Vmware, Inc.

Siddharth Ekbote

Todd Sabin

Weiqing Wu

Leon Cui

Liang Cui

Serge Maskalik

Uday Suresh Masurekar

Derek William Beard

Arunachalam Ramanathan

Yanlei Zhao

Pavan Narasimhaprasad

Chung-Shang Shao

Jesse Schachter

Techniques for implementing data plane isolation for VM mobility operations are provided. In one set of embodiments, these techniques include creating a virtual network path between a source host system and a destination host system participating in a VM mobility operation, which allows the host systems to exchange data for carrying out the operation without exposing their physical IP addresses to each other and without requiring the use of intermediate proxies. In certain embodiments, the virtual network path can be dynamically established upon initiation of the VM mobility operation and dynamically rolled back upon operation completion, thereby reducing the overhead of virtual path management.

Data plane isolation for virtual machine (VM) mobility operations

Mac learning for cross-site layer-2 connectivity. Some embodiments provide a method for enabling data traffic to be sent between across which a logical network spans. A logical network segment (i.e., a layer-2 network segment such as a logical switch) spans at least two sites via tunnels between network elements deployed in the sites that operate as bridges (or 2-port switches) to pass data traffic between the sites without leaving the logical network segment. Because these network elements operate similarly to bridges, they are not assigned network (layer 3) addresses (e.g., IP addresses). In order to send address resolution protocol (ARP) requests to a router in one site, the network element in another site uses a network address of one of the data compute nodes (DCNs) operating in its site that is connected to the logical network segment spanning the two sites.

MAC learning for cross-site layer-2 connectivity

The disclosure provides an approach for selecting a path to use in transferring a virtual computing instance such as a virtual machine (VM), across data centers. In one embodiment, throughput and throttling information are sampled (e.g., per second) when VMs are transferred from a source data center to a destination data center, and the sampled information is used to construct histograms that provide performance profiles of the VM transfers. Such histogram information across a number of VM transfers can then be mined to determine trends. In turn, trends determined from historical histogram information may be extrapolated into the future to predict performance of a subsequent VM transfer operation and to select a path and/or destination storage and host pair to use for the VM transfer operation.

Virtual computing instance transfer path selection

The disclosure provides an approach for diagnosing a data plane of a network, wherein the network spans a first data center and a second data center, and wherein the second data center is remote to the first, the method comprising: accessing a secure connection between the first data center and the second data center; modifying, by the first performance controller, firewall settings of the first data center from a first setting to a second setting; opening on the second data center an instance of a performance tool; opening on the first data center a client of the instance of the performance tool; sending data packets over the data plane of the network; receiving the data packets; generating metrics associated with the data packets; and modifying firewall settings of the first data center from the second setting to the first setting.

Method of diagnosing data delivery over a network between data centers

The disclosure provides an approach for preventing the failure of virtual computing instance transfers across data centers. In one embodiment, a flow control module collects performance information primarily from components in a local site, as opposed to components in a remote site, during the transfer of a virtual machine (VM) from the local site to the remote site. The performance information that is collected may include various performance metrics, each of which is considered a feature. The flow control module performs feature preparation by normalizing feature data and imputing missing feature data, if any. The flow control module then inputs the prepared feature data into machine learning model(s) which have been trained to predict whether a VM transfer will succeed or fail, given the input feature data. If the prediction is that the VM transfer will fail, then remediation actions may be taken, such as slowing down the VM transfer.

Machine learning prediction of virtual computing instance transfer performance

A method of transferring data between local and remote computing systems includes the step of transferring data between the local and remote computing systems via a local buffer in the local computing system and a series of steps carried out during transferring of data from the local to the remote computing system. The steps include receiving a statistic from the remote computing system, computing an average transfer rate of the data transfer between the local and remote computing systems based on the statistic, determining whether or not a throttle condition is in effect based on the computed average transfer rate, and upon determining that the throttle condition is in effect, throttling the transferring of data into the local buffer.

Dynamic flow control for transferring data efficiently and effectively over non-linear buffered network paths

The disclosure provides an approach for managing and diagnosing middleboxes in a cloud computing system. In one embodiment, a network operations center, that is located remote to a virtualized cloud computing system and communicates with the cloud computing system via a wide area network, controls network middleboxes in the cloud computing system through a secure routing module inside a gateway of the cloud computing system. The secure routing module is configured to receive, from an authenticated management application and via a secure communication channel, packets intended for managing network middleboxes. In turn, the secure routing module establishes secure communication channels with the target middleboxes, translates the identified packets to protocols and/or application programming interfaces (APIs) of the target middleboxes, and transmits the translated packets to the target middleboxes.

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San Jose, CA, United States of America

Siddharth Ekbote