Nicira, Inc.

Vmware, Inc.

Somik Behera

Henry Mai

Donghai Han

Jianjun Shen

Justin Pettit

Samuel P McBride

Some embodiments provide a system that implements a set of tools to define a set of one or more logical forwarding elements from a number of physical forwarding elements and a scalable framework to retrieve statistics relating each logical forwarding element. In some embodiments, the statistics relate to the logical ports of a logical forwarding element. The system of some embodiments allows a network administrator to retrieve a total packet count and byte count for one or more logical ports of the logical forwarding element, even though the logical ports may be distributed across multiple physical forwarding elements.

System for aggregating statistics relating to a logical forwarding element

Some embodiments provide a local network controller that manages a first managed forwarding element (MFE) operating to forward traffic on a host machine for several logical networks and configures the first MFE to forward traffic for a set of containers operating within a container virtual machine (VM) that connects to the first MFE. The local network controller receives, from a centralized network controller, logical network configuration information for a logical network to which the set of containers logically connect. The local network controller receives, from the container VM, a mapping of a tag value used by a second MFE operating on the container VM to a logical forwarding element of the logical network to which the set of containers connect. The local network controller configures the first MFE to apply the logical network configuration information to data messages received from the container VM that are tagged with the tag value.

Logical processing for containers

A method includes determining a capacity model that configures computing resource capacity for a capacity container. The method also includes estimating an available capacity in a capacity container based on a capacity of host devices in the capacity container. The method also includes generating, based on a selection of a visualization method, a visualization of a trend curve and a forecast curve, the trend curve representing historical capacity usage of the host devices. Implementations may include selecting an average virtual machine unit display or a raw units display and determining an average virtual machine based on averaging an attribute of one or more virtual machines.

Capacity and load analysis using storage attributes

Some embodiments provide a statistics collection framework that is used to aggregate statistic for interfaces such as logical ports and logical port pairs. Flows that are related with these interfaces are tagged with the identifier of the logical entities for which statistics are being collected. The interface statistics is periodically sent in the background to a statistics aggregator. The read queries for the interface statistics are directed to the statistics aggregator. The statistics aggregator, therefore, acts as a cumulative cache for the interface statistics.

System for aggregating statistics associated with interfaces

A method includes determining a capacity model that configures computing resource capacity for a capacity container. The computing resource capacity includes a first storage attribute for an amount of storage in a storage component. A load model is determined that configures load for the capacity container. The load includes a second storage attribute for a storage requirement for a virtual machine. A profile of a virtual machine unit is determined for estimating available capacity in a capacity container. The profile is determined using virtual machine attributes for a set of virtual machines, wherein the virtual machine unit includes a storage requirement based on storage requirements for the set of virtual machines. The profile of the virtual machine unit is fit into available capacity. A number of virtual machine units is determined based on the fitting, the number of virtual machine units being a measure of available capacity.

Some embodiments provide a scalable framework to retrieve statistics relating different aggregated entities. In some embodiments, the aggregated entity is a pair of ports. The pair of ports can be physical ports of one or more physical forwarding elements. The pair of ports can be logical ports of one or more logical forwarding elements. In some embodiments, the aggregated entity is a machine or a group of machines. In some embodiments, the aggregated entity is an access control list (ACL).

Network virtualization operations using a scalable statistics collection framework

Some embodiments provide a method for a first managed forwarding element (MFE). The method receives a data message that includes a logical context tag that identifies a logical port of a particular logical forwarding element. Based on the logical context tag, the method adds a local tag to the data message. The local tag is associated with the particular logical forwarding element, which is one of several logical forwarding elements to which one or more containers operating on a container virtual machine (VM) belong. The container VM connects to the first MFE. The method delivers the data message to the container VM without any logical context. A second MFE operating on the container VM uses the local tag to forward the data message to a correct container of several containers operating on the container VM.

One or more embodiments provide methods of creating datacenter capacity and/or load models for a datacenter in a virtualized environment; methods of simulating the capacity and/or load models ('What-if' simulations); and methods of visualizing simulation results for assessing the impact of the capacity and/or load models on the datacenter capacity.

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San Francisco, CA, United States of America

Somik Behera