The use of containers has changed the way applications are packaged and deployed, with monolithic applications being replaced by microservice-based applications. Here, the application is broken down into multiple, loosely coupled services running in containers, with each service implementing a specific, well-defined part of the application. However, the use of containers also introduces new challenges, in that the fleet of containers need to be managed and all these services and containers need to communicate with each other.
Management of the containers is addressed by container orchestration systems, such as Docker Swarm®, Apache Mesos®, or Kubernetes®, the latter of which has become a de-facto choice for container orchestration. Kubernetes clusters can be run in an on-premises datacenter or in any public cloud (e.g., as a managed service or by bringing up your own cluster on compute instances). In certain cases, an application could be offered by an application provider as a multi-tenant application. In such a scenario, the application provider needs to ensure fairness in distribution of resources to the different tenants.
Some embodiments provide a multi-tenant network policy manager implemented in a container cluster (e.g., a Kubernetes cluster). The network policy manager manages the logical networks for multiple tenants, each of which may have a logical network that is implemented across a respective set of one or more datacenters. The network policy manager cluster is responsible for receiving logical network configuration policy from administrators for the tenants, storing the logical network configuration, and distributing this configuration to the different tenant datacenters so that the logical networks can be correctly implemented across the tenant datacenters.
Within the container cluster, different functions of the network policy manager are implemented as different services (e.g., micro-services) on their own containers (e.g., on separate Kubernetes Pods). In some embodiments, the cluster includes multiple nodes, with the various services assigned to different nodes. In some embodiments, the services include both (i) shared services that are shared by all of the tenants and (ii) per-tenant services that are instantiated on a per-tenant basis (i.e., each container implementing the service is dedicated to a single tenant).
The network policy manager of some embodiments includes (i) application programming interface (API) processing services, (ii) a database service or services, (iii) queue management services, (iv) span determination services, and (v) channel management services. In some embodiments, the API processing services and the database service are shared between the various tenants, while the queue management services, span determination services, and channel management services are implemented on a per-tenant basis.
The API processing services receive configuration requests from tenants (e.g., specifying modifications to the tenant's logical network). In some embodiments, the ingress path for the container cluster is handled by a gateway that performs load balancing across the API processing services. That is, each configuration request is distributed by the gateway to one of the API processing services in the container cluster according to a load balancing algorithm. Each of these API processing services can receive configuration requests from multiple different tenants, as the API processing services of some embodiments are not instantiated on a per-tenant basis. In some embodiments, the gateway/load balancer also ensures that a single tenant cannot overload the system and prevent other tenants from being able to access the API processing services.
When a configuration request is received by one of the API processing services, the service parses the request to identify (i) the tenant making the request and (ii) the logical network modification requested. The request may specify to add, remove, or change a logical network element (e.g., a logical forwarding element, logical port, policy rule, etc.) in some embodiments. The API processing service then posts the logical network configuration change to a configuration queue for the identified tenant as well as to the logical network configuration stored for the tenant in the shared database.
The shared database, in some embodiments, is managed by one or more database services in the cluster. In some embodiments, the database is a distributed database (e.g., distributed across nodes in the cluster or stored outside of the container cluster) that stores the logical network configuration for each tenant. The database may be organized so as to store separate sets of tables for each tenant, or in any other way, so long as the tenant logical network configurations are accessible. In some embodiments, the logical network configuration data in the database tables for a particular tenant is expressed as a hierarchical tree of tenant intent.
As mentioned, the other services that make up the multi-tenant policy manager are separated per tenant in some embodiments, rather than shared. These services include the queue management services, span determination services, and channel management services. In some embodiments, a particular enterprise may have more than one separate logical network spanning different sets of (potentially overlapping) datacenters, which are treated as different tenants by the policy manager in some embodiments (and thus have separate corresponding sets of services).
The queue management service for a tenant stores the logical network configuration changes in a persistent configuration queue for the tenant. In some embodiments, this queue is created for the tenant logical network when the tenant is first defined within the policy manager.
The span determination service for a given tenant determines, for each logical network configuration change, which of the datacenters spanned by the tenant logical network needs to receive the update. In some embodiments, certain logical network elements only span a subset of the datacenters spanned by the logical network (e.g., logical switches or routers defined only within a specific datacenter, policy rules defined only for a subset of datacenters, etc.). The span determination service is responsible for making this determination for each update and providing one or more copies of the update to its corresponding channel management service (for the same tenant). In some embodiments, the span determination service also identifies for each item of logical network configuration stored in the database, which tenant datacenters require that configuration item.
The span determination services, in some embodiments, can either be on-demand or dedicated services. If a tenant has specified (e.g., via its subscription to the policy manager) for a dedicated span determination service, then this service will be instantiated either at the same time as the corresponding tenant queue or when a first logical network configuration change is added to that queue and will not be removed even when inactive. On the other hand, if a tenant specifies for on-demand span determination service, then this service is instantiated when the first logical network configuration change is added to the corresponding tenant queue but can be removed (and its resources recovered for use in the cluster) after a predetermined period of inactivity.
The channel management service for a particular tenant, in some embodiments, maintains dedicated channels (e.g., asynchronous channels) with each of the datacenters spanned by the tenant's logical network. Specifically, in some embodiments, the channel management service maintains channels with local network managers at each of these datacenters. In some embodiments, the channel management service includes queues for each of the tenant datacenters and logical network configuration changes are stored to each of the queues corresponding to the datacenters that require the changes. In addition, in some such embodiments, the channel management service guarantees various connection parameters required for dissemination of data.
By separating the queue management services, span determination services, and channel management services on a per-tenant basis, this ensures that a single tenant making large-scale logical network configuration changes does not overload the system to the detriment of the other tenants. Each per-tenant service has its own allocated resources (which may be dependent on the tenant's subscription with the policy manager) and thus can continue processing any logical network configuration changes for its respective tenants even if another tenant's services are overloaded. In addition, the number of services can be scaled as additional tenants are added to the policy manager.
In some cases, a datacenter spanned by one of the tenant logical networks will require a complete synchronization of the logical network for that tenant (i.e., at least the portion of the logical network that spans to that datacenter). This can be a fairly resource-intensive process, as the entire logical network configuration relating to that particular datacenter needs to be streamed from the database to the local network manager for that datacenter. In some embodiments, rather than burdening all of the existing services that handle the provision of updates for that tenant, the policy manager instantiates a separate on-demand configuration streaming service to handle the synchronization process. In different embodiments, this on-demand service may be instantiated within the container cluster or in a different container cluster (so as to avoid overloading resources of the primary container cluster housing the network policy manager).
The full synchronization of the configuration can be required for various reasons. For instance, if connectivity is lost between a tenant's channel management service and the local network manager for a particular datacenter, upon restoration of that connectivity the channel management service will notify a management service (e.g., a shared service) that executes in the container cluster. This management service is responsible for instantiating the on-demand configuration streaming service in some embodiments. In other cases, the synchronization might be required due to the receipt of an API command (i.e., via the shared API policy processing services) to synchronize the configuration for a particular datacenter or when a new datacenter is added to the span of a tenant logical network (as a certain portion of the tenant logical network may automatically span to this new datacenter).
In order to stream the requisite configuration data to the local network manager at the particular datacenter, the instantiated on-demand configuration streaming service reads the data from the shared database and provides the data (as a stream of updates) to the channel management service for the tenant (identified for being sent to the particular datacenter so that it is enqueued correctly by the channel management service). In some embodiments, each item of network configuration data has a span that is marked within the database and this span is used by the on-demand streaming configuration service to retrieve the correct configuration data. Once the configuration data has been fully streamed to the particular datacenter, the management service stops and removes the on-demand configuration streaming service in order to free up the resources.
