Patent Application
20250240202
The present disclosure relates to networking. More particularly, the present disclosure relates to facilitating a disaster recovery between various network devices monitored by a workload protection solution.
Software applications have become critically important for organizations worldwide, serving as the lifeblood of their operations. Applications not only drive revenue but also engage customers, facilitate business outcomes, and differentiate organizations from their competitors. Developers, as the creators of these applications, play a central role in business transformation and are valued customers of enterprise IT. IT operators, including networking professionals, provide business value by supporting applications with agility and efficiency.
Developers are deploying applications in multiple public and private clouds, often alongside legacy applications in various data centers. The rise of microservices is also contributing to the development of highly distributed application environments, with application tiers and data services spread across data centers and public clouds. However, outdated protocols and tools have failed to keep up with these dynamic application environments, leading to challenges in monitoring and ensuring application availability and performance.
Addressing these challenges can lead to better network performance and reliability. In response, workload protection solutions offer machine learning capabilities that provide actionable insights into network performance. They can enhance network visibility, supports mission-critical applications in both on-premises data centers and the public cloud, and offers comprehensive traffic telemetry information. The platform performs advanced analytics and tracks network topology, making it easier for operations teams to manage and optimize network performance for digital business and cloud infrastructures. Such a holistic approach to protect data centers and workloads across multiple cloud environments can be achieved, in part, by implementing segmentation, zero-trust models, and automated compliance enforcement.
However, as segmentation becomes more important to network administrators, so too does the availability of data sets that are utilized for enforcing policy. The policy that is enforced is one part of an overall challenge and can be exasperated during an actual disaster. This creates a challenge with managing the data related to segmentation related to the sources of telemetry that also need to accompany the policy. The workload protection solutions are often required to understand and define any changes in scope, label context, and/or other configuration aspects, even in the event of a disaster. As such, handling disasters in workload protection solutions can be critical.
Systems and methods for automatically identifying and classifying network traffic to generate a recommended policy in accordance with embodiments of the disclosure are described herein. In some embodiments, a device includes a processor, at least one network interface controller configured to provide access to a network, and a memory communicatively coupled to the processor, wherein the memory includes a workload protection logic. The logic is configured to receive a disaster recovery request, create a plurality of keys, replicate one or more configuration components, and execute a disaster recovery process.
In some embodiments, the disaster recovery request is received in response to a disaster event.
In some embodiments, the disaster recovery request is received in response to a time-based event.
In some embodiments, the plurality of keys are application programming interface keys.
In some embodiments, the network includes a plurality of network devices.
In some embodiments, the plurality of network devices are configured with security certificates.
In some embodiments, the security certificates are identical across the plurality of network devices.
In some embodiments, the replication of the one or more configuration components includes at least querying a source network device for one or more configurations, copying the one or more configurations, replicating the one or more configurations to a target network device.
In some embodiments, executing the disaster recovery process includes at least determining a plurality of configurations to replicate, selecting one or more target network devices, and replicating the plurality of configurations to the one or more target network devices.
In some embodiments, the replication of at least two of the one or more configuration components are done in parallel.
In some embodiments, the configuration components include at least one of user defined labels, scopes, inventory filters, agent profiles, agent intents, workspaces, workspace policies, or workspace clusters.
In some embodiments, the configuration components include at least one of user roles, user accounts, exclusion filters, external orchestrators, client server configurations, forensics profiles and intents, policy templates, collection rules, default application dependency mapping configuration, alert configurations, or connectors.
In some embodiments, the workload protection logic is further configured to determine a recovery interval.
In some embodiments, the recovery interval is dynamically determined.
In some embodiments, the dynamic determination is based on an event.
In some embodiments, the event is one of receiving a warning notification, receiving a command to change the recovery interval, or determining that one or more connection problems are present.
In some embodiments, a device includes a processor, at least one network interface controller configured to provide access to a network, and a memory communicatively coupled to the processor, wherein the memory includes a workload protection logic. The logic is configured to establish a connection with a plurality of network devices on the network, configure identical security certificates on each of the plurality of network devices, receive a disaster recovery request, determine at least one target network device, select a source network device from the plurality of network devices, replicate one or more configuration components from the source network device, and apply the one or more configuration components to the target network device.
In some embodiments, the disaster recovery request is received in response to an event.
In some embodiments, the event is one of receiving a warning notification, receiving a command to change the recovery interval, or determining that one or more connection problems are present.
In some embodiments, a method generates an application dependency mapping, including configure identical security certificates on a plurality of network devices, receive a disaster recovery request, determine at least one target network device, select a source network device from the plurality of network devices, replicate one or more configuration components from the source network device, and apply the one or more configuration components to the target network device.
Other objects, advantages, novel features, and further scope of applicability of the present disclosure will be set forth in part in the detailed description to follow, and in part will become apparent to those skilled in the art upon examination of the following or may be learned by practice of the disclosure. Although the description above contains many specificities, these should not be construed as limiting the scope of the disclosure but as merely providing illustrations of some of the presently preferred embodiments of the disclosure. As such, various other embodiments are possible within its scope. Accordingly, the scope of the disclosure should be determined not by the embodiments illustrated, but by the appended claims and their equivalents.
The above, and other, aspects, features, and advantages of several embodiments of the present disclosure will be more apparent from the following description as presented in conjunction with the following several figures of the drawings.
