Research Blog: Google Cluster Data

Google Cluster Data

Thursday, January 07, 2010

Posted by Joseph L. Hellerstein, Manager of Google Performance Analytics

Workload characterizations: How can we characterize Google workloads in a way that readily generates synthetic work that is representative of production workloads so that we can run stand alone benchmarks?

Predictive models of workload characteristics: What is normal and what is abnormal workload? Are there "signals" that can indicate problems in a time-frame that is possible for automated and/or manual responses?

New algorithms for machine assignment: How can we assign tasks to machines so that we make best use of machine resources, avoid excess resource contention on machines, and manage power efficiently?

Scalable management of cell work: How should we design the future cell management system to efficiently visualize work in cells, to aid in problem determination, and to provide automation of management tasks?