In addition, the network policy manager of some embodiments limits the number of concurrently instantiated configuration streaming services (therefore limiting the number of datacenters that can be synchronized at the same time) in order to limit the strain on the shared database (e.g., to 5, 10, 20, etc. concurrent synchronizations). Some embodiments also limit the number of concurrent synchronizations for a particular tenant to a smaller number or otherwise ensure that this maximum number of concurrently instantiated configuration streaming services is spread fairly among all of the tenants (e.g., based on tenant subscriptions).
The preceding Summary is intended to serve as a brief introduction to some embodiments of the invention. It is not meant to be an introduction or overview of all inventive subject matter disclosed in this document. The Detailed Description that follows and the Drawings that are referred to in the Detailed Description will further describe the embodiments described in the Summary as well as other embodiments. Accordingly, to understand all the embodiments described by this document, a full review of the Summary, Detailed Description, and the Drawings is needed. Moreover, the claimed subject matters are not to be limited by the illustrative details in the Summary, Detailed Description, and the Drawings, but rather are to be defined by the appended claims, because the claimed subject matters can be embodied in other specific forms without departing from the spirit of the subject matters.
The novel features of the invention are set forth in the appended claims. However, for purpose of explanation, several embodiments of the invention are set forth in the following figures.
In the following detailed description of the invention, numerous details, examples, and embodiments of the invention are set forth and described. However, it will be clear and apparent to one skilled in the art that the invention is not limited to the embodiments set forth and that the invention may be practiced without some of the specific details and examples discussed.
Some embodiments provide a multi-tenant network policy manager implemented in a container cluster (e.g., a Kubernetes cluster). The network policy manager manages the logical networks for multiple tenants, each of which may have a logical network that is implemented across a respective set of one or more datacenters. The network policy manager cluster is responsible for receiving logical network configuration policy from administrators for the tenants, storing the logical network configuration, and distributing this configuration to the different tenant datacenters so that the logical networks can be correctly implemented across the tenant datacenters.
The network policy manager, in some embodiments, is responsible for acting as a global network manager for multiple tenant logical networks. Each tenant logical network spans one or more physical sites (e.g., datacenters), and a separate local network manager operates at each of these physical sites to communicate with the network policy manager. It should be noted that a single tenant may administer multiple separate logical networks, but for the purposes of this description these are treated as separate tenants (e.g., in some embodiments each logical network has its own subscription with the network policy manager provider that specifies its own separate requirements and is thus treated separately by the network policy manager).
For a given tenant logical network, the network policy manager receives global logical network configuration data (e.g., from a network administrator through a user interface provided to the administrator). The primary purpose of the network policy manager (with respect to a particular tenant) is to receive and store the global configuration for a logical network that spans multiple datacenters, determine the span for each logical network element in the global logical network configuration (i.e., the datacenters at which the logical network is implemented) based on the specified configuration, and distribute the configuration data for each element to the local network managers at the datacenters that require the configuration data for that element. The operation of a global network manager for a single tenant logical network is described in greater detail in U.S. Pat. Nos. 11,381,456 and 11,088,919, both of which are incorporated herein by reference.
As shown in
The management service 105, in some embodiments, handles the management of the other services in the cluster 100. For instance, the management service 105 is responsible for instantiating and configuring additional API processing services 110 as needed, as well as starting up new sets of per-tenant queue management services, span determination services, and channel management services as new tenant logical networks are defined. The management service 105 is also responsible for stopping these services as needed (e.g., removing a set of per-tenant services when its corresponding tenant logical network is deleted). It should be noted that although the management service 105 is only shown communicating with the per-tenant services 120, 135, and 150 of tenant 1 (via the dashed lines), it actually communicates similarly with all of the other per-tenant services as well.
The API processing services 110 receive configuration requests from tenants (e.g., specifying modifications to the tenant's logical network). In some embodiments, the ingress path for the container cluster 100 is handled by a gateway 165 that performs load balancing across the API processing services 110. That is, each configuration request is distributed by the gateway (which may be a single gateway or a gateway cluster) to one of the API processing services 110 in the container cluster 100 according to a load balancing algorithm. The gateway 165, in some embodiments, executes within the same datacenter as the container cluster 100 (e.g., as a gateway managed at least partly by the cloud provider that owns the public cloud in which the container cluster 100 is implemented). Configuration requests are received at the gateway 165 from tenants via a network (e.g., the public Internet, a virtual private network, etc.). In some embodiments, the tenant administrators use a network management client (e.g., provided by the network policy manager provider) that enables easy configuration of logical networks.
As mentioned, the API processing services 110 are shared between tenants (i.e., are not instantiated on a per-tenant basis) and thus each of these API processing services 110 can receive configuration requests from multiple different tenants. In some embodiments, the gateway/load balancer 165 also ensures that a single tenant cannot overload the system and prevent other tenants from being able to access the API processing services 110. For instance, the gateway 165 can be configured to detect when a single source is sending a large number of configuration requests and either throttle these requests or send all of them to the same API processing service 110 so that they back up at that service while the other services are able to process configuration requests from other tenants.
When a configuration request is received by one of the API processing services 110, the service 110 parses the request to identify (i) the tenant making the request and (ii) the logical network modification requested. The request may specify to add, remove, or change a logical network element (e.g., a logical forwarding element, logical port, policy rule, etc.) in some embodiments. The API processing service 110 then posts the logical network configuration change to a configuration queue for the identified tenant as well as to the logical network configuration stored for the tenant in a shared database 170.
The shared database 170, in some embodiments, is managed by one or more shared database services 115. In some embodiments, the database 170 is a distributed database (e.g., Amazon DynamoDB® or a similar distributed database) that stores the logical network configuration for each tenant. In different embodiments, the database 170 may be distributed across nodes in the container cluster 100 or stored outside of the cluster (but accessed by the database service 115). The database 170 may be organized so as to store separate sets of tables for each tenant, or in any other way, so long as the tenant logical network configurations are accessible. In some embodiments, the logical network configuration data in the database tables for a particular tenant is expressed as a hierarchical tree of tenant intent. The hierarchical policy tree used to store a logical network configuration in some embodiments is described in U.S. Pat. Nos. 11,381,456 and 11,088,919, both of which are incorporated by reference above.
As mentioned, the other services 120-160 that make up the multi-tenant policy manager are separated per tenant in some embodiments, rather than shared between tenants. These services include the queue management services 120-130, span determination services 135-145, and channel management services 150-160. As mentioned, a particular enterprise may have more than one separate logical network spanning different sets of (potentially overlapping) datacenters, which are treated as different tenants by the policy manager in some embodiments (and thus have separate corresponding sets of services).
The queue management service 120-130 for a given tenant stores the logical network configuration changes requested for that tenant (as parsed by the API processing services 110) in a persistent configuration queue for the tenant. Because the API processing services 110 are shared, multiple different API processing services 110 may post configuration requests to the same queue. In some embodiments, the queue for a particular tenant logical network is created (and the queue management service instantiated to manage access to that queue) when the tenant logical network is initially defined within the policy manager (even if no configuration has yet been received). It should be noted that, in some embodiments, one or more shared queue management services are used in the network policy manager (instead of per-tenant services) to manage per-tenant configuration queues.
The span determination services 135-145 determine, for each logical network configuration change in its tenant's corresponding queue, which of the datacenters spanned by the tenant logical network needs to receive the update. In some embodiments, certain logical network elements only span a subset of the datacenters spanned by the logical network (e.g., logical switches or routers defined only within a specific datacenter, policy rules defined only for a subset of datacenters, etc.). The span determination service 135-145 is responsible for making this determination for each update and providing the update to its corresponding channel management service 150-160 (i.e., the channel management service for the same tenant). In some embodiments, the span determination service 135-145 also identifies, for each item of logical network configuration stored in the shared database 170, which tenant datacenters require that configuration item so that this span information can be stored in the database 170. The span calculations of some embodiments are described in U.S. Pat. Nos. 11,381,456 and 11,088,919, both of which are incorporated by reference above.