Corresponding reference characters indicate corresponding components throughout the several figures of the drawings. Elements in the several figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures might be emphasized relative to other elements for facilitating understanding of the various presently disclosed embodiments. In addition, common, but well-understood, elements that are useful or necessary in a commercially feasible embodiment are often not depicted in order to facilitate a less obstructed view of these various embodiments of the present disclosure.
In response to the issues described above, devices and methods are discussed herein that can facilitate disaster recoveries in workload protection solutions. Generally, this can occur by provided a means of allowing agents to access various network devices with a common security certificate. Target network devices can have one or more configurations applied to them from a source network device. The source network device can have a set of keys provided that allow accessing the various configurations. In response to a disaster event, the configurations can be applied to the affected target network devices. The replication of these network devices can occur in response to that disaster event or may be replication at an interval or upon user prompt such as a disaster recovery request, detection of a warning or network connection, etc.
Embodiments described herein can be part of a multi-faceted solution that involves replication the security certificates from one environment to another. This can ensure that data collection continues as desired during a disaster. Replication can occur for the required configuration aspects of the implementation along with the desired policy. The initial deployment of the desired environment can require deploying multiple network devices with the same security identification (certificates) to allow agent mobility for disaster recovery testing and actual events. Following steps can be for the replication of the configuration or policy data required for a consistent policy model. This can be accomplished by utilizing a workload protection solution API to query the source network device and replicating the data to the target network device.
As described in more detail below, the keys may be API keys that can allow access to various configurations which may include, but are not limited to user defined labels, scopes, inventory filters, agent profiles, agent intents, workspaces, workspace policies, workspace clusters, user roles, user accounts, exclusion filters, external orchestrators, client server configurations (i.e., server ports), forensics profiles/intents, policy templates, collection rules, default application dependency mapping configurations, alert configurations, and/or connectors. A workload protection logic can query a source network device for one or more of these configurations, copy them, and replicate them to various network devices. The order of replication of these configurations often does not matter.
In many embodiments, the workload protection logic can execute a disaster recovery process by determining a plurality of configurations to replicate, selecting one or more target devices, and replicating the determined plurality of configurations to the one or more target devices. However, in certain embodiments, the determination of the plurality of configurations may not occur until after the one or more target devices are selected. In this way, each target device may have different configurations which are relevant for replicating from source network device to target network devices. In some embodiments, the target network device may receive configurations from two or more source network devices.
This replication process can often be done in parallel between a plurality of different network devices. As those skilled in the art will recognize, this can vary depending on the type of disaster that has occurred. In order to facilitate this process, the replication of configurations can be done at a pre-determined time interval in order to prepare for a future disaster. In more embodiments, the replication or recovery interval can dynamically vary in response to a determined event such as a one or more connection issues or warning signals. This recovery interval can change in response to receiving a command or the like. Those skilled in the art will recognize that the replication interval can vary depending on the optimal arrangement. By way of non-limiting example, a replication interval can be set up for once a day until a warning error or connection issue is determined which can trigger a dynamic change in the replication interval to once every five minutes.
In many embodiments, a workload protection solution offers a holistic approach to protect data centers across multiple cloud environments by implementing a zero-trust model through segmentation. This approach helps in faster detection of security incidents, containment of lateral movement, and reduction of the attack surface. Workload protection solutions are often infrastructure-agnostic and support on-premises as well as public cloud workloads. These solutions can provide capabilities like automated “allow list” policy generation based on real-time telemetry data, enforcing a zero-trust model, identifying process behavior deviations, and detecting software vulnerabilities. These workload protection solutions can be deployed in numerous way including, but not limited to, appliance-based, virtual, and Software as a Service (“SaaS”) deployment solutions.
In the context of various network infrastructures, a “workload” typically refers to a unit of work or a specific set of tasks that a computing system, server, or other network device is responsible for executing. In some environments, the term “workload” may be hosts that have a Secure Workload Agent (“SWA”) installed while hosts that do not have a SWA installed on them can be considered “IP addresses”.
Workloads can vary widely and encompass various types of applications and services, including application workloads like web applications and databases, virtualization workloads represented by virtual machines or containers in virtualized environments, data workloads related to data processing and storage tasks, network workloads associated with network services and data transmission, security workloads for services like firewalls and encryption, and storage workloads concerning data storage and management. Workload protection solutions can secure these various workloads in data centers, cloud environments, and network infrastructures. Understanding and efficiently securing various workloads is often considered essential for optimizing resource utilization and ensuring the performance, and reliability of IT systems.
In networking, “segmentation” often refers to the strategic practice of dividing a network into smaller, isolated segments or subnetworks. Workload protection solutions can utilize segmentation to achieve several critical objectives. Firstly, it bolsters network security by isolating different segments from one another, safeguarding against the potential fallout of a security breach in one segment from affecting the entire network. These segmentation solutions can enforce security policies and regulate traffic flow between segments to prevent unauthorized access and data breaches.
Secondly, segmentation can often simplify network management. By breaking down a large network into more manageable parts, administrators can apply specific policies, monitor network traffic, and troubleshoot issues more effectively within each isolated segment. Additionally, network performance can benefit from segmentation as it reduces congestion and contention for network resources, ultimately enhancing the performance of critical applications and services. Workload protection solutions can be configured to implement network segmentation and micro-segmentation. These tools empower organizations to create, manage, and maintain network segments efficiently, contributing to a more secure, manageable, and streamlined network infrastructure.
