloud assist logic 110 may execute within a cloud computing platform provided by a web services provider (e.g., Amazon). The cloud computing platform may provide large amounts of computing assets and storage availability to cloud assist logic 110. In another embodiment, cloud assist logic 110 may execute on a separate system or network external to the local network of storage system 105.
Storage system 105 may be configured to generate a local graphical user interface (GUI) 135 to allow a local administrator or other users to view the status of storage system 105 and to manage the performance of storage system 105. In one embodiment, the log data generated by storage system 105 may be repurposed by cloud assist logic 110 to create read-only GUI 140 to allow a remote administrator or other user who is not able to login directly to storage system 105 to view the status of storage system 105 in the same familiar GUI presented locally on local GUI 135. For example, a user may be travelling or off-site and may not have local access to storage system 105. In some cases, the user may not wish to login through the local network of storage system 105 for a variety of reasons. For example, the user may be on an insecure network or insecure device and may not wish to compromise the security of storage system 105. Therefore, the user may login to cloud assist logic 110 via network 120 to allow the user to view the read-only GUI 140 generated from the log data retrieved from storage system 105.
Turning now to
Storage array 205 may be configured to generate performance data and send the performance data to cloud assist logic 250. Cloud assist logic 250 may be configured to generate a read-only GUI from the received performance data to allow users to remotely login and view the status of storage array 205. The read-only GUI may have the same or a substantially similar view as the local GUI which storage array 205 generates for local users to manage storage array 205.
Storage controller 210 of storage array 205 may be coupled directly to client computer system 225, and storage controller 210 may be coupled remotely over network 220 to client computer system 215. Clients 215 and 225 are representative of any number of clients which may utilize storage system 200 for storing and accessing data. It is noted that some systems may include only a single client, connected directly or remotely to storage controller 210. It is also noted that storage array 205 may include more than one storage controller in some embodiments.
Storage controller 210 may include software and/or hardware configured to provide access to storage devices 235A-N. Although storage controller 210 is shown as being separate from storage device groups 230 and 240, in some embodiments, storage controller 210 may be located within one or each of storage device groups 230 and 240. Storage controller 210 may include or be coupled to a base operating system (OS), a volume manager, and additional control logic for implementing the various techniques disclosed herein.
Storage controller 210 may include and/or execute on any number of processors and may include and/or execute on a single host computing device or be spread across multiple host computing devices, depending on the embodiment. In some embodiments, storage controller 210 may generally include or execute on one or more file servers and/or block servers. Storage controller 210 may use any of various techniques for replicating data across devices 235A-N to prevent loss of data due to the failure of a device or the failure of storage locations within a device. Storage controller 210 may also utilize any of various deduplication and/or compression techniques for reducing the amount of data stored in devices 235A-N.
Network 220 may utilize a variety of techniques including wireless connection, direct local area network (LAN) connections, wide area network (WAN) connections such as the Internet, a router, storage area network, Ethernet, and others. Network 220 may further include remote direct memory access (RDMA) hardware and/or software, transmission control protocol/internet protocol (TCP/IP) hardware and/or software, router, repeaters, switches, grids, and/or others. Protocols such as Fibre Channel, Fibre Channel over Ethernet (FCoE), iSCSI, and so forth may be used in network 220. The network 220 may interface with a set of communications protocols used for the Internet such as the Transmission Control Protocol (TCP) and the Internet Protocol (IP), or TCP/IP.
Client computer systems 215 and 225 are representative of any number of stationary or mobile computers such as desktop personal computers (PCs), servers, server farms, workstations, laptops, handheld computers, servers, personal digital assistants (PDAs), smart phones, and so forth. Generally speaking, client computer systems 215 and 225 include one or more processors comprising one or more processor cores. Each processor core includes circuitry for executing instructions according to a predefined general-purpose instruction set. For example, the x86 instruction set architecture may be selected. Alternatively, the ARM®, Alpha®, PowerPC®, SPARC®, or any other general-purpose instruction set architecture may be selected. The processor cores may access cache memory subsystems for data and computer program instructions. The cache subsystems may be coupled to a memory hierarchy comprising random access memory (RAM) and a storage device.