In some embodiments the span determination services 135-145 can either be on-demand or dedicated services. In some embodiments, the network policy manager restricts the span determination services to one or the other. However, in other embodiments, as shown in this example, the tenant can specify (e.g., via their subscription to the network policy manager) whether their span determination service should be on-demand (e.g., a function as a service) or dedicated.
If a tenant specifies a dedicated span determination service (e.g., tenant 1 in the example shown in the figure), then this service 135 is instantiated (e.g., by the management service 105) either at the same time as the corresponding tenant queue or when a first logical network configuration change is added to that queue. Even if the queue has not received any configuration change requests over a period of time, the span management service 135 remains operational. On the other hand, if a tenant specifies on-demand span determination service (e.g., tenant 2 in the example), then this service 140 is instantiated (e.g., by the management service 105) when the first logical network configuration change is added to the corresponding tenant queue but can be removed (e.g., by the management service 105) and its resources recovered for use in the cluster after a period of inactivity lasting a predetermined time.
The channel management services 150-160 each maintain dedicated channels with each of the datacenters spanned by their respective tenant's logical network. Specifically, in some embodiments, the channel management service for each tenant maintains asynchronous channels with local network managers at each of the datacenters spanned by the tenant's logical network. In some embodiments, each channel management service 150-160 includes queues for each of the tenant datacenters. When the corresponding span determination service 135-145 identifies the datacenters spanned by a particular logical network configuration change, that change is stored to each of the queues corresponding to those identified datacenters. The channel management service 150-160 then manages the transmission of these configuration changes from the respective queues to the respective local network managers. In addition, in some such embodiments, the channel management service guarantees various connection parameters required for dissemination of this configuration data and receives notifications and/or certain configuration updates from the local network managers. The channel management service for a single tenant is also discussed in further detail in U.S. Pat. Nos. 11,381,456 and 11,088,919, both of which are incorporated by reference above.
By separating the queue management services, span determination services, and channel management services on a per-tenant basis, this ensures that a single tenant making large-scale logical network configuration changes does not overload the system to the detriment of the other tenants. Each per-tenant service has its own allocated resources (which may be dependent on the tenant's subscription with the policy manager) and thus can continue processing any logical network configuration changes for its respective tenants even if another tenant's services are overloaded. In addition, the number of services can be easily scaled as additional tenants are added to the policy manager.
As shown, the process 200 begins by receiving (at 205) a configuration change request. In some embodiments, this request is previously received by the ingress gateway/load balancer for the network policy manager, which selects one of the shared API processing services of the network policy manager to process the request.
Next, the process 200 parses (at 210) the received change request to identify (i) the tenant and (ii) the requested logical network configuration change. The tenant, in some embodiments, is specified using a unique identifier in the change request. Other embodiments identify the tenant based on the source of the change request (e.g., a source network address) or other identifying information. Logical network configuration changes can add, delete, or modify any aspect of the logical network and/or certain aspects of how that logical network is implemented across the physical datacenters. The logical network aspects can include logical forwarding elements (e.g., logical switches and/or routers), logical services (e.g., distributed firewall, network address translation, etc.), and/or security policy (e.g., security groups and/or security rules), as well as changes to the span of these elements. In addition, the logical network configuration changes can specify groups of physical devices that are eligible at specific datacenters for implementation of the logical network at those datacenters.
After parsing the received change, the process 200 posts (at 215) the logical network configuration change, marked with an identifier of the tenant, to the shared database service for storage in the shared network policy manager database. As discussed, this database stores the logical network configuration for all of the tenants, either within the network policy manager container cluster or separate from the cluster. The shared database service is responsible, in some embodiments, for accessing (i.e., storing data to and retrieving data from) this database.
The process 200 also posts (at 220) the logical network configuration change to the persistent queue of the identified tenant, then ends. In some embodiments, because each tenant logical network has its own queue managed by a separate queue management service, this logical network configuration change need not specify the tenant.
As shown, the process 400 begins by, at the span determination service for a particular tenant, identifying (at 405) a new configuration change in the corresponding queue for the particular tenant. In some embodiments, the queue management service notifies the corresponding span determination service each time a new configuration change is added to the queue. In other embodiments, a notification is passed through the management service for the network policy manager, or the span determination service regularly polls the corresponding queue management service to determine whether any configuration changes are present in the queue.
The process 400 then retrieves (at 410) this configuration change from the queue. In some embodiments, when the span determination service has finished processing any previous configuration changes and has been notified that there is at least one configuration change pending in its queue, the span determination service sends a retrieval request to the corresponding queue management service to retrieve the next configuration change in the queue for that tenant. Figure shows that the queue management service 505 for tenant N provides a configuration change 510 to the span determination service 500 for tenant N (e.g., based on a retrieval request from the span determination service 500 for the next configuration change in the queue). The queue management service 505 also removes this configuration change 510 from the queue, such that the next request from the span determination service 500 will retrieve a different configuration change.
Next, the process 400 determines (at 415) the one or more datacenters spanned by the configuration change. In some embodiments, the span determination service interacts with the shared database to make this determination, as the span for a particular logical network element may depend on other logical network elements. In other embodiments, the span determination service stores a mapping of existing logical network elements to groups of datacenters and can use this mapping for changes that do not affect the span of a logical network element (e.g., connecting a logical switch to an existing logical router with a known span). However, for some changes (e.g., certain changes to policy), assessment of the hierarchical policy tree for the logical network is required and thus the span determination service needs to interact with the shared database service to retrieve at least a portion of the existing logical network configuration.
Finally, the process 400 provides a copy of the configuration change to the channel management service for the particular tenant for each datacenter spanned by the change, so that the channel management service can distribute the configuration change to the local network managers at these datacenters. The process 400 then ends. Different embodiments provide this configuration change differently when multiple datacenters require the change. In some embodiments, the span determination service provides a separate copy of the configuration change to the channel management service, with each copy marked for a specific datacenter. In other embodiments, the span determination provides a single copy of the change along with the list of datacenters to the channel management service, which replicates the change for each datacenter.
In some cases, a datacenter spanned by one of the tenant logical networks will require a complete synchronization of the logical network for that tenant (i.e., at least the portion of the logical network that spans to that datacenter). This can be a fairly resource-intensive process, as the entire logical network configuration relating to that particular datacenter needs to be streamed from the database to the local network manager for that datacenter. In some embodiments, rather than burdening all of the existing services that handle the provision of updates for that tenant, the policy manager (e.g., the management service of the policy manager) instantiates a separate on-demand configuration streaming service to handle the synchronization process. In different embodiments, this on-demand service may be instantiated within the container cluster or in a different container cluster (so as to avoid overloading resources of the primary container cluster housing the network policy manager).
As shown, the process 600 begins by determining (at 605) that a particular datacenter for a particular tenant (i.e., spanned by the particular tenant's logical network) requires a complete synchronization of its logical network configuration from the global network policy manager. The logical network configuration synchronization may be required for various different reasons. For instance, if connectivity is lost between a tenant's channel management service and the local network manager for a particular datacenter, upon restoration of that connectivity, the channel management service notifies the management service that is responsible for instantiating the on-demand configuration streaming service in some embodiments. In other cases, the synchronization might be required due to the receipt of an API command (i.e., via the shared API policy processing services) to synchronize the configuration for a particular datacenter or when a new datacenter is added to the span of a tenant logical network (as a certain portion of the tenant logical network may automatically span to this new datacenter).
