Resource overbooking and application profiling in shared hosting platforms

ABSTRACT

In this paper, we present techniques for provisioning CPU and network resources in shared hosting platforms running potentially antagonistic third-party applications. The primary contribution of our work is to demonstrate the feasibility and benefits of overbooking resources in shared platforms, to maximize the platform yield: the revenue generated by the available resources. We do this by first deriving an accurate estimate of application resource needs by profiling applications on dedicated nodes, and then using these profiles to guide the placement of application components onto shared nodes. By overbooking cluster resources in a controlled fashion, our platform can provide performance guarantees to applications even when overbooked, and combine these techniques with commonly used QoS resource allocation mechanisms to provide application isolation and performance guarantees at run-time. When compared to provisioning based on the worst-case, the efficiency (and consequently revenue) benefits from controlled overbooking of resources can be dramatic. Specifically, experiments on our Linux cluster implementation indicate that overbooking resources by as little as 1% can increase the utilization of the cluster by a factor of two, and a 5% overbooking yields a 300--500% improvement, while still providing useful resource guarantees to applications.

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INDEX TERMS

Primary Classification:
  D. Software
  D.4 OPERATING SYSTEMS
      D.4.7 Organization and Design
          Subjects: Distributed systems

Additional Classification:
  D. Software
  D.4 OPERATING SYSTEMS
      D.4.8 Performance
          Subjects: Operational analysis

  F. Theory of Computation
  F.2 ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY
      F.2.2 Nonnumerical Algorithms and Problems
          Subjects: Sequencing and scheduling

General Terms:
Algorithms, Design, Performance