It is noted that in alternative embodiments, the number and type of storage arrays, client computers, storage controllers, networks, storage device groups, and data storage devices is not limited to those shown in
Referring now to
On the left side of the dashboard, recent alerts may be listed. In the center of the dashboard, the capacity of the storage system may be listed, with the provisioned storage listed as 74.00 terabytes (TB). The total reduction of data due to compression and deduplication is also listed in the capacity view as 9.3 to 1. The total reduction of data may vary depending on the type of data being stored and the amount of compression and deduplication that can be achieved. Also, the data reduction is listed as 3.5 to 1 in the capacity section of the GUI. Additionally, the amount of storage space currently being utilized by the storage system is shown to the right of the data reduction value, with the current utilization listed as “61% full”.
A horizontal graph showing the utilization of storage capacity may also be shown in the GUI. The capacity utilized for system data, shared space, volumes, snapshots, and empty space are shown in the GUI. In other embodiments, this information may be displayed using a bar graph, pie chart, a line graph, or any of various other types of charts.
The storage system GUI also displays timeline charts of latency, input/output operations per second (IOPS), and bandwidth. A tool at the bottom of the GUI allows the user to select the range of these timeline charts and to zoom in or out. In the top right of the GUI, the user may enter in the names of hosts or volumes to search for, with the GUI returning the corresponding results depending on the user's search query.
It should be understood that the local storage system GUI shown in
Turning now to
The advantages of the read-only GUI are that a user may monitor the status of a storage system without impacting the security of the storage system. For example, if the user is on an insecure network, the user may login to the cloud assist service without compromising the security of the storage system. Similarly, if the user is on a device which the user does not trust, the user can still access the read-only GUI to view the status of the storage system.
In one embodiment, all the configuration and performance data which is used to generate the local GUI at the storage system may be recorded and conveyed to the cloud assist service. Then this stored data may be utilized by the cloud assist service to create the read-only GUI. This allows a user to view the status of the storage system without having to connect directly to the storage system. There may be a slight lag in time where the read-only GUI is showing the state of the storage system as of the most recently received log data.
The read-only GUI will appear to the user to be the same as the local GUI, albeit with some slight differences. The main difference is that the user will not be able to make any changes to the storage system. For example, actions that the user is accustomed to being able to perform on the local GUI, such as creating a new host or deleting a volume, will be unavailable via the read-only GUI. However, the status information and performance data will be available and presented in the same manner on the read-only GUI as is presented on the local GUI.
Referring now to
The worker VMs 530 may retrieve Structured Query Language (SQL) logs from log storage 515 and apply the SQL logs to playback tables 535. Playback server 545 may be configured to load playback remote procedure calls (RPC) requests and query log storage 515 for the corresponding RPC responses. Playback server 545 may include GUI server 555 and fake RPC server 560. In one embodiment, GUI server 555 and fake RPC server 560 may be scripts or programs executing on the cloud assist service. It is noted that in other embodiments, other types of requests and responses, besides RPC requests and responses, may be utilized to query the state of the storage subsystems. For example, in another embodiment, representational state transfer (REST) requests and responses may be utilized rather than RPC requests and responses.
In one embodiment, a storage subsystem may be configured to record and phone home different types of log files. The first type of log file may be a full SQL database dump, which may be performed initially and then on a regularly scheduled basis. A second type of log file which may be utilized is an incremental SQL file, and these may be generated and conveyed to the cloud assist service on a more frequent basis than the full SQL database dump. These first two types of log files may include historical capacity and performance data. The storage subsystem may maintain multiple separate tables for performance data, capacity utilization, volume data, and other information, and when these tables are updated, corresponding log files may also be sent to the cloud assist service. These tables may be used to drive the historical graphs (for IOPS, bandwidth, latency, etc.) in the local GUI. The cloud assist service may also maintain corresponding tables for each storage subsystem, and the GUI server 555 may access these tables for generating the read-only GUI. A third type of log file which may be utilized is a listing of remote procedure call (RPC) requests and responses, which may be in a serialized python object (or pickle) format. In other embodiments, alternative types of formats may be utilized.