The first stage 705 of
Next, the process 600 determines (at 610) whether an on-demand service can currently be instantiated for the particular tenant. Some embodiments limit the number of concurrently instantiated on-demand configuration streaming services, therefore limiting the number of datacenters for which the configurations can be synchronized at the same time (e.g., to 10, 20, etc. concurrent synchronizations). This limits the strain on the shared database. While ideally the need for complete synchronizations would be rare, if the network policy manager were to lose external connectivity or a tenant simultaneously added a larger number of new datacenters to its logical network, overloads could occur.
In addition, to prevent a single tenant from locking other tenants out from synchronizing their own datacenters, some embodiments limit the number of concurrent synchronizations for a particular tenant to a smaller number or otherwise ensure that this maximum number of concurrently instantiated configuration streaming services is spread fairly among all of the tenants. For instance, a single tenant might be limited to a maximum that is a particular percentage (50%, 67%, etc.) of the total allowed number of concurrent synchronizations, with this per-tenant maximum variable based on the tenant subscription.
If the on-demand service cannot yet be instantiated for the particular tenant (either because the overall maximum or the per-tenant maximum has been reached), the process 600 holds off (at 615) on synchronizing the configuration for the particular datacenter. While the process 600 is shown as returning to 610 to continuously check whether the service can be instantiated for the tenant, it should be understood that this is a conceptual process, and the management service of the network policy manager may handle this situation differently in different embodiments. For instance, in some embodiments, the management service stores a queue of required synchronizations and is configured to instantiate an on-demand service for the next synchronization in the queue once one of the ongoing synchronizations is complete (although if the first synchronization in the queue is for a tenant at their per-tenant maximum and the completed synchronization is for a different tenant, then the first synchronization for an eligible tenant is begun instead).
Once the service can be instantiated for the particular tenant (i.e., either upon determining that the synchronization is needed or after completion of another datacenter synchronization), the process 600 instantiates (at 620) a configuration streaming service for the particular tenant datacenter. In some embodiments, the management service instantiates the configuration streaming service by communicating with a cluster control plane (e.g., a Kubernetes control plane) to instantiate a Pod for the on-demand streaming service. The management service also configures this new service by specifying the particular tenant and datacenter that requires the configuration synchronization. The second stage 710 of
Once instantiated, the on-demand configuration streaming service retrieves the required logical network configuration data from the configuration database. If the database is organized with the span information stored for each logical network element, then the configuration streaming service can retrieve only the configuration data that spans to the specified datacenter. On the other hand, if this span information is not stored in the database, then the configuration streaming service of some embodiments retrieves all of the logical network data for the tenant and performs its own span calculations to determine which data should be streamed to the particular datacenter.
The configuration streaming service, in some embodiments, provides this data to the channel management service for the particular tenant, and the channel management service streams the logical network configuration data via its connection with the local network manager at the particular datacenter. In some embodiments, the logical network configuration is streamed as a series of configuration changes (in addition to start and stop indicators) that are added to the channel management service queue for the particular datacenter and then transmitted by the channel management service. In other embodiments, the configuration streaming service uses the connection maintained by the channel management service but bypasses its datacenter queue.
The third stage 715 of
As noted, once all of the logical network configuration data has been fully streamed to the particular datacenter, the on-demand configuration streaming service should be stopped (and deleted) in order to free up resources (potentially for additional synchronizations with other datacenters). Returning to
In some embodiments, the on-demand configuration streaming service sends this notification to the management service. The first stage 805 of
Upon receiving such a notification, the process 600 stops and removes (at 630) the configuration streaming service, then ends. In some embodiments, the management service stops the configuration streaming service by communicating with a cluster control plane (e.g., a Kubernetes control plane) to remove the Pod implementing the on-demand streaming service. In other embodiments, the management service stops and deletes the service (and its Pod) directly. The second stage 810 of
The bus 905 collectively represents all system, peripheral, and chipset buses that communicatively connect the numerous internal devices of the electronic system 900. For instance, the bus 905 communicatively connects the processing unit(s) 910 with the read-only memory 930, the system memory 925, and the permanent storage device 935.
From these various memory units, the processing unit(s) 910 retrieve instructions to execute and data to process in order to execute the processes of the invention. The processing unit(s) may be a single processor or a multi-core processor in different embodiments.
The read-only-memory (ROM) 930 stores static data and instructions that are needed by the processing unit(s) 910 and other modules of the electronic system. The permanent storage device 935, on the other hand, is a read-and-write memory device. This device is a non-volatile memory unit that stores instructions and data even when the electronic system 900 is off. Some embodiments of the invention use a mass-storage device (such as a magnetic or optical disk and its corresponding disk drive) as the permanent storage device 935.
Other embodiments use a removable storage device (such as a floppy disk, flash drive, etc.) as the permanent storage device. Like the permanent storage device 935, the system memory 925 is a read-and-write memory device. However, unlike storage device 935, the system memory is a volatile read-and-write memory, such a random-access memory. The system memory stores some of the instructions and data that the processor needs at runtime. In some embodiments, the invention's processes are stored in the system memory 925, the permanent storage device 935, and/or the read-only memory 930. From these various memory units, the processing unit(s) 910 retrieve instructions to execute and data to process in order to execute the processes of some embodiments.
The bus 905 also connects to the input and output devices 940 and 945. The input devices enable the user to communicate information and select commands to the electronic system. The input devices 940 include alphanumeric keyboards and pointing devices (also called “cursor control devices”). The output devices 945 display images generated by the electronic system. The output devices include printers and display devices, such as cathode ray tubes (CRT) or liquid crystal displays (LCD). Some embodiments include devices such as a touchscreen that function as both input and output devices.
Finally, as shown in
Some embodiments include electronic components, such as microprocessors, storage and memory that store computer program instructions in a machine-readable or computer-readable medium (alternatively referred to as computer-readable storage media, machine-readable media, or machine-readable storage media). Some examples of such computer-readable media include RAM, ROM, read-only compact discs (CD-ROM), recordable compact discs (CD-R), rewritable compact discs (CD-RW), read-only digital versatile discs (e.g., DVD-ROM, dual-layer DVD-ROM), a variety of recordable/rewritable DVDs (e.g., DVD-RAM, DVD-RW, DVD+RW, etc.), flash memory (e.g., SD cards, mini-SD cards, micro-SD cards, etc.), magnetic and/or solid state hard drives, read-only and recordable Blu-Ray® discs, ultra-density optical discs, any other optical or magnetic media, and floppy disks. The computer-readable media may store a computer program that is executable by at least one processing unit and includes sets of instructions for performing various operations. Examples of computer programs or computer code include machine code, such as is produced by a compiler, and files including higher-level code that are executed by a computer, an electronic component, or a microprocessor using an interpreter.
While the above discussion primarily refers to microprocessor or multi-core processors that execute software, some embodiments are performed by one or more integrated circuits, such as application specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs). In some embodiments, such integrated circuits execute instructions that are stored on the circuit itself.
As used in this specification, the terms “computer”, “server”, “processor”, and “memory” all refer to electronic or other technological devices. These terms exclude people or groups of people. For the purposes of the specification, the terms display or displaying means displaying on an electronic device. As used in this specification, the terms “computer readable medium,” “computer readable media,” and “machine readable medium” are entirely restricted to tangible, physical objects that store information in a form that is readable by a computer. These terms exclude any wireless signals, wired download signals, and any other ephemeral signals.
This specification refers throughout to computational and network environments that include virtual machines (VMs). However, virtual machines are merely one example of data compute nodes (DCNs) or data compute end nodes, also referred to as addressable nodes. DCNs may include non-virtualized physical hosts, virtual machines, containers that run on top of a host operating system without the need for a hypervisor or separate operating system, and hypervisor kernel network interface modules.