Also, in the realm of networking, “zero-trust” typically represents a security paradigm that fundamentally challenges the traditional notion of trust within network environments. This model can operate on the premise that no entity, whether situated inside or outside the network, should be automatically trusted. Instead, it mandates stringent access controls and continuous validation procedures. Entities, including users, devices, and applications, are required to authenticate their identity and demonstrate their security posture before being granted access to network resources. This approach aims to fortify network security by eliminating assumptions of trust and significantly reducing the risk of unauthorized access or breaches.
Zero trust principles encompass several key tenets. Firstly, identity verification is a prerequisite for access, necessitating robust authentication methods like multi-factor authentication (“MFA”). Secondly, access rights are strictly governed by the principle of least privilege, limiting permissions to the bare minimum essential for entities to perform their designated functions. Micro-segmentation can be employed to isolate and secure network segments, ensuring rigorous controls on traffic flow and minimizing the potential attack surface. Continuous monitoring of network traffic and entity behavior is paramount to promptly detect and respond to anomalies or security threats.
Lastly, encryption is often widely adopted to safeguard data, whether in transit or at rest. This comprehensive zero trust model can address the evolving threat landscape, acknowledging the presence of potential threats both within and outside the network. It is designed to enhance data and resource security, regardless of their location, in recognition that traditional perimeter-based security approaches are no longer adequate in today's complex and dynamic network environments. Workload protection solutions can be configured to provide solutions to implement a zero-trust security model effectively.
Scopes serve as a fundamental component in configuring and establishing policies within a workload protection solution. Scopes can be considered as collections of workloads organized in a hierarchical structure. Workloads can be labeled with attributes that provide insights into their location, role, and/or function in the environment. Often, the purpose of scopes is to offer a framework for dynamic mechanisms, particularly in terms of identification and attributes associated with changing IP addresses.
Scopes may also be primarily utilized for grouping datacenter applications and, when combined with roles, they enable precise control over the management of these applications. For instance, scopes play a pivotal role in defining access to policies, flows, and filters throughout the product. These scopes can be structured hierarchically, forming sets of trees with the root representing, for example, a Virtual Routing and Forwarding (VRF). Each scope tree hierarchy can represent distinct data that does not overlap with others. When defining individual scopes, key attributes can include the parent scope, name (for identification), type (for specifying different categories of inventory), and a query (that can define the individual scope). Often, it may be desired to organize one or more scopes hierarchically to mirror the application ownership hierarchy within the organization.
These scopes are often instrumental in constructing a hierarchical map of your network, which can be referred to as a “scope tree.” This hierarchical representation is essential for efficiently establishing and maintaining network policies. For example, utilizing a scope tree can enable the creation of a policy that can be automatically applied to every workload within a specific branch of that tree. Additionally, a scope tree can facilitate the delegation of responsibility for managing certain applications or network segments to individuals with the necessary expertise to define the appropriate policies for those workloads.
Labels can play a crucial role in defining logical policies within a managed network. By way of non-limiting example, labels can be configured to enable the creation of policies like “allow traffic from “consumer network applications” to “provider database”.” Rather than specifying the exact members of the consumer and provider workload groups, these logical policies can be formulated using labels, providing flexibility in dynamically modifying the membership of these groups without altering the policy. Workload protection solutions can receive notifications from configured services, such as external orchestrators and cloud connectors, when workloads are added or removed. This may allow the workload protection solution to continually assess the composition of groups like “consumer network applications” and “provider database” to ensure accurate policy enforcement. Additionally, subnet-based label inheritance is supported, which can allow smaller subnets and IP addresses to inherit labels from larger subnets they belong to. This inheritance can occur when labels are either missing from the smaller subnet/address or when the label value for the smaller subnet/address is empty, enhancing the efficiency and consistency of label management.
As those skilled in the art will recognize, a software agent or “agent” typically refers to a specialized and autonomous program or script that is designed to perform tasks or make decisions on behalf of a user, system, or organization. These agents can range from simple to highly complex and are often used to automate tasks, gather, and analyze data, and/or interact with other software systems and users. They can act on predefined rules and logic or adapt and learn from their environment. Software agents are used in various applications, including network management, artificial intelligence, data mining, and automation of routine tasks. They can be configured to allow software components to act independently or collaboratively to achieve specific goals.
Aspects of the present disclosure may be embodied as an apparatus, system, method, or computer program product. Accordingly, aspects of the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, or the like) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “function,” “module,” “apparatus,” or “system.” Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more non-transitory computer-readable storage media storing computer-readable and/or executable program code. Many of the functional units described in this specification have been labeled as functions, in order to emphasize their implementation independence more particularly. For example, a function may be implemented as a hardware circuit comprising custom VLSI circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. A function may also be implemented in programmable hardware devices such as via field programmable gate arrays, programmable array logic, programmable logic devices, or the like.
Functions may also be implemented at least partially in software for execution by various types of processors. An identified function of executable code may, for instance, comprise one or more physical or logical blocks of computer instructions that may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables of an identified function need not be physically located together but may comprise disparate instructions stored in different locations which, when joined logically together, comprise the function and achieve the stated purpose for the function.