In one embodiment, each storage subsystem may execute a script which generates a plurality of RPC requests and records the corresponding responses generated by the storage subsystem. The script may use the same RPC requests that the local GUI makes in order to generate the different types of views and data shown in the local GUI. For each request made, a key may be stored and the response to the request may be recorded as the corresponding value. Once all of the RPC requests have been made and the responses recorded, the listing of key-value pairs may be sent to the cloud assist service. In one embodiment, the listing may identify volumes and hosts on the storage subsystem as well as additional information. These listings may be generated on a periodic basis (e.g., hourly, daily). In one embodiment, the listing may be stored as a serialized python object (or pickle) format file. In other embodiments, alternative types of formats may be utilized.
To perform GUI playback for a given storage subsystem, the SQL log files may be processed to update the tables corresponding to the given storage subsystem in playback tables 535. In some cases, preprocessing may be performed so that the logs may be processed more efficiently. In one embodiment, there may be one database created per storage subsystem. GUI server 555 may access the database to generate the historical capacity and performance data for the read-only GUI generated during GUI playback. GUI server 555 may also generate RPC requests for conveyance to the actual storage subsystem. However, instead of sending the RPC requests to the storage subsystem, the RPC requests may be redirected to fake RPC server 560. Fake RPC server 560 may be configured to accept requests from GUI server 555 and to lookup responses from the most recently recorded RPC request-response listing for the given storage subsystem. The fake RPC server 560 may also be referred to as a “subsystem simulator”. When GUIs are run in playback mode, an extra RPC argument with the storage subsystem identifier (ID) may be sent to the fake RPC server 560. The fake RPC server 560 may find the appropriate listing using the storage subsystem ID and may look up responses using the storage subsystem ID and a key, which may be the sorted request in JavaScript Object Notation (JSON).
The fake RPC server 560 may communicate with the GUI server 555 as if the fake RPC server 560 were the selected storage subsystem. In other words, when GUI server 555 receives a response from fake RPC server 560, GUI server 555 treats the response as if it came from the selected storage subsystem. Accordingly, the fake RPC server 560 responds as if it were the selected storage subsystem when receiving requests from the GUI server 555. When the fake RPC server 560 receives a RPC request from the GUI server 555, the fake RPC server 560 may look up the RPC request-response listing for the selected storage subsystem, find the key that corresponds to the received request, and return the value from the key-value pair in the listing. The GUI server 555 receives the response as if it came from the actual storage subsystem and then the GUI server 555 continues with additional requests or processes the responses to generate the read-only GUI.
For example, in one embodiment, a sample GUI RPC request may be the following: ‘volume.list({“user”:“api”}, “123-456-7890”)’. The fake RPC server 560 may look up the latest pickle file for the storage subsystem ID: “123-456-7890”. The fake RPC server 560 may load the pickle file and cache it. Then, the fake RPC server 560 may remove the “user” key from the request JSON and lookup and return the response for ‘volumelist({ })’. Another example of a RPC request is the following: ‘volumelist({“pending”:False. “space”:True, “total”:False})’. In playback mode, the GUI server 555 may be configured to keep track of one subsystem ID per session and use the ID to connect to the appropriate database in playback tables 535. The GUI server 555 may be configured to pass the subsystem ID when executing RPC requests. The GUI server 555 may also be configured to turn off all in-memory caching of state and run mostly stateless, disable editing controls, pretend that the current time is the last recorded time of the subsystem being viewed, and turn off polling for page refreshes.
In one embodiment, multiple GUI servers may be hosted by the cloud assist service, with each GUI server handling a range of storage subsystem GUI versions. Versions of every supported GUI server may be automatically downloaded and installed on instances with the playback role. When clicking on a GUI link, the launch script may pick the appropriate server to redirect to. In this way, the simulated playback GUI generated by the cloud assist service will match the local GUI generated by the storage subsystem.
For example, if a first storage array has version 3 of the GUI, and a second storage array has version 4 of the GUI, then the GUI server utilized in the cloud assist service for the first storage array will be version 3, and the GUI server utilized for the second storage array will be version 4. This prevents errors or other unintended consequences if mismatched GUI versions are paired up between the storage array and the cloud assist service. For example, version 4 of the GUI may show information that is not available (e.g., replication events) in version 3 of the GUI, and this information may be obtained from RPC responses to new RPC requests that were not included in version 3. If the first storage array uses a version 3 based script to generate the RPC request-response listing, this script will not generate the new RPC requests and will not have the corresponding responses. This listing will be stored with the cloud assist service, and if the cloud assist service were to use version 4 of the simulated playback GUI for the first storage array, then the simulated playback GUI would not be able to display the information about the replication events since this information was not captured by the script executing on the first storage array.