VMs, in some embodiments, operate with their own guest operating systems on a host using resources of the host virtualized by virtualization software (e.g., a hypervisor, virtual machine monitor, etc.). The tenant (i.e., the owner of the VM) can choose which applications to operate on top of the guest operating system. Some containers, on the other hand, are constructs that run on top of a host operating system without the need for a hypervisor or separate guest operating system. In some embodiments, the host operating system uses name spaces to isolate the containers from each other and therefore provides operating-system level segregation of the different groups of applications that operate within different containers. This segregation is akin to the VM segregation that is offered in hypervisor-virtualized environments that virtualize system hardware, and thus can be viewed as a form of virtualization that isolates different groups of applications that operate in different containers. Such containers are more lightweight than VMs.
Hypervisor kernel network interface modules, in some embodiments, is a non-VM DCN that includes a network stack with a hypervisor kernel network interface and receive/transmit threads. One example of a hypervisor kernel network interface module is the vmknic module that is part of the ESXi™ hypervisor of VMware, Inc.
It should be understood that while the specification refers to VMs, the examples given could be any type of DCNs, including physical hosts, VMs, non-VM containers, and hypervisor kernel network interface modules. In fact, the example networks could include combinations of different types of DCNs in some embodiments.
While the invention has been described with reference to numerous specific details, one of ordinary skill in the art will recognize that the invention can be embodied in other specific forms without departing from the spirit of the invention. In addition, a number of the figures (including
Number | Name | Date | Kind |
---|---|---|---|
5842043 | Nishimura | Nov 1998 | A |
6219699 | McCloghrie et al. | Apr 2001 | B1 |
6347374 | Drake et al. | Feb 2002 | B1 |
6615230 | Nishimura | Sep 2003 | B2 |
7502884 | Shah et al. | Mar 2009 | B1 |
7539745 | Wang et al. | May 2009 | B1 |
7802000 | Huang et al. | Sep 2010 | B1 |
7965699 | Accardi et al. | Jun 2011 | B1 |
8479275 | Naseh | Jul 2013 | B1 |
8611351 | Gooch et al. | Dec 2013 | B2 |
8625616 | Vobbilisetty et al. | Jan 2014 | B2 |
8660129 | Brendel et al. | Feb 2014 | B1 |
8707417 | Liang et al. | Apr 2014 | B1 |
9069599 | Martinez et al. | Jun 2015 | B2 |
9215213 | Bansal et al. | Dec 2015 | B2 |
9294270 | Wainner et al. | Mar 2016 | B2 |
9311122 | Guay et al. | Apr 2016 | B2 |
9330161 | D'Amato et al. | May 2016 | B2 |
9432215 | Stabile et al. | Aug 2016 | B2 |
9602312 | Koponen et al. | Mar 2017 | B2 |
9672054 | Gupta et al. | Jun 2017 | B1 |
9672060 | Behere et al. | Jun 2017 | B2 |
9755965 | Yadav et al. | Sep 2017 | B1 |
9825851 | Agarwal et al. | Nov 2017 | B2 |
9847938 | Chanda et al. | Dec 2017 | B2 |
9876711 | Chu et al. | Jan 2018 | B2 |
9906560 | Jain et al. | Feb 2018 | B2 |
9912616 | Shen et al. | Mar 2018 | B2 |
9923811 | Agarwal et al. | Mar 2018 | B2 |
9977688 | Nipane et al. | May 2018 | B2 |
10091028 | Koponen et al. | Oct 2018 | B2 |
10110417 | Hankins et al. | Oct 2018 | B1 |
10120668 | Palavalli et al. | Nov 2018 | B2 |
10129142 | Goliya et al. | Nov 2018 | B2 |
10135675 | Yu et al. | Nov 2018 | B2 |
10142127 | Cherian et al. | Nov 2018 | B2 |
10162656 | Palavalli et al. | Dec 2018 | B2 |
10187302 | Chu et al. | Jan 2019 | B2 |
10205771 | Palavalli et al. | Feb 2019 | B2 |
10241820 | Lambeth et al. | Mar 2019 | B2 |
10243797 | Lambeth et al. | Mar 2019 | B2 |
10243834 | Shekhar et al. | Mar 2019 | B1 |
10243846 | Jiang et al. | Mar 2019 | B2 |
10243848 | Agarwal et al. | Mar 2019 | B2 |
10257049 | Fried et al. | Apr 2019 | B2 |
10298489 | Williams et al. | May 2019 | B2 |
10333959 | Katrekar et al. | Jun 2019 | B2 |
10339123 | Venkatesh et al. | Jul 2019 | B2 |
10382529 | Wan et al. | Aug 2019 | B2 |
10412018 | Feng et al. | Sep 2019 | B1 |
10560343 | Cartsonis et al. | Feb 2020 | B1 |
10579945 | Gaurav et al. | Mar 2020 | B2 |
10587479 | Shakimov et al. | Mar 2020 | B2 |
10601705 | Hira et al. | Mar 2020 | B2 |
10616279 | Nimmagadda et al. | Apr 2020 | B2 |
10637800 | Wang et al. | Apr 2020 | B2 |
10673752 | Agarwal et al. | Jun 2020 | B2 |
10693833 | Mathew et al. | Jun 2020 | B2 |
10832224 | Palavalli et al. | Nov 2020 | B2 |
10862753 | Hira et al. | Dec 2020 | B2 |
10880158 | Lambeth et al. | Dec 2020 | B2 |
10880170 | Wang et al. | Dec 2020 | B2 |
10897420 | Pianigiani et al. | Jan 2021 | B1 |
10908938 | Palavalli et al. | Feb 2021 | B2 |
10942788 | Palavalli et al. | Mar 2021 | B2 |
10999154 | Ahrenholz et al. | May 2021 | B1 |
11057275 | Arunachalam et al. | Jul 2021 | B1 |
11088902 | Palavalli et al. | Aug 2021 | B1 |
11088916 | Chandrashekhar et al. | Aug 2021 | B1 |
11088919 | Chandrashekhar et al. | Aug 2021 | B1 |
11115301 | Margarian et al. | Sep 2021 | B1 |
11133958 | Torvi et al. | Sep 2021 | B2 |
11153170 | Chandrashekhar et al. | Oct 2021 | B1 |
11182163 | Beals et al. | Nov 2021 | B1 |
11258668 | Chandrashekhar et al. | Feb 2022 | B2 |
11303557 | Chandrashekhar et al. | Apr 2022 | B2 |
11316773 | Dubey et al. | Apr 2022 | B2 |
11336486 | Sharma et al. | May 2022 | B2 |
11336556 | Chandrashekhar et al. | May 2022 | B2 |
11343227 | Vaidya et al. | May 2022 | B2 |
11343283 | Vaidya et al. | May 2022 | B2 |
11374817 | Chandrashekhar et al. | Jun 2022 | B2 |
11374850 | Chandrashekhar et al. | Jun 2022 | B2 |
11381456 | Manzanilla et al. | Jul 2022 | B2 |
11394634 | Chandrashekhar et al. | Jul 2022 | B2 |
11438238 | Chandrashekhar et al. | Sep 2022 | B2 |
11496392 | Agarwal et al. | Nov 2022 | B2 |
11509522 | Palavalli et al. | Nov 2022 | B2 |