Indeed, a function of executable code may include a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, across several storage devices, or the like. Where a function or portions of a function are implemented in software, the software portions may be stored on one or more computer-readable and/or executable storage media. Any combination of one or more computer-readable storage media may be utilized. A computer-readable storage medium may include, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing, but would not include propagating signals. In the context of this document, a computer readable and/or executable storage medium may be any tangible and/or non-transitory medium that may contain or store a program for use by or in connection with an instruction execution system, apparatus, processor, or device.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object-oriented programming language such as Python, Java, Smalltalk, C++, C#, Objective C, or the like, conventional procedural programming languages, such as the “C” programming language, scripting programming languages, and/or other similar programming languages. The program code may execute partly or entirely on one or more of a user's computer and/or on a remote computer or server over a data network or the like.
A component, as used herein, comprises a tangible, physical, non-transitory device. For example, a component may be implemented as a hardware logic circuit comprising custom VLSI circuits, gate arrays, or other integrated circuits; off-the-shelf semiconductors such as logic chips, transistors, or other discrete devices; and/or other mechanical or electrical devices. A component may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices, or the like. A component may comprise one or more silicon integrated circuit devices (e.g., chips, die, die planes, packages) or other discrete electrical devices, in electrical communication with one or more other components through electrical lines of a printed circuit board (PCB) or the like. Each of the functions and/or modules described herein, in certain embodiments, may alternatively be embodied by or implemented as a component.
A circuit, as used herein, comprises a set of one or more electrical and/or electronic components providing one or more pathways for electrical current. In certain embodiments, a circuit may include a return pathway for electrical current, so that the circuit is a closed loop. In another embodiment, however, a set of components that does not include a return pathway for electrical current may be referred to as a circuit (e.g., an open loop). For example, an integrated circuit may be referred to as a circuit regardless of whether the integrated circuit is coupled to ground (as a return pathway for electrical current) or not. In various embodiments, a circuit may include a portion of an integrated circuit, an integrated circuit, a set of integrated circuits, a set of non-integrated electrical and/or electrical components with or without integrated circuit devices, or the like. In one embodiment, a circuit may include custom VLSI circuits, gate arrays, logic circuits, or other integrated circuits; off-the-shelf semiconductors such as logic chips, transistors, or other discrete devices; and/or other mechanical or electrical devices. A circuit may also be implemented as a synthesized circuit in a programmable hardware device such as field programmable gate array, programmable array logic, programmable logic device, or the like (e.g., as firmware, a netlist, or the like). A circuit may comprise one or more silicon integrated circuit devices (e.g., chips, die, die planes, packages) or other discrete electrical devices, in electrical communication with one or more other components through electrical lines of a printed circuit board (PCB) or the like. Each of the functions and/or modules described herein, in certain embodiments, may be embodied by or implemented as a circuit.
Reference throughout this specification to “one embodiment,” “an embodiment,” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, appearances of the phrases “in one embodiment,” “in an embodiment,” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment, but mean “one or more but not all embodiments” unless expressly specified otherwise. The terms “including,” “comprising,” “having,” and variations thereof mean “including but not limited to”, unless expressly specified otherwise. An enumerated listing of items does not imply that any or all of the items are mutually exclusive and/or mutually inclusive, unless expressly specified otherwise. The terms “a,” “an,” and “the” also refer to “one or more” unless expressly specified otherwise.
Further, as used herein, reference to reading, writing, storing, buffering, and/or transferring data can include the entirety of the data, a portion of the data, a set of the data, and/or a subset of the data. Likewise, reference to reading, writing, storing, buffering, and/or transferring non-host data can include the entirety of the non-host data, a portion of the non-host data, a set of the non-host data, and/or a subset of the non-host data.
Lastly, the terms “or” and “and/or” as used herein are to be interpreted as inclusive or meaning any one or any combination. Therefore, “A, B or C” or “A, B and/or C” mean “any of the following: A; B; C; A and B; A and C; B and C; A, B and C.” An exception to this definition will occur only when a combination of elements, functions, steps, or acts are in some way inherently mutually exclusive.
Aspects of the present disclosure are described below with reference to schematic flowchart diagrams and/or schematic block diagrams of methods, apparatuses, systems, and computer program products according to embodiments of the disclosure. It will be understood that each block of the schematic flowchart diagrams and/or schematic block diagrams, and combinations of blocks in the schematic flowchart diagrams and/or schematic block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a computer or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor or other programmable data processing apparatus, create means for implementing the functions and/or acts specified in the schematic flowchart diagrams and/or schematic block diagrams block or blocks.
It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. Other steps and methods may be conceived that are equivalent in function, logic, or effect to one or more blocks, or portions thereof, of the illustrated figures. Although various arrow types and line types may be employed in the flowchart and/or block diagrams, they are understood not to limit the scope of the corresponding embodiments. For instance, an arrow may indicate a waiting or monitoring period of unspecified duration between enumerated steps of the depicted embodiment.
In the following detailed description, reference is made to the accompanying drawings, which form a part thereof. The foregoing summary is illustrative only and is not intended to be in any way limiting. In addition to the illustrative aspects, embodiments, and features described above, further aspects, embodiments, and features will become apparent by reference to the drawings and the following detailed description. The description of elements in each figure may refer to elements of proceeding figures. Like numbers may refer to like elements in the figures, including alternate embodiments of like elements.