Turning now to
In one embodiment, log data 600 may include fields including a subsystem ID, host name, storage device count, host count, volume count, queue depth, read bandwidth (BW), read IOPS, read latency, write BW, write IOPS, write latency, and one or more other fields. In other embodiments, log data 600 may include other information and/or may be structured differently.
Log data 605 is another example of log data which may be generated by a storage system and conveyed to cloud assist logic. In one embodiment, log data 605 may be automatically generated on a scheduled basis and sent to the cloud assist logic. In other embodiments, log data 605 may be manually generated by a user or the user may determine when log data 605 is generated and conveyed to the cloud assist logic.
Log data 605 may include a code to identify which type of data it represents and a time stamp to identify when the data was generated. Log data 605 may also include latency data, IOPS, and bandwidth values that were captured during the most recent time period. Log data 605 may also include storage capacity utilization metrics, such as the amount of storage space utilized by system, shared space, volumes, and snapshots. In other embodiments, other storage capacity utilization metrics in addition to the above may be utilized. Log data 605 may also include one or more additional data fields.
Log data 610 is another type of log data which may be sent from a storage system to the cloud assist logic. In one embodiment, the storage system may alternate between sending log data 600, 605, and 610 to the cloud assist logic, with the code field or subsystem ID indicating which type of packet is being sent. Other types of log data not shown in
Log data 610 includes a code field followed by a transaction number of status ID field. Next, log data 610 may include a sequence number to indicate the most recently used sequence number. Alternatively, the sequence number field may specify a range of sequence numbers that were used over a recent period of time. Next, log data 610 may include a text descriptor field. The text descriptor field may be automatically generated text or this field may include comments inserted manually by an administrator or other user. Log data 610 may also include one or more additional data fields.
The size of log data 605 and 610 may vary depending on the embodiment. In one embodiment, the log data may have a fixed size. In another embodiment, the log data may have a variable size, with the size of the data indicated in one of the data fields. In other embodiments, the log data may have a variable size which is not specified within any of the data fields. It is noted that in other embodiments, other types of log data may be captured and sent from one or more storage systems to the cloud assist logic.
Referring now to
A first storage subsystem may generate and send log data to a cloud assist service (block 705). The log data may include diagnostics and performance data associated with various operating conditions of the first storage subsystem. In one embodiment, the first storage subsystem may be a storage array. In some embodiments, the first storage subsystem may be coupled to one or more other storage subsystems, and the first storage subsystem may convey log data from a plurality of storage subsystems to the cloud assist service. The cloud assist service may be configured to perform any combination of various functions for the first storage subsystem, such as storage and analysis of log data, generation of alerts, replication of data, generation of read-only GUIs, as well as other functions.
The first storage subsystem may also generate a local GUI for a locally connected user (block 710). In one embodiment, a GUI library may make RPC calls to the first storage subsystem to generate the GUI. The GUI may have a familiar interface to the user, with tabs and clickable buttons, and graphs, bars, charts indicating the current performance and status of the first storage subsystem. However, this local GUI may only be available to users directly connected to the first storage subsystem or to remote users who login to the network of the first storage subsystem.
The cloud assist service may receive the log data generated by the first storage subsystem (block 715). Then, the cloud assist service may generate a read-only GUI from the log data (block 720). The cloud assist service may generate the read-only GUI to utilize a substantially similar appearance to the local GUI so that a user will be familiar with the look and feel of the read-only GUI. The cloud assist service may allow authorized users to remotely access the read-only GUI (block 725). After block 725, method 700 may end.
Users may be able to login and view the read-only GUI to monitor the status of the first storage subsystem. A user will be able to switch views within the GUI by selecting different tabs and access menu items the same way as the user is accustomed to using as if the user were connected to the local GUI, with the exception that the user will be unable to make changes to the first storage subsystem. For example, in one embodiment, some of the actions the user may be accustomed to seeing and clicking on may be grayed out to indicate these actions cannot be performed using the read-only GUI. Also, there may be other minor differences between the local GUI and the read-only GUI.