11528214 | Chandrashekar et al. | Dec 2022 | B2 |
11601474 | Vaidya et al. | Mar 2023 | B2 |
11683233 | Rogozinsky et al. | Jun 2023 | B2 |
11736383 | Chandrashekhar et al. | Aug 2023 | B2 |
11743168 | Dubey et al. | Aug 2023 | B2 |
11843548 | Devendranath | Dec 2023 | B1 |
20020029270 | Szczepanek | Mar 2002 | A1 |
20020093952 | Gonda | Jul 2002 | A1 |
20020131414 | Hadzic | Sep 2002 | A1 |
20030046347 | Nishimura | Mar 2003 | A1 |
20030167333 | Kumar et al. | Sep 2003 | A1 |
20030185151 | Kurosawa et al. | Oct 2003 | A1 |
20030185152 | Nederveen et al. | Oct 2003 | A1 |
20030188114 | Lubbers et al. | Oct 2003 | A1 |
20030188218 | Lubbers et al. | Oct 2003 | A1 |
20040052257 | Abdo et al. | Mar 2004 | A1 |
20050190757 | Sajassi | Sep 2005 | A1 |
20050235352 | Staats et al. | Oct 2005 | A1 |
20050288040 | Charpentier et al. | Dec 2005 | A1 |
20060092976 | Lakshman et al. | May 2006 | A1 |
20060179243 | Fields et al. | Aug 2006 | A1 |
20060179245 | Fields et al. | Aug 2006 | A1 |
20060193252 | Naseh et al. | Aug 2006 | A1 |
20060195896 | Fulp et al. | Aug 2006 | A1 |
20060221720 | Reuter | Oct 2006 | A1 |
20060251120 | Arimilli et al. | Nov 2006 | A1 |
20060287842 | Kim | Dec 2006 | A1 |
20070058631 | Mortier et al. | Mar 2007 | A1 |
20070130295 | Rastogi et al. | Jun 2007 | A1 |
20070217419 | Vasseur | Sep 2007 | A1 |
20070219653 | Martin | Sep 2007 | A1 |
20070239987 | Hoole et al. | Oct 2007 | A1 |
20080013474 | Nagarajan et al. | Jan 2008 | A1 |
20080049646 | Lu | Feb 2008 | A1 |
20080104302 | Carpio | May 2008 | A1 |
20080133729 | Fridman et al. | Jun 2008 | A1 |
20080268847 | Mukherjee et al. | Oct 2008 | A1 |
20080301379 | Pong | Dec 2008 | A1 |
20090037367 | Wein | Feb 2009 | A1 |
20090070337 | Romem et al. | Mar 2009 | A1 |
20090193297 | Williams et al. | Jul 2009 | A1 |
20090241192 | Thomas | Sep 2009 | A1 |
20090279536 | Unbehagen et al. | Nov 2009 | A1 |
20090279545 | Moonen | Nov 2009 | A1 |
20090292858 | Lambeth et al. | Nov 2009 | A1 |
20090296726 | Snively et al. | Dec 2009 | A1 |
20100250784 | Henry et al. | Sep 2010 | A1 |
20100257263 | Casado et al. | Oct 2010 | A1 |
20100275199 | Smith et al. | Oct 2010 | A1 |
20100322255 | Hao et al. | Dec 2010 | A1 |
20110032898 | Kazmi et al. | Feb 2011 | A1 |
20110047218 | Nojima et al. | Feb 2011 | A1 |
20110051714 | Somes | Mar 2011 | A1 |
20110085569 | Gnanasekaran et al. | Apr 2011 | A1 |
20110164752 | Wainner et al. | Jul 2011 | A1 |
20110188509 | Kern et al. | Aug 2011 | A1 |
20110231602 | Woods et al. | Sep 2011 | A1 |
20110299413 | Chatwani et al. | Dec 2011 | A1 |
20120084406 | Kumbalimutt | Apr 2012 | A1 |
20120120964 | Koponen et al. | May 2012 | A1 |
20120147898 | Koponen et al. | Jun 2012 | A1 |
20120275328 | Iwata et al. | Nov 2012 | A1 |
20130018947 | Archer et al. | Jan 2013 | A1 |
20130024579 | Zhang et al. | Jan 2013 | A1 |
20130042242 | Kagan | Feb 2013 | A1 |
20130044636 | Koponen et al. | Feb 2013 | A1 |
20130044641 | Koponen et al. | Feb 2013 | A1 |
20130044761 | Koponen et al. | Feb 2013 | A1 |
20130058250 | Casado et al. | Mar 2013 | A1 |
20130058335 | Koponen et al. | Mar 2013 | A1 |
20130058350 | Fulton | Mar 2013 | A1 |
20130058354 | Casado et al. | Mar 2013 | A1 |
20130058358 | Fulton et al. | Mar 2013 | A1 |
20130060819 | Lambeth et al. | Mar 2013 | A1 |
20130060940 | Koponen et al. | Mar 2013 | A1 |
20130074065 | McNeeney et al. | Mar 2013 | A1 |
20130103817 | Koponen et al. | Apr 2013 | A1 |
20130125120 | Zhang et al. | May 2013 | A1 |
20130132533 | Padmanabhan et al. | May 2013 | A1 |
20130144992 | Barabash et al. | Jun 2013 | A1 |
20130159637 | Forgette et al. | Jun 2013 | A1 |
20130212212 | Addepalli et al. | Aug 2013 | A1 |
20130215769 | Beheshti-Zavareh et al. | Aug 2013 | A1 |
20130254328 | Inoue et al. | Sep 2013 | A1 |
20130286833 | Torres et al. | Oct 2013 | A1 |
20130287026 | Davie | Oct 2013 | A1 |
20130301425 | Udutha et al. | Nov 2013 | A1 |
20130301501 | Olvera-Hernandez et al. | Nov 2013 | A1 |
20130301646 | Bogdanski et al. | Nov 2013 | A1 |
20130308641 | Ackley | Nov 2013 | A1 |
20140006354 | Parkison et al. | Jan 2014 | A1 |
20140006357 | Davis et al. | Jan 2014 | A1 |
20140006465 | Davis et al. | Jan 2014 | A1 |
20140007239 | Sharpe et al. | Jan 2014 | A1 |
20140064104 | Nataraja et al. | Mar 2014 | A1 |
20140075002 | Pradhan et al. | Mar 2014 | A1 |
20140136908 | Maggiari et al. | May 2014 | A1 |
20140146817 | Zhang | May 2014 | A1 |
20140169365 | Sundaram et al. | Jun 2014 | A1 |
20140172740 | McCormick et al. | Jun 2014 | A1 |
20140172939 | McSherry et al. | Jun 2014 | A1 |
20140201218 | Catalano et al. | Jul 2014 | A1 |
20140208150 | Abuelsaad et al. | Jul 2014 | A1 |
20140211661 | Gorkemli et al. | Jul 2014 | A1 |
20140241356 | Zhang et al. | Aug 2014 | A1 |
20140250220 | Kapadia et al. | Sep 2014 | A1 |
20140269435 | McConnell et al. | Sep 2014 | A1 |
20140301391 | Krishnan et al. | Oct 2014 | A1 |
20140304355 | Kamath et al. | Oct 2014 | A1 |
20140307744 | Dunbar et al. | Oct 2014 | A1 |
20140337500 | Lee | Nov 2014 | A1 |
20140351396 | Stabile et al. | Nov 2014 | A1 |
20150009797 | Koponen et al. | Jan 2015 | A1 |
20150009808 | Bejerano et al. | Jan 2015 | A1 |
20150010012 | Koponen et al. | Jan 2015 | A1 |
20150016276 | Decusatis et al. | Jan 2015 | A1 |
20150063364 | Thakkar et al. | Mar 2015 | A1 |
20150085862 | Song | Mar 2015 | A1 |
20150100704 | Davie et al. | Apr 2015 | A1 |
20150103842 | Chandrashekhar et al. | Apr 2015 | A1 |
20150103843 | Chandrashekhar et al. | Apr 2015 | A1 |
20150106804 | Chandrashekhar et al. | Apr 2015 | A1 |
20150117216 | Anand et al. | Apr 2015 | A1 |
20150117256 | Sabaa et al. | Apr 2015 | A1 |
20150154330 | Yachide et al. | Jun 2015 | A1 |
20150195126 | Vasseur et al. | Jul 2015 | A1 |
20150229641 | Sun et al. | Aug 2015 | A1 |
20150234668 | Ravinoothala et al. | Aug 2015 | A1 |
20150237014 | Bansal et al. | Aug 2015 | A1 |
