Vmware, Inc.

Chirag Bhatt

Ganesha Shanmuganathan

Anne Holler

Irfan Ahmad

Chengwei Wang

Canturk Isci

Aalap Desai

A technique for managing distributed computing resources in a virtual computing environment is disclosed. In an embodiment, a method includes receiving a recommended change to a virtual architecture of a virtual computing environment; determining an impact on current workload in the virtual computing environment if the recommended change is performed; determining an impact on future workload in the virtual computing environment if the recommended change is performed; calculating a combined impact on current and future workload; determining if the combined impact is above or below a threshold; if the combined impact on current and future workload is below the threshold, do not perform the recommended change; and if the combined impact on current and future workload is above the threshold, perform the recommended change.

System and method for managing a virtualized computing environment

Methods and systems for allocating resources in a virtual desktop resource environment are provided. A method includes making a prediction on the future demand for processes running on a distributed environment with several hosts. The prediction is based on the process demand history and includes the removal of historic process demand glitches. Further, the prediction is used to perform a cost and benefit analysis for moving a candidate process from one host to another, and the candidate process is moved to a different host when the cost and benefit analysis recommends such move. In another embodiment, the predictions on future process demand are used for distributed power management by putting hosts in stand-by mode when the overall demand decreases or by adding hosts to the distributed environment when the load increases.

Process demand prediction for distributed power and resource management

A technique for predictive distributed resource scheduling and distributed power management includes analyzing patterns in the workload, predicting future workloads, and making recommendations for changes to the virtual computing environment. In addition, a cost-benefit analysis can be performed to determine whether the recommended change would likely result in improved performance.

Embodiments perform adaptive throttling of tasks into a virtual datacenter having dynamically changing resources. Tasks are processed concurrently in batches. The rate of change in throughput at different batch sizes is calculated. With each iteration, the batch size is increased or decreased based on the rate of change to achieve a maximum throughput for given resources and load on the virtual datacenter.

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Sunnyvale, CA, United States of America

Chirag Bhatt