Turning now to
A first storage subsystem may generate and send log files to the cloud assist logic on a periodic basis (block 805). The log files may include database files and request-response listings. In one embodiment, the database files may include historical capacity and performance data while the request-response listings may include information regarding the objects utilized by the first storage subsystem. The cloud assist logic may receive and store the log files generated by the first storage subsystem (block 810). In one embodiment, the cloud assist logic may maintain a database corresponding to the first storage subsystem, and the cloud assist logic may update the first storage subsystem's database using the received database files.
Next, the cloud assist logic may determine if it has received a request from an authorized user to login and access the read-only GUI of the first storage subsystem (conditional block 815). If no authorized users have requested access to the read-only GUI of the first storage subsystem (conditional block 815, “no” leg), then method 800 may return to block 805 with the first storage subsystem generating additional log files.
If an authorized user has requested access to the read-only GUI of the first storage subsystem (conditional block 815, “yes” leg), then the cloud assist logic may launch a GUI server for generating the read-only GUI (block 820). The GUI server may access the first storage subsystem's cloud-based database for the data (e.g., historical capacity, performance data) needed to generate the read-only GUI (block 825). The GUI server may also generate requests which may be conveyed to a subsystem simulator (block 830). In one embodiment, the requests may be RPC requests and the subsystem simulator may be a fake RPC server. The GUI server may generate requests with the intention of sending the requests to the first storage subsystem. However, a redirection layer may instead route the requests to the subsystem simulator.
Next, the subsystem simulator may look up the most recent request-response listing stored in the cloud for the first storage subsystem (block 835). Then, the subsystem simulator may generate corresponding responses from the listing as if the subsystem simulator were the first storage subsystem (block 840). Then, the GUI server may utilize the responses when generating the read-only GUI (block 845). At a later point in time, the cloud assist logic may terminate the read-only GUI session in response to detecting that the user has logged out (block 850). After block 850, method 800 may return to block 805 with the first storage subsystem generating additional logs.
Referring now to
An authorized user may remotely login to cloud assist logic (block 905). In response to the user logging in, the cloud assist logic may determine the version of the GUI which resides on the storage subsystem with which the user is associated (block 910). Different storage subsystems may have different versions of the GUI as the GUI evolves over time, and the user may be accustomed to using the specific version of the GUI they see when they are able to login to their storage subsystem.
After determining the version of the GUI which is running on the storage subsystem associated with the user, the cloud assist logic may initiate a GUI server of the same version as the user's storage subsystem (block 915). The GUI server may access the cloud-based database corresponding to the user's storage subsystem (block 920). Also, the GUI server may generate RPC requests and then receive the corresponding RPC responses from a fake RPC server (block 925). Then, the GUI server may generate a read-only GUI of the user's storage subsystem using the data from the corresponding database and RPC responses (block 930). After block 930, method 900 may end.
It is noted that the above-described embodiments may comprise software. In such an embodiment, the program instructions that implement the methods and/or mechanisms may be conveyed or stored on a non-transitory computer readable medium. Numerous types of media which are configured to store program instructions are available and include hard disks, floppy disks, CD-ROM, DVD, flash memory, Programmable ROMs (PROM), random access memory (RAM), and various other forms of volatile or non-volatile storage.
In various embodiments, one or more portions of the methods and mechanisms described herein may form part of a cloud-computing environment. In such embodiments, resources may be provided over the Internet as services according to one or more various models. Such models may include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). In IaaS, computer infrastructure is delivered as a service. In such a case, the computing equipment is generally owned and operated by the service provider. In the PaaS model, software tools and underlying equipment used by developers to develop software solutions may be provided as a service and hosted by the service provider. SaaS typically includes a service provider licensing software as a service on demand. The service provider may host the software, or may deploy the software to a customer for a given period of time. Numerous combinations of the above models are possible and are contemplated.
Although the embodiments above have been described in considerable detail, numerous variations and modifications will become apparent to those skilled in the art once the above disclosure is fully appreciated. It is intended that the following claims be interpreted to embrace all such variations and modifications.
