Vmware, Inc.

Sai Inabattini

Adarsh Jagadeeshwaran

Fei Guo

Maarten Wiggers

Kalyan Saladi

Sabareesh Subramaniam

Sankaran Sivathanu

Priyanka Gayam

System and computer-implemented method for managing workload volatility in a cloud architecture including a plurality of computing instances in a group of hosts use volatiltiy factors to identify first and second hosts and then a first virtual computing instance in the first host. A workload metric associated with the group of hosts is used to identify a second virtual computing instance in the second host to be swapped with the first virtual computing instance in the first host. The first and second virtual computing instances are swapped so that the first virtual computing instance is migrated from the first host to the second host and the second virtual computing instance is migrated from the second host to the first host.

Method and apparatus for workload volatility management in cloud computing

A system and method for automatically consolidating clusters of host computers in a distributed computer system uses a digital representation of a simulated merged cluster of host computers to produce resource management analysis results on the simulated merged cluster of host computers. The simulated merged cluster of host computers is a simulation of a consolidation of first and second clusters of host computers. In addition, the system and method involves executing an automatic consolidation operation on the first and second clusters of host computers to generate a merged cluster of host computers that includes the host computers from both the first and second clusters.

Automatic cluster consolidation for efficient resource management

Techniques for representative-based approach to store historical resource usage data are disclosed. In one embodiment, a management node may include a statistical representative computational unit to obtain historical resource usage data associated with a workload running on a host, divide the historical resource usage data into a plurality of pools with each pool comprising a predefined number of resource usage statistics, and determine a statistical representative corresponding to each of the pools. Each statistical representative may represent the predefined number of resource usage statistics in a corresponding one of the pools. Further, the management node may include a monitoring and managing unit to monitor and/or manage the workload using the statistical representatives.

Representative-based approach to store historical resource usage data

Exemplary methods, apparatuses, and systems receive from a client a request to access data from a client. Whether metadata for the data is stored in a first caching layer is determined. In response to the metadata for the data not being stored in the first caching layer, it is determined if the data is stored in the second caching layer. In response to determining that the data is stored in the second caching layer, the data is retrieved from the second caching layer. In response to determining that the data is not stored in the second caching layer, writing of the data to the second caching layer is bypassed. The retrieved data is sent to the client.

Caching using an admission control cache layer

A management server and method for load balancing a cluster of host computers analyzes load metrics of clients naming on the host computers in the cluster to select a first client that can be migrated from a first host computer in the cluster to a second host computer in the cluster to improve load balance for the cluster and a second client running on the second host computer that can be swapped with the first client running on the first host computer for a client swapping operation. The client swapping operation involves simultaneously migrating the first client from the first host computer to the second host computer and migrating the second client from the second host computer to the first host computer.

Growing community of inventors

Bengaluru, India

Sai Inabattini