Referring to
In many embodiments, the network 100 may comprise a plurality of devices that are configured to transmit and receive data for a plurality of clients. In various embodiments, cloud-based centralized management servers 80 are connected to a wide-area network such as, for example, the Internet 80. In further embodiments, cloud-based centralized management servers 80 can be configured with or otherwise operate a workload protection logic. The workload protection logic can be provided as a cloud-based service that can service remote networks, such as, but not limited to the deployed network 140. In these embodiments, the workload protection logic can be a logic that receives data from the deployed network 140 and generates predictions, receives environmental sensor signal data, and perhaps automates certain decisions or protective actions associated with the network devices. In certain embodiments, the workload protection logic can generate historical and/or algorithmic data in various embodiments and transmit that back to one or more network devices within the deployed network 140.
However, in additional embodiments, the workload protection logic may be operated as distributed logic across multiple network devices. In the embodiment depicted in
In still further embodiments, the workload protection logic may be integrated within another network device. In the embodiment depicted in
Although a specific embodiment for a conceptual network diagram of a various environments that a workload protection logic operating on a plurality of network devices suitable for carrying out the various steps, processes, methods, and operations described herein is discussed with respect to
Referring to
In many embodiments, the network 200 can have a tenant or root scope 210 that encompasses all other segments. Within the root scope 210, an internal scope 220 and various external scopes can be segmented. In the embodiment depicted in
In a number of embodiments, the internal scope 220 can include a number of segments. In the embodiment depicted in
In some embodiments, the infrastructure services can include a plurality of segments. The embodiment depicted in
Similarly, in various embodiments, the cloud services segment 270 can include a plurality of various third-party cloud services 271. Those skilled in the art will recognize that different cloud-based services can be incorporated based on the specific need. Likewise, additional embodiments may include a production segment 280 comprising a web segment 281, an app segment 282, and a database segment 283 (shown “DB”). In still more embodiments, a common/shared services segment 290 may comprise a shared databases segment 291, a SAN segment 292, and an ISCSI segment 293. Each of these segments can provide an additional layer of security and overall workload protection within a network.
Although a specific embodiment for a conceptual illustration of a segmentation model within a workload protection system suitable for carrying out the various steps, processes, methods, and operations described herein is discussed with respect to
Referring to
In the organization scope level 320, the embodiment depicted in
In further embodiments, an environment scope level 340 can be associated with a plurality of segments. In the embodiment depicted in
In more embodiments, the application scope level 350 can be associated with segments that are children of segments within the environment scope level 340. In the embodiment depicted in
Although a specific embodiment for a conceptual hierarchal scope design within a workload protection system suitable for carrying out the various steps, processes, methods, and operations described herein is discussed with respect to
Referring to
In various embodiments, a data center segment 460 can include a plurality of data center segments. In the embodiment depicted in
In more embodiments, the topology 400 can include an application segment 490 that can include various sub-segments. In the embodiment depicted in
Each of these segments, as shown in the topology 400 can allow for unique policy applications that can keep the overall network more secure. As those skilled in the art will recognize, the embodiments depicted in
Although a specific embodiment for a conceptual illustration of a network topology operating with a workload protection system suitable for carrying out the various steps, processes, methods, and operations described herein is discussed with respect to
Referring to
In a number of embodiments, the process 500 can create one or more keys (block 520). Often, these keys can be a plurality of application programming interface (API) keys. In some embodiments, there will be a number of network devices within the network subject to the disaster recovery, and each of these network devices can be configured with a plurality of API keys. These keys can often be configured to allow access to various data or configurations that can be utilized in the disaster recovery.
In additional embodiments, the process 500 can replicate configuration components (block 530). A network device can comprise a variety of different configurations that may need to be replicated in the event of a disaster. As discussed in more detail below, the process 500 may select a number of target devices and source devices. The configurations of a source network device may be replicated to target network devices. However, in embodiments where the disaster recovery is being established, the process 500 may simply select which components are to be replicated in the event of a future disaster based on each source and/or target network device.
In more embodiments, the process 500 can define a replication interval (block 540). As those skilled in the art will recognize, replication can be achieved at various rates. In some embodiments, replication of network devices can happen in parallel while other embodiments can operate replication in a serial fashion. In still more embodiments, the process 500 can determine a specific interval on which replication shall be repeated between network devices both as a preventative measure against disasters, but also as a method to have an up-to-date copy of various configurations.
In various embodiments, the process 500 can execute the disaster recovery (block 550). In embodiments described herein, the process 500 can be considered a setup to a future disaster recovery wherein the received disaster recovery request is a request to establish an environment where a future disaster recovery can be performed. In certain embodiments, the execution of a disaster recovery can be in response to a specific event, notification, or manual execution. For example, the replication interval may expire which triggers a disaster recovery process. In some embodiments, the workload protection solution may receive a notification about a network connection issue that can trigger a preemptive disaster recovery, etc.
Although a specific embodiment for a process 500 for executing a disaster recovery suitable for carrying out the various steps, processes, methods, and operations described herein is discussed with respect to
Referring to
In a number of embodiments, the process 600 can deploy the plurality of network devices (block 620). In some embodiments, the configuration of the network devices can be done by the manufacturer prior to deployment out into the field. However, certain embodiments may “deploy” the network devices that are already in the field with the workload protection solution and the associated agents, etc.
In various embodiments, the process 600 can determine a target network device (block 630). A target network device can often be considered a network device that is configured to receive one or more configurations from a source network device. In some embodiments, the target network device can be a network device that has been affected by a disaster. The workload protection solution can be configured to determine one or more target network devices in response to a variety of different disasters. This determination can be done in response to a disaster-related event, or can be selected as a part of a routine disaster recovery update process.