Number | Name | Date | Kind |
---|---|---|---|
5208813 | Stallmo | May 1993 | A |
5403639 | Belsan et al. | Apr 1995 | A |
5940838 | Schmuck et al. | Aug 1999 | A |
6263350 | Wollrath et al. | Jul 2001 | B1 |
6412045 | DeKoning et al. | Jun 2002 | B1 |
6718448 | Ofer | Apr 2004 | B1 |
6757769 | Ofer | Jun 2004 | B1 |
6799283 | Tamai et al. | Sep 2004 | B1 |
6834298 | Singer et al. | Dec 2004 | B1 |
6850938 | Sadjadi | Feb 2005 | B1 |
6915434 | Kuroda et al. | Jul 2005 | B1 |
6973549 | Testardi | Dec 2005 | B1 |
7028216 | Aizawa et al. | Apr 2006 | B2 |
7028218 | Schwarm et al. | Apr 2006 | B2 |
7039827 | Meyer et al. | May 2006 | B2 |
7216164 | Whitmore et al. | May 2007 | B1 |
7292969 | Aharoni | Nov 2007 | B1 |
7783682 | Patterson | Aug 2010 | B1 |
7873619 | Faibish et al. | Jan 2011 | B1 |
7913300 | Flank et al. | Mar 2011 | B1 |
7933936 | Aggarwal et al. | Apr 2011 | B2 |
7975115 | Wayda et al. | Jul 2011 | B2 |
7979613 | Zohar et al. | Jul 2011 | B2 |
8086652 | Bisson et al. | Dec 2011 | B1 |
8117464 | Kogelnik | Feb 2012 | B1 |
8200887 | Bennett | Jun 2012 | B2 |
8205065 | Matze | Jun 2012 | B2 |
8352540 | Anglin et al. | Jan 2013 | B2 |
8504797 | Mimatsu | Aug 2013 | B2 |
8527544 | Colgrove et al. | Sep 2013 | B1 |
8560747 | Tan et al. | Oct 2013 | B1 |
8621241 | Stephenson | Dec 2013 | B1 |
8700875 | Barron et al. | Apr 2014 | B1 |
8751463 | Chamness | Jun 2014 | B1 |
8806160 | Colgrove et al. | Aug 2014 | B2 |
8822155 | Sukumar et al. | Sep 2014 | B2 |
8874850 | Goodson et al. | Oct 2014 | B1 |
8959305 | LeCrone et al. | Feb 2015 | B1 |
9081713 | Bennett | Jul 2015 | B1 |
9189334 | Bennett | Nov 2015 | B2 |
9280678 | Redberg | Mar 2016 | B2 |
9311182 | Bennett | Apr 2016 | B2 |
9395922 | Nishikido et al. | Jul 2016 | B2 |
9423967 | Colgrove et al. | Aug 2016 | B2 |
9436396 | Colgrove et al. | Sep 2016 | B2 |
9436720 | Colgrove et al. | Sep 2016 | B2 |
9454476 | Colgrove et al. | Sep 2016 | B2 |
9454477 | Colgrove et al. | Sep 2016 | B2 |
9513820 | Shalev | Dec 2016 | B1 |
9516016 | Colgrove et al. | Dec 2016 | B2 |
9552248 | Miller et al. | Jan 2017 | B2 |
9632870 | Bennett | Apr 2017 | B2 |
10164841 | Colgrove et al. | Dec 2018 | B2 |
10324639 | Seo | Jun 2019 | B2 |
10567406 | Astigarraga et al. | Feb 2020 | B2 |
10846137 | Vallala et al. | Nov 2020 | B2 |
10877683 | Wu et al. | Dec 2020 | B2 |
10999157 | Colgrove et al. | May 2021 | B1 |
11076509 | Alissa et al. | Jul 2021 | B2 |
11106810 | Natanzon et al. | Aug 2021 | B2 |
11194707 | Stalzer | Dec 2021 | B2 |
11444849 | Colgrove et al. | Sep 2022 | B2 |
20020038436 | Suzuki | Mar 2002 | A1 |
20020087544 | Selkirk et al. | Jul 2002 | A1 |
20020178335 | Selkirk et al. | Nov 2002 | A1 |
20030093619 | Sugino et al. | May 2003 | A1 |
20030140209 | Testardi | Jul 2003 | A1 |
20040049572 | Yamamoto et al. | Mar 2004 | A1 |
20050066095 | Mullick et al. | Mar 2005 | A1 |
20050216535 | Saika et al. | Sep 2005 | A1 |
20050223154 | Uemura | Oct 2005 | A1 |
20060074940 | Craft et al. | Apr 2006 | A1 |
20060136365 | Kedem et al. | Jun 2006 | A1 |