20150263946 | Tubaltsev et al. | Sep 2015 | A1 |
20150264135 | Kandula et al. | Sep 2015 | A1 |
20150312274 | Bishop et al. | Oct 2015 | A1 |
20150312326 | Archer et al. | Oct 2015 | A1 |
20150326467 | Fullbright et al. | Nov 2015 | A1 |
20150381494 | Cherian et al. | Dec 2015 | A1 |
20160057014 | Thakkar et al. | Feb 2016 | A1 |
20160094396 | Chandrashekhar et al. | Mar 2016 | A1 |
20160094661 | Jain et al. | Mar 2016 | A1 |
20160134528 | Lin et al. | May 2016 | A1 |
20160173338 | Wolting | Jun 2016 | A1 |
20160191374 | Singh et al. | Jun 2016 | A1 |
20160210209 | Verkaik et al. | Jul 2016 | A1 |
20160226700 | Zhang et al. | Aug 2016 | A1 |
20160226762 | Zhang et al. | Aug 2016 | A1 |
20160226822 | Zhang et al. | Aug 2016 | A1 |
20160226959 | Zhang et al. | Aug 2016 | A1 |
20160226967 | Zhang et al. | Aug 2016 | A1 |
20160277289 | Madabushi et al. | Sep 2016 | A1 |
20160352588 | Subbarayan et al. | Dec 2016 | A1 |
20160359705 | Parandehgheibi et al. | Dec 2016 | A1 |
20160373530 | Duda | Dec 2016 | A1 |
20160380815 | Agarwal et al. | Dec 2016 | A1 |
20160380891 | Agarwal et al. | Dec 2016 | A1 |
20160380925 | Agarwal et al. | Dec 2016 | A1 |
20160380973 | Sullenberger et al. | Dec 2016 | A1 |
20170005988 | Bansal et al. | Jan 2017 | A1 |
20170034052 | Chanda et al. | Feb 2017 | A1 |
20170034129 | Sawant et al. | Feb 2017 | A1 |
20170041347 | Nagaratnam et al. | Feb 2017 | A1 |
20170048110 | Wu et al. | Feb 2017 | A1 |
20170048130 | Goliya et al. | Feb 2017 | A1 |
20170063633 | Goliya et al. | Mar 2017 | A1 |
20170063794 | Jain et al. | Mar 2017 | A1 |
20170063822 | Jain et al. | Mar 2017 | A1 |
20170093617 | Chanda et al. | Mar 2017 | A1 |
20170093636 | Chanda et al. | Mar 2017 | A1 |
20170104720 | Bansal et al. | Apr 2017 | A1 |
20170126431 | Han et al. | May 2017 | A1 |
20170126497 | Dubey et al. | May 2017 | A1 |
20170126551 | Pfaff et al. | May 2017 | A1 |
20170163442 | Shen et al. | Jun 2017 | A1 |
20170163532 | Tubaltsev et al. | Jun 2017 | A1 |
20170163598 | Shen et al. | Jun 2017 | A1 |
20170163599 | Shen et al. | Jun 2017 | A1 |
20170171055 | Wang et al. | Jun 2017 | A1 |
20170222873 | Lee et al. | Aug 2017 | A1 |
20170249195 | Sadana et al. | Aug 2017 | A1 |
20170250912 | Chu et al. | Aug 2017 | A1 |
20170264483 | Lambeth et al. | Sep 2017 | A1 |
20170288981 | Hong et al. | Oct 2017 | A1 |
20170289033 | Singh et al. | Oct 2017 | A1 |
20170302531 | Maes | Oct 2017 | A1 |
20170310641 | Jiang et al. | Oct 2017 | A1 |
20170317954 | Masurekar et al. | Nov 2017 | A1 |
20170317969 | Masurekar et al. | Nov 2017 | A1 |
20170317971 | Dubey et al. | Nov 2017 | A1 |
20170318113 | Ganichev et al. | Nov 2017 | A1 |
20170324645 | Johnsen et al. | Nov 2017 | A1 |
20170331711 | Duda | Nov 2017 | A1 |
20170344444 | Costa-Roberts et al. | Nov 2017 | A1 |
20180007004 | Basler | Jan 2018 | A1 |
20180062880 | Yu et al. | Mar 2018 | A1 |
20180062881 | Chandrashekhar et al. | Mar 2018 | A1 |
20180062923 | Katrekar et al. | Mar 2018 | A1 |
20180062944 | Altman et al. | Mar 2018 | A1 |
20180063036 | Chandrashekhar et al. | Mar 2018 | A1 |
20180063195 | Nimmagadda et al. | Mar 2018 | A1 |
20180083835 | Cole et al. | Mar 2018 | A1 |
20180123877 | Saxena et al. | May 2018 | A1 |
20180123903 | Holla et al. | May 2018 | A1 |
20180157537 | Chen et al. | Jun 2018 | A1 |
20180191682 | Liu et al. | Jul 2018 | A1 |
20180234337 | Goliya et al. | Aug 2018 | A1 |
20180234459 | Kung et al. | Aug 2018 | A1 |
20180309718 | Zuo | Oct 2018 | A1 |
20180373961 | Wang et al. | Dec 2018 | A1 |
20190014040 | Yerrapureddy et al. | Jan 2019 | A1 |
20190069335 | Wu | Feb 2019 | A1 |
20190109669 | Zachman et al. | Apr 2019 | A1 |
20190158537 | Miriyala | May 2019 | A1 |
20190190780 | Wang et al. | Jun 2019 | A1 |
20190207847 | Agarwal et al. | Jul 2019 | A1 |
20190245888 | Martinez et al. | Aug 2019 | A1 |
20190260610 | Dubey et al. | Aug 2019 | A1 |
20190260630 | Stabile et al. | Aug 2019 | A1 |
20190297114 | Panchalingam et al. | Sep 2019 | A1 |
20190303326 | Desai et al. | Oct 2019 | A1 |
20190334765 | Jain et al. | Oct 2019 | A1 |
20190342175 | Wan et al. | Nov 2019 | A1 |
20190363975 | Djernaes | Nov 2019 | A1 |
20190379731 | Johnsen et al. | Dec 2019 | A1 |
20200007392 | Goyal | Jan 2020 | A1 |
20200007582 | Dixit et al. | Jan 2020 | A1 |
20200007584 | Dixit et al. | Jan 2020 | A1 |
20200014662 | Chanda et al. | Jan 2020 | A1 |
20200021541 | Chanda | Jan 2020 | A1 |
20200057669 | Hutcheson et al. | Feb 2020 | A1 |
20200076684 | Naveen et al. | Mar 2020 | A1 |
20200106744 | Miriyala et al. | Apr 2020 | A1 |
20200162325 | Desai et al. | May 2020 | A1 |
20200162337 | Jain et al. | May 2020 | A1 |
20200169496 | Goliya et al. | May 2020 | A1 |
20200169516 | Patel et al. | May 2020 | A1 |
20200195607 | Wang et al. | Jun 2020 | A1 |
20200257549 | Vlaznev et al. | Aug 2020 | A1 |
20200296035 | Agarwal et al. | Sep 2020 | A1 |
20200304427 | Sandler et al. | Sep 2020 | A1 |
20200358693 | Rawlins | Nov 2020 | A1 |
20200366741 | Kancherla et al. | Nov 2020 | A1 |
20200409563 | Parasnis et al. | Dec 2020 | A1 |
20210036889 | Jain et al. | Feb 2021 | A1 |
20210067556 | Tahan | Mar 2021 | A1 |
20210117217 | Croteau | Apr 2021 | A1 |
20210117908 | Coles et al. | Apr 2021 | A1 |
20210126641 | Yan et al. | Apr 2021 | A1 |
20210168197 | Jones et al. | Jun 2021 | A1 |
20210194729 | Semwal et al. | Jun 2021 | A1 |
20210216565 | Petschulat | Jul 2021 | A1 |
20210311764 | Rosoff | Oct 2021 | A1 |
20210311960 | Rogozinsky et al. | Oct 2021 | A1 |
20210314192 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314193 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314212 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314215 | Manzanilla et al. | Oct 2021 | A1 |
20210314219 | Gujar et al. | Oct 2021 | A1 |