In additional embodiments, the process 600 can select a source network device (block 640). Based on the type of target network device that has been selected, embodiments described herein can select a similar or other compatible source network device. This selection can be done in response to a determination that the target and source device share one or more characteristics, traits, and/or other configurations.
In further embodiments, the process 600 can retrieve configuration data from the source network device (block 650). As described above, various embodiments may utilize one or more API keys that are assigned to the source network device to query or otherwise obtain various configurations within the source network device. These characteristics can include, but are not limited to, user defined labels, scopes, inventory filters, agent profiles, agent intents, workspaces, workspace policies, workspace clusters, user roles, user accounts, exclusion filters, external orchestrators, client server configurations (i.e., server ports), forensics profiles/intents, policy templates, collection rules, default application dependency mapping configurations, alert configurations, and/or connectors. Depending on the type of disaster and/or the desired application, the process 600 can retrieve all of these configurations or a subset of them.
In still more embodiments, the process 600 can apply the configuration data to the target network device (block 660). As those skilled in the art will recognize, these configurations can be applied in a variety of ways. There may be calls to the network device that can insert the configurations, or a file may be transferred to the target network device. The target network device may be configured to accept such data in response to a disaster or other message from the workload protection solution.
Although a specific embodiment for a process 600 for replicating configuration components suitable for carrying out the various steps, processes, methods, and operations described herein is discussed with respect to
Referring to
In a number of embodiments, the process 700 can determine if an event has occurred (block 720). As described above, an event can be a manual execution by a user (such as a network administrator etc.), a warning signal received by one or more network devices, a determination that a connection issue has occurred, or the like. When it is determined that no event has occurred, the process 700 can again monitor the network (block 710).
However, when it is determined that an event has occurred, the process 700 can determine one or more target network devices (block 730). The target network device can be any network device that may be affected by an event or is determined to be subject to an upcoming event (e.g., network connection issues, etc.). In certain events, multiple target devices may be affected and therefore determined.
In further embodiments, the process 700 can select a source network device (block 740). In some embodiments, the source network device may be a similar network device to the target network device. In additional embodiments, the source network device may be a virtualized or other image of the target network device previously stored prior to the event. In response to multiple target network devices being affected, multiple source network devices may be selected as well.
In various embodiments, the process 700 can retrieve configuration data from the source network device (block 750). As discussed above, the configuration data can comprise any number of configurations, settings, rules, policies, intents, filters, or other adjustable items associated with the network device. As previously discussed, these characteristics can include, but are not limited to, user defined labels, scopes, inventory filters, agent profiles, agent intents, workspaces, workspace policies, workspace clusters, user roles, user accounts, exclusion filters, external orchestrators, client server configurations (i.e., server ports), forensics profiles/intents, policy templates, collection rules, default application dependency mapping configurations, alert configurations, and/or connectors. These configurations can be accessed in any suitable manner including, but not limited to, an API call to the network device.
In more embodiments, the process 700 can apply the configuration data to the target network device (block 760). This application can be carried out via any suitable method. This can be a direct file transfer of an image or other state management method. In some embodiments, the application can be achieved by adjusting each configuration in series or in parallel to match a pre-defined configuration list or similar state.
In additional embodiments, the process 700 can determine if all target network devices have been processed (block 770). If all target network devices have not been processed, the process 700 can again determine a new target network device (block 730). However, if all target network devices have been processed, various optional embodiments can again continue to monitor the network (block 780). However, in some embodiments, the process 700 can stop as the disaster recovery has finished and can thus wait until it is triggered to execute again. In more embodiments, when the disaster recovery is set to occur at a predetermined interval, the process 700 may reset the timer.
Although a specific embodiment for a process 700 for processing network devices during a disaster recovery suitable for carrying out the various steps, processes, methods, and operations described herein is discussed with respect to
Referring to
In many embodiments, the device 800 may include an environment 802 such as a baseboard or “motherboard,” in physical embodiments that can be configured as a printed circuit board with a multitude of components or devices connected by way of a system bus or other electrical communication paths. Conceptually, in virtualized embodiments, the environment 802 may be a virtual environment that encompasses and executes the remaining components and resources of the device 800. In more embodiments, one or more processors 804, such as, but not limited to, central processing units (“CPUs”) can be configured to operate in conjunction with a chipset 806. The processor(s) 804 can be standard programmable CPUs that perform arithmetic and logical operations necessary for the operation of the device 800.
In additional embodiments, the processor(s) 804 can perform one or more operations by transitioning from one discrete, physical state to the next through the manipulation of switching elements that differentiate between and change these states. Switching elements generally include electronic circuits that maintain one of two binary states, such as flip-flops, and electronic circuits that provide an output state based on the logical combination of the states of one or more other switching elements, such as logic gates. These basic switching elements can be combined to create more complex logic circuits, including registers, adders-subtractors, arithmetic logic units, floating-point units, and the like.
In certain embodiments, the chipset 806 may provide an interface between the processor(s) 804 and the remainder of the components and devices within the environment 802. The chipset 806 can provide an interface to communicatively couple a random-access memory (“RAM”) 808, which can be used as the main memory in the device 800 in some embodiments. The chipset 806 can further be configured to provide an interface to a computer-readable storage medium such as a read-only memory (“ROM”) 810 or non-volatile RAM (“NVRAM”) for storing basic routines that can help with various tasks such as, but not limited to, starting up the device 800 and/or transferring information between the various components and devices. The ROM 810 or NVRAM can also store other application components necessary for the operation of the device 800 in accordance with various embodiments described herein.
