Abstract: Some embodiments of the invention provide a method of deploying a tenant deployable element to one public cloud. The method identifies first and second candidate resource elements respectively of first and second resource element sub-types to deploy in a public cloud to implement the tenant deployable element. The method identifies, for the first and second candidate resource elements respectively first and second sets of performance metric values to evaluate. The method evaluates the identified first and second sets of metrics to select one candidate resource element to implement the tenant deployable element in the public cloud. The method uses the selected resource element to implement the tenant deployable element in the public cloud.

Abstract: Some embodiments provide a novel method for dynamically processing data message flows using different non-uniform memory access (NUMA) nodes of a processing system. Each NUMA node includes a memory and processors that can access data other memories of other NUMA nodes. A load balancing application associated with a first NUMA node receives flows destined for an endpoint application. The flows are assigned to the first NUMA node to be forwarded to the endpoint application. The load balancing application monitors a central processing (CPU) usage of the first NUMA node to determine whether the CPU usage of the first NUMA node exceeds a particular threshold. When the CPU usage of the first NUMA node exceeds the particular threshold, the load balancing application reassigns at least a subset of the flows to the second NUMA node for processing.

Abstract: Some embodiments provide a novel method for processing data message flows using several non-uniform memory access (NUMA) nodes of a processing system. Each NUMA node includes a local memory and a set of processors that can access data from local memories of other NUMA nodes. A load balancing application associated with a first NUMA node receives a data message flow destined for an endpoint application. The load balancing application determines whether the first NUMA node should perform a middlebox service operation on the data message flow that is destined to the endpoint application. Based on a determination that the first NUMA node should not process the data message flow, the load balancing application directs the data message flow to a second NUMA node for performing the middlebox service operation.

Abstract: Some embodiments of the invention provide a method of deploying first and second tenant deployable elements to a set of one or more public clouds, the first and second tenant deployable elements being different types of elements. The method identifies first and second sets of performance metrics respectively for first and second sets of candidate resource elements to use to deploy the first and second tenant deployable elements, the two sets of performance metrics being different sets of metrics because the first and second tenant deployable elements being different types of elements, the first set of performance metrics having at least one metric that is not included in the second set of performance metrics.

Abstract: Some embodiments of the invention provide a method for evaluating multiple candidate resource elements associated with different resource element types for deploying one tenant deployable element in a single public cloud. The method deploys a set of one or more agents in the public cloud to collect metrics evaluating performance of each of the multiple candidate resource elements. The method communicates with the set of deployed agents to collect metrics to quantify performance of each candidate resource element. The method aggregates the collected metrics in order to generate a report that quantifies performance of each type of candidate resource element for deploying the tenant deployable element in the single public cloud.

Abstract: Some embodiments of the invention provide a method of deploying a tenant deployable element to one public cloud. The method identifies first and second candidate resource elements respectively of first and second resource element sub-types to deploy in a public cloud to implement the tenant deployable element. The method identifies, for the first and second candidate resource elements respectively first and second sets of performance metric values to evaluate. The method evaluates the identified first and second sets of metrics to select one candidate resource element to implement the tenant deployable element in the public cloud. The method uses the selected resource element to implement the tenant deployable element in the public cloud.

Abstract: Some embodiments of the invention provide a method of deploying first and second tenant deployable elements to a set of one or more public clouds, the first and second tenant deployable elements being different types of elements. The method identifies first and second sets of performance metrics respectively for first and second sets of candidate resource elements to use to deploy the first and second tenant deployable elements, the two sets of performance metrics being different sets of metrics because the first and second tenant deployable elements being different types of elements, the first set of performance metrics having at least one metric that is not included in the second set of performance metrics.

Abstract: Some embodiments of the invention provide a method for evaluating multiple candidate resource elements that are candidates for deploying a set of one or more tenant deployable elements in a public cloud. For each particular tenant deployable element, the method deploys in the public cloud at least one instance of each of a set of one or more candidate resource elements and at least one agent to execute on the deployed resource element instance. The method communicates with each deployed agent to collect metrics for quantifying performance of the agent's respective resource element instance. The method then aggregates the collected metrics in order to generate a report that quantifies performance of each candidate resource element in the set of candidate resource elements for deploying the particular tenant deployable element in the public cloud.

Abstract: Some embodiments of the invention provide a method of adjusting deployment of a set of resource elements in a public cloud. The method deploys agents on a first set of resource elements in the public cloud. The method communicates with the deployed agents to generate performance metrics regarding the first set of resource elements. The method analyzes the performance metrics to determine that a deployment of a second set of resource elements in the public cloud has to be modified. The method modifies the deployment of the second set of resource elements based on the analysis.

Abstract: Some embodiments provide a method for generating a test traffic configuration for testing a first network. From a second network, the method receives a set of data streams representing data traffic observed in the second network. The method uses a machine learning engine to analyze the set of data streams in order to determine traffic patterns in the second network. The method generates the test traffic configuration for testing the first network by replicating the traffic patterns of the second network in the first network.

Abstract: Some embodiments of the invention provide a method of deploying tenant deployable elements on resource elements in public cloud datacenters. The method receives a request to deploy a particular tenant deployable element in one of a first public cloud datacenter (PCD) and a second PCD, the first public cloud datacenter belonging to a first cloud service provider (CSP) and the second public cloud datacenter belonging to a second CSP. For each candidate resource element in the first PCD, the method identifies a first set of performance metrics associated with the candidate resource element. For each candidate resource element in the second PCD, the method identifies a second set of performance metrics associated with the candidate resource element. The method evaluates the identified first and second sets of metrics to select a resource element to implement the particular tenant deployable element in one of the first and second PCDs.

Abstract: Some embodiments provide a method for generating a test traffic configuration for testing a first network. From a second network, the method receives a set of data streams representing data traffic observed in the second network. The method uses a machine learning engine to analyze the set of data streams in order to determine traffic patterns in the second network. The method generates the test traffic configuration for testing the first network by replicating the traffic patterns of the second network in the first network.

Abstract: Some embodiments provide a method for generating a test traffic configuration for testing a first network. From a second network, the method receives a set of data streams representing data traffic observed in the second network. The method uses a machine learning engine to analyze the set of data streams in order to determine traffic patterns in the second network. The method generates the test traffic configuration for testing the first network by replicating the traffic patterns of the second network in the first network.