20060155946 | Ji | Jul 2006 | A1 |
20070067585 | Ueda et al. | Mar 2007 | A1 |
20070162954 | Pela | Jul 2007 | A1 |
20070171562 | Maejima et al. | Jul 2007 | A1 |
20070174673 | Kawaguchi et al. | Jul 2007 | A1 |
20070220313 | Katsuragi et al. | Sep 2007 | A1 |
20070245090 | King et al. | Oct 2007 | A1 |
20070266179 | Chavan et al. | Nov 2007 | A1 |
20080059699 | Kubo et al. | Mar 2008 | A1 |
20080065852 | Moore et al. | Mar 2008 | A1 |
20080134174 | Sheu et al. | Jun 2008 | A1 |
20080155191 | Anderson et al. | Jun 2008 | A1 |
20080178040 | Kobayashi | Jul 2008 | A1 |
20080209096 | Lin et al. | Aug 2008 | A1 |
20080244205 | Amano et al. | Oct 2008 | A1 |
20080256141 | Wayda et al. | Oct 2008 | A1 |
20080275928 | Shuster | Nov 2008 | A1 |
20080285083 | Aonuma | Nov 2008 | A1 |
20080307270 | Li | Dec 2008 | A1 |
20090006587 | Richter | Jan 2009 | A1 |
20090037662 | La Frese et al. | Feb 2009 | A1 |
20090204858 | Kawaba | Aug 2009 | A1 |
20090228648 | Wack | Sep 2009 | A1 |
20090300084 | Whitehouse | Dec 2009 | A1 |
20100057673 | Savov | Mar 2010 | A1 |
20100058026 | Heil et al. | Mar 2010 | A1 |
20100067706 | Anan et al. | Mar 2010 | A1 |
20100077205 | Ekstrom et al. | Mar 2010 | A1 |
20100082879 | McKean et al. | Apr 2010 | A1 |
20100106905 | Kurashige et al. | Apr 2010 | A1 |
20100153620 | McKean et al. | Jun 2010 | A1 |
20100153641 | Jagadish et al. | Jun 2010 | A1 |
20100191897 | Zhang et al. | Jul 2010 | A1 |
20100250802 | Waugh et al. | Sep 2010 | A1 |
20100250882 | Hutchison et al. | Sep 2010 | A1 |
20100281225 | Chen et al. | Nov 2010 | A1 |
20100287327 | Li et al. | Nov 2010 | A1 |
20100306500 | Mimatsu | Dec 2010 | A1 |
20110035540 | Fitzgerald et al. | Feb 2011 | A1 |
20110072300 | Rousseau | Mar 2011 | A1 |
20110145598 | Smith et al. | Jun 2011 | A1 |
20110161559 | Yurzola et al. | Jun 2011 | A1 |
20110167221 | Pangal et al. | Jul 2011 | A1 |
20110238634 | Kobara | Sep 2011 | A1 |
20120023375 | Dutta et al. | Jan 2012 | A1 |
20120036309 | Dillow et al. | Feb 2012 | A1 |
20120117029 | Gold | May 2012 | A1 |
20120198175 | Atkisson | Aug 2012 | A1 |
20120330954 | Sivasubramanian et al. | Dec 2012 | A1 |
20130042052 | Colgrove et al. | Feb 2013 | A1 |
20130046995 | Movshovitz | Feb 2013 | A1 |
20130047029 | Ikeuchi et al. | Feb 2013 | A1 |
20130091102 | Nayak | Apr 2013 | A1 |
20130179461 | Sharma | Jul 2013 | A1 |
20130205110 | Kettner | Aug 2013 | A1 |
20130227236 | Flynn et al. | Aug 2013 | A1 |
20130275391 | Batwara et al. | Oct 2013 | A1 |
20130275656 | Talagala et al. | Oct 2013 | A1 |
20130283058 | Fiske et al. | Oct 2013 | A1 |
20130290648 | Shao et al. | Oct 2013 | A1 |
20130318314 | Markus et al. | Nov 2013 | A1 |
20130339303 | Potter et al. | Dec 2013 | A1 |
20140052946 | Kimmel | Feb 2014 | A1 |
20140068791 | Resch | Mar 2014 | A1 |
20140089730 | Watanabe et al. | Mar 2014 | A1 |
20140101361 | Gschwind | Apr 2014 | A1 |
20140143517 | Jin et al. | May 2014 | A1 |
20140172929 | Sedayao et al. | Jun 2014 | A1 |
20140201150 | Kumarasamy et al. | Jul 2014 | A1 |