Different embodiments of the device 800 can be configured to operate in a networked environment using logical connections to remote computing devices and computer systems through a network, such as the network 840. The chipset 806 can include functionality for providing network connectivity through a network interface card (“NIC”) 812, which may comprise a gigabit Ethernet adapter or similar component. The NIC 812 can be capable of connecting the device 800 to other devices over the network 840. It is contemplated that multiple NICs 812 may be present in the device 800, connecting the device to other types of networks and remote systems.
In further embodiments, the device 800 can be connected to a storage 818 that provides non-volatile storage for data accessible by the device 800. The storage 818 can, for example, store an operating system 820, applications 822, and data 828, 830, 832, which are described in greater detail below. The storage 818 can be connected to the environment 802 through a storage controller 814 connected to the chipset 806. In certain embodiments, the storage 818 can consist of one or more physical storage units. The storage controller 814 can interface with the physical storage units through a serial attached SCSI (“SAS”) interface, a serial advanced technology attachment (“SATA”) interface, a fiber channel (“FC”) interface, or other type of interface for physically connecting and transferring data between computers and physical storage units.
The device 800 can store data within the storage 818 by transforming the physical state of the physical storage units to reflect the information being stored. The specific transformation of physical state can depend on various factors. Examples of such factors can include, but are not limited to, the technology used to implement the physical storage units, whether the storage 818 is characterized as primary or secondary storage, and the like.
For example, the device 800 can store information within the storage 818 by issuing instructions through the storage controller 814 to alter the magnetic characteristics of a particular location within a magnetic disk drive unit, the reflective or refractive characteristics of a particular location in an optical storage unit, or the electrical characteristics of a particular capacitor, transistor, or other discrete component in a solid-state storage unit, or the like. Other transformations of physical media are possible without departing from the scope and spirit of the present description, with the foregoing examples provided only to facilitate this description. The device 800 can further read or access information from the storage 818 by detecting the physical states or characteristics of one or more particular locations within the physical storage units.
In addition to the storage 818 described above, the device 800 can have access to other computer-readable storage media to store and retrieve information, such as program modules, data structures, or other data. It should be appreciated by those skilled in the art that computer-readable storage media is any available media that provides for the non-transitory storage of data and that can be accessed by the device 800. In some examples, the operations performed by a cloud computing network, and or any components included therein, may be supported by one or more devices similar to device 800. Stated otherwise, some or all of the operations performed by the cloud computing network, and or any components included therein, may be performed by one or more devices 800 operating in a cloud-based arrangement.
By way of example, and not limitation, computer-readable storage media can include volatile and non-volatile, removable and non-removable media implemented in any method or technology. Computer-readable storage media includes, but is not limited to, RAM, ROM, erasable programmable ROM (“EPROM”), electrically-erasable programmable ROM (“EEPROM”), flash memory or other solid-state memory technology, compact disc ROM (“CD-ROM”), digital versatile disk (“DVD”), high definition DVD (“HD-DVD”), BLU-RAY, or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information in a non-transitory fashion.
As mentioned briefly above, the storage 818 can store an operating system 820 utilized to control the operation of the device 800. According to one embodiment, the operating system comprises the LINUX operating system. According to another embodiment, the operating system comprises the WINDOWS® SERVER operating system from MICROSOFT Corporation of Redmond, Washington. According to further embodiments, the operating system can comprise the UNIX operating system or one of its variants. It should be appreciated that other operating systems can also be utilized. The storage 818 can store other system or application programs and data utilized by the device 800.
In various embodiment, the storage 818 or other computer-readable storage media is encoded with computer-executable instructions which, when loaded into the device 800, may transform it from a general-purpose computing system into a special-purpose computer capable of implementing the embodiments described herein. These computer-executable instructions may be stored as application 822 and transform the device 800 by specifying how the processor(s) 804 can transition between states, as described above. In some embodiments, the device 800 has access to computer-readable storage media storing computer-executable instructions which, when executed by the device 800, perform the various processes described above with regard to
In still further embodiments, the device 800 can also include one or more input/output controllers 816 for receiving and processing input from a number of input devices, such as a keyboard, a mouse, a touchpad, a touch screen, an electronic stylus, or other type of input device. Similarly, an input/output controller 816 can be configured to provide output to a display, such as a computer monitor, a flat panel display, a digital projector, a printer, or other type of output device. Those skilled in the art will recognize that the device 800 might not include all of the components shown in
As described above, the device 800 may support a virtualization layer, such as one or more virtual resources executing on the device 800. In some examples, the virtualization layer may be supported by a hypervisor that provides one or more virtual machines running on the device 800 to perform functions described herein. The virtualization layer may generally support a virtual resource that performs at least a portion of the techniques described herein.
In many embodiments, the device 800 can include a workload protection logic 824 that can be configured to perform one or more of the various steps, processes, operations, and/or other methods that are described above. While the embodiment shown in
In a number of embodiments, the storage 818 can include telemetry data 828. As discussed above, the telemetry data 828 can be collected in a variety of ways and may involve data related to multiple network devices. The telemetry data 828 may be associated with an entire network or a portion/partition of a network. This may also include a relationship of the various associated devices that are associated with each other. In additional embodiments, the telemetry data 828 can include data related to the configuration of one or more network devices, data centers, applications, or the like, including, but not limited to, IP addresses, subnets, etc. This telemetry data 828 can be utilized by a first-time user experience process to generate prompts, suggestions, or other interactions with a user when setting up a network for workload protection. As those skilled in the art will recognize, telemetry data 828 can be configured to track a variety of different aspects of a network, it's devices, and associated workloads.
