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Optimizing VM Interference and Placement Strategies for Effective Server Consolidation

This study focuses on enhancing application performance in virtualized environments by addressing VM interference and placement strategies. It aims to translate application Quality of Service (QoS) into optimal VM configurations while quantifying the effects of interference and affinity between VMs. Key challenges include automating application performance characterization and effectively predicting performance in the presence of varying workloads. The output includes a set of VM configurations and a mapping of application components to VMs, ultimately optimizing resource utilization in data centers.

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Optimizing VM Interference and Placement Strategies for Effective Server Consolidation

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  1. VM Interference and Placement for Server Consolidation Umesh Bellur IIT Bombay

  2. Current Deployment App Lifecycle in a VM Env.

  3. Some Problems • Translating application QoS into VM configurations • Quantifying the effects of interference and affinity • Placement strategies

  4. Generating VM Configs • Input: • Application performance characterization leading to: • Building and solving predictive performance models for the application • QoS operating ranges and estimated load patterns • Output: • A set of VM configurations along with a mapping of application components to VMs.

  5. Challenges: • Automating characterizing appl perf. For virtualized env. • Extending standard performance prediction techniques (Queuing) to include the effects of virtualization

  6. Interference/Affinity • VMs don’t provide performance isolation • VMM takes up some percentage of resources. • Given an application component’s performance on a single VM, can we estimate the effect the colocating other VMs running different types of workloads (CPU intensive, I/O intensive etc.). Further, can we characterize this effect with changing parameters of the interfering component?

  7. Results of interference

  8. Results - 2 • Ping latency of a VM doubled when when it was deployed with a mixture of CPU-intensive and I/O bandwidth intensive VMs, as compared to when it was deployed with only I/O bandwidth intensive VMs.

  9. VM Placement • Given a current deployment and the set of VMs that need to be deployed in a data center, output a plan of placing the VMs on the existing physical machines to optimize number of physical servers used and other application specified constraints (for fault tolerance etc.) • Migration costs • A multi dimensional bin packing problem subject to various constraints: • Interference conflicts • App driven conflicts

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