20210314225 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314226 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314227 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314228 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314235 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314251 | Dubey et al. | Oct 2021 | A1 |
20210314256 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314257 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314258 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314289 | Chandrashekhar et al. | Oct 2021 | A1 |
20210314291 | Chandrashekhar et al. | Oct 2021 | A1 |
20210367834 | Palavalli et al. | Nov 2021 | A1 |
20220103429 | Vaidya et al. | Mar 2022 | A1 |
20220103430 | Vaidya et al. | Mar 2022 | A1 |
20220103514 | Vaidya et al. | Mar 2022 | A1 |
20220103521 | Vaidya et al. | Mar 2022 | A1 |
20220103598 | Vaidya et al. | Mar 2022 | A1 |
20220191126 | Dubey et al. | Jun 2022 | A1 |
20220255896 | Jain et al. | Aug 2022 | A1 |
Number | Date | Country |
---|---|---|
3119423 | Mar 2018 | CA |
102124456 | Jul 2011 | CN |
102986172 | Mar 2013 | CN |
103650433 | Mar 2014 | CN |
103890751 | Jun 2014 | CN |
110061899 | Jul 2019 | CN |
1154601 | Nov 2001 | EP |
1290856 | Mar 2003 | EP |
1635506 | Mar 2006 | EP |
1868318 | Dec 2007 | EP |
3016331 | May 2016 | EP |
3314831 | May 2018 | EP |
3485610 | May 2019 | EP |
2010028364 | Mar 2010 | WO |
2011140028 | Nov 2011 | WO |
2012113444 | Aug 2012 | WO |
2013026049 | Feb 2013 | WO |
2013152716 | Oct 2013 | WO |
2015054671 | Apr 2015 | WO |
2017003881 | Jan 2017 | WO |
2018044341 | Mar 2018 | WO |
2021206785 | Oct 2021 | WO |
2021206786 | Oct 2021 | WO |
2021206790 | Oct 2021 | WO |
2022066269 | Mar 2022 | WO |
Entry |
---|
Non-Published Commonly Owned U.S. Appl. No. 18/227,655 (G568.C2), filed Jul. 28, 2023, 133 pages, VMware, Inc. |
Non-Published Commonly Owned U.S. Appl. No. 18/243,435 (G551.C1), filed Sep. 7, 2023, 135 pages, VMware, Inc. |
Author Unknown, “What is a Data Center?,” Cyberpedia, Month Unknown 2022, 5 pages, Palo Alto Networks, retrieved from https://www.paloaltonetworks.com/cyberpedia/what-is-a-data-center. |
Author Unknown, “Apache Cassandra™ 1.2 Documentation,” Jan. 13, 2013, 201 pages, DataStax. |
Author Unknown, “OpenFlow Switch Specification, Version 1.1.0 Implemented (Wire Protocol 0x02),” Feb. 28, 2011, 56 pages, Open Networking Foundation. |
Berde, Pankaj, et al., “ONOS Open Network Operating System An Open-Source Distributed SDN OS,” Dec. 19, 2013, 34 pages. |
Giannakou, Anna, et al., “Al-Safe: A Secure Self-Adaptable Application-Level Firewall for laaS Clouds,” 2016 IEEE 8th International Conference on Cloud Computing Technology and Science, Dec. 12-15, 2016, 8 pages, IEEE, Luxembourg City, LU. |
Guo, Yingya, et al., “Traffic Engineering in SDN/OSPF Hybrid Network,” The 22nd IEEE International Conference on Network Protocols (ICNP 2014), Oct. 21-24, 2014, 6 pages, IEEE, The Research Triangle, North Carolina, USA. |
Hanna, Jeremy, “How ZooKeeper Handles Failure Scenarios,” http://.apache.org/hadoop/Zookeeper/FailureScenarios. Dec. 9, 2010, 1 page. |
Heller, Brandon, et al., “The Controller Placement Problem,” Hot Topics in Software Defined Networks, Aug. 13, 2012, 6 pages, Helsinki, Finland. |
Jin, Xin, et al., “Dynamic Scheduling of Network Updates,” SIGCOMM'14, Aug. 17-22, 2014, 12 pages, ACM, Chicago, IL, USA. |
Kohila, N., et al., “Data Security in Local Network Using Distributed Firewall,” International Journal of Scientific Research in Computer Science Applications and Management Studies, Nov. 2014, 8 pages, vol. 3, Issue 6, jsrcams.com. |
Krishnaswamy, Umesh, et al., “ONOS Open Network Operating System—An Experimental Open-Source Distributed SDN OS,” Apr. 16, 2013, 24 pages. |
Lebresne, Sylvain, “[Release] Apache Cassandra 1.2 released,” Jan. 2, 2013, 1 page. |
Loshin, Peter, et al., “What is a data center?,” Special Report: Everything You Need to Know About the Log4j Vulnerability, Oct. 2021, 13 pages, retrieved from https://searchdatacenter.techtarget.com/definition/data-center. |
Mahalingham, Mallik, et al., “VXLAN: A Framework for Overlaying Virtualized Layer 2 Networks over Layer 3 Networks,” draft-mahalingham-dutt-dcops-vxlan-00.txt Internet Draft, Aug. 26, 2011, 20 pages, Internet Engineering Task Force. |
Mahalingham, Mallik, et al., “VXLAN: A Framework for Overlaying Virtualized Layer 2 Networks over Layer 3 Networks,” draft-mahalingham-dutt-dcops-vxlan-02.txt Internet Draft, Aug. 22, 2012, 20 pages, Internet Engineering Task Force. |
Non-Published Commonly Owned Related U.S. Appl. No. 17/869,640 with similar specification, filed Jul. 20, 2022, 37 pages, VMware, Inc. |
PCT International Search Report and Written Opinion of Commonly Owned International Patent Application PCT/US2021/015967 (G543.01.WO), mailed May 18, 2021, 13 pages, International Searching Authority (EP). |
PCT International Search Report and Written Opinion of Commonly Owned International Patent Application PCT/US2021/015968 (G551.WO), mailed Apr. 23, 2021, 14 pages, International Searching Authority (EP). |
PCT International Search Report and Written Opinion of Commonly Owned International Patent Application PCT/US2021/016118 (G548.01.WO), mailed Apr. 15, 2021, 11 pages, International Searching Authority (EP). |
Schuba, Christoph, et al., “Integrated Network Service Processing Using Programmable Network Devices,” SMLI TR-2005-138, May 2005, 30 pages, Sun Microsystems, Inc. |
Surantha, Nico, et al., “Secure Kubernetes Networking Design Based on Zero Trust Model: A Case Study of Financial Service Enterprise in Indonesia,” Innovative Mobile and Internet Services in Ubiquitous Computing, Jan. 2020, 14 pages, Springer Nature, Switzerland. |
Wack, John, et al., “Guidelines on Firewalls and Firewall Policy,” Recommendations of the National Institute of Standards and Technology, Special Publication 800-41, Jan. 2002, 75 pages, NIST, Gaithersburg, MD, USA. |
Number | Date | Country | |
---|---|---|---|
20240031225 A1 | Jan 2024 | US |