In various embodiments, the storage 818 can include workload data 830. As described above, workload data 830 can be associated with various network devices, data centers, applications, or other processes within a network. Each workload may have additional workload data 830 associated with it including origin, status, label, scope, etc. In various embodiments, workload data 830 may be utilized to describe additional attributes of the workload, including one of: a workload's bandwidth usage, latency, traffic patterns, quality-related metrics, throughput, performance, security-related events, resource utilization, and/or scalability traits.
In still more embodiments, the storage 818 can include policy data 832. As discussed above, policy data 832 can include data that related to a network's configuration, such as hierarchy, segmentation, scope, labels, etc. In some embodiments, policy data 832 can be associated with one of: access control, quality-related policies, security, routing, traffic shaping, authentication/authorization, compliance, data retention/backup, remote access, wireless network policies, and/or any service level agreements. Policy data 832 can be utilized by the workload protection solution in various ways including, but not limited to, developing a segmentation policy, and/or generating one or more prompts during a first-time user experience.
In still more embodiments, the storage 818 can include user input data 834. As discussed above, user input data 834 can be received from various user inputs via disaster recovery prompts or the like. The user input data 834 can be combined or utilized in tandem with various data received from one or more agents deployed on the network. In certain embodiments, the user input data 834 can be received via one or more web-based protocols which can be stored on a temporary basis or parsed and stored in a long-term way within the user input data 834.
Finally, in many embodiments, data may be processed into a format usable by a machine-learning model 826 (e.g., feature vectors, etc.), and or other pre-processing techniques. The machine learning (“ML”) model 826 may be any type of ML model, such as supervised models, reinforcement models, and/or unsupervised models. The ML model 826 may include one or more of linear regression models, logistic regression models, decision trees, Naïve Bayes models, neural networks, k-means cluster models, random forest models, and/or other types of ML models 826. The ML model 826 may be configured to learn the pattern of a network's current setup and/or any security needs of various network devices and generate predictions, configurations, and/or confidence levels regarding disaster recovery of a network for workload protection and/or segmentation, etc. In some embodiments, the ML model 826 can be configured to determine which method of generating those predictions would work best based on certain conditions or with certain network devices.
The ML model(s) 826 can be configured to generate inferences to make predictions or draw conclusions from data. An inference can be considered the output of a process of applying a model to new data. This can occur by learning from at least the telemetry data 828, workload data 830, policy data 832, user input data 834, and/or the underlying algorithmic data and use that learning to predict future configurations, outcomes, and needs. These predictions are based on patterns and relationships discovered within the data. To generate an inference, such as a determination on anomalous movement, the trained model can take input data and produce a prediction or a decision/determination. The input data can be in various forms, such as images, audio, text, or numerical data, depending on the type of problem the model was trained to solve. The output of the model can also vary depending on the problem, and can be a single number, a probability distribution, a set of labels, a decision about an action to take, etc. Ground truth for the ML model(s) 826 may be generated by human/administrator verifications or may compare predicted outcomes with actual outcomes. The training set of the ML model(s) 826 can be provided by the manufacturer prior to deployment and can be based on previously verified data.
Although a specific embodiment for a device 800 suitable for configuration with a workload protection logic 824 suitable for carrying out the various steps, processes, methods, and operations described herein is discussed with respect to
Although the present disclosure has been described in certain specific aspects, many additional modifications and variations would be apparent to those skilled in the art. In particular, any of the various processes described above can be performed in alternative sequences and/or in parallel (on the same or on different computing devices) in order to achieve similar results in a manner that is more appropriate to the requirements of a specific application. It is therefore to be understood that the present disclosure can be practiced other than specifically described without departing from the scope and spirit of the present disclosure. Thus, embodiments of the present disclosure should be considered in all respects as illustrative and not restrictive. It will be evident to the person skilled in the art to freely combine several or all of the embodiments discussed here as deemed suitable for a specific application of the disclosure. Throughout this disclosure, terms like “advantageous”, “exemplary” or “example” indicate elements or dimensions which are particularly suitable (but not essential) to the disclosure or an embodiment thereof and may be modified wherever deemed suitable by the skilled person, except where expressly required. Accordingly, the scope of the disclosure should be determined not by the embodiments illustrated, but by the appended claims and their equivalents.
Any reference to an element being made in the singular is not intended to mean “one and only one” unless explicitly so stated, but rather “one or more.” All structural and functional equivalents to the elements of the above-described preferred embodiment and additional embodiments as regarded by those of ordinary skill in the art are hereby expressly incorporated by reference and are intended to be encompassed by the present claims.
Moreover, no requirement exists for a system or method to address each, and every problem sought to be resolved by the present disclosure, for solutions to such problems to be encompassed by the present claims. Furthermore, no element, component, or method step in the present disclosure is intended to be dedicated to the public regardless of whether the element, component, or method step is explicitly recited in the claims. Various changes and modifications in form, material, workpiece, and fabrication material detail can be made, without departing from the spirit and scope of the present disclosure, as set forth in the appended claims, as might be apparent to those of ordinary skill in the art, are also encompassed by the present disclosure.