20140215129 | Kuzmin et al. | Jul 2014 | A1 |
20140220561 | Sukumar et al. | Aug 2014 | A1 |
20140229131 | Cohen et al. | Aug 2014 | A1 |
20140229452 | Serita et al. | Aug 2014 | A1 |
20140281308 | Lango et al. | Sep 2014 | A1 |
20140325115 | Ramsundar et al. | Oct 2014 | A1 |
20150019620 | Gidron et al. | Jan 2015 | A1 |
20150154418 | Redberg | Jun 2015 | A1 |
20150234709 | Koarashi | Aug 2015 | A1 |
20150244775 | Vibhor et al. | Aug 2015 | A1 |
20150278534 | Thiyagarajan et al. | Oct 2015 | A1 |
20160019114 | Han et al. | Jan 2016 | A1 |
20160026397 | Nishikido et al. | Jan 2016 | A1 |
20160098191 | Golden et al. | Apr 2016 | A1 |
20160098199 | Golden et al. | Apr 2016 | A1 |
20160099844 | Colgrove et al. | Apr 2016 | A1 |
20160182542 | Staniford | Jun 2016 | A1 |
20160248631 | Duchesneau | Aug 2016 | A1 |
20170262202 | Seo | Sep 2017 | A1 |
20180054454 | Astigarraga et al. | Feb 2018 | A1 |
20180081562 | Vasudevan | Mar 2018 | A1 |
20190220315 | Vallala et al. | Jul 2019 | A1 |
20200034560 | Natanzon et al. | Jan 2020 | A1 |
20200326871 | Wu et al. | Oct 2020 | A1 |
20210250248 | Colgrove et al. | Aug 2021 | A1 |
20210360833 | Alissa et al. | Nov 2021 | A1 |
Number | Date | Country |
---|---|---|
103370685 | Oct 2013 | CN |
103370686 | Oct 2013 | CN |
104025010 | Nov 2016 | CN |
3066610 | Sep 2016 | EP |
3082047 | Oct 2016 | EP |
3120235 | Jan 2017 | EP |
2007087036 | Apr 2007 | JP |
2007094472 | Apr 2007 | JP |
2008250667 | Oct 2008 | JP |
2010211681 | Sep 2010 | JP |
1995002349 | Jan 1995 | WO |
1999013403 | Mar 1999 | WO |
2008102347 | Aug 2008 | WO |
2010071655 | Jun 2010 | WO |
2016053887 | Apr 2016 | WO |
Entry |
---|
Hwang et al., “RAID-x: A New Distributed Disk Array for I/O-Centric Cluster Computing”, Proceedings of The Ninth International Symposium On High-performance Distributed Computing, Aug. 2000, pp. 279-286, The Ninth International Symposium on High-Performance Distributed Computing, IEEE Computer Society, Los Alamitos, CA. |
International Search Report and Written Opinion, PCT/US2015/052689, dated Jan. 25, 2016, 11 pages. |
Microsoft Corporation, “Fundamentals of Garbage Collection”, Retrieved Aug. 30, 2013 via the WayBack Machine, 11 pages. |
Microsoft Corporation, “GCSettings.IsServerGC Property”, Retrieved Oct. 27, 2013 via the WayBack Machine, 3 pages. |
Stalzer, “FlashBlades: System Architecture and Applications”, Proceedings of the 2nd Workshop on Architectures and Systems for Big Data, Jun. 2012, pp. 10-14, Association for Computing Machinery, New York, NY. |
Storer et al., “Pergamum: Replacing Tape with Energy Efficient, Reliable, Disk-Based Archival Storage”, FAST'08: Proceedings of the 6th USENIX Conference on File and Storage Technologies, Article No. 1, Feb. 2008, pp. 1-16, USENIX Association, Berkeley, CA. |
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20230006894 A1 | Jan 2023 | US |
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Parent | 14504945 | Oct 2014 | US |
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