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AutoScale: Dynamic, Robust Capacity Management for Multi-Tier Data Centers

Published:01 November 2012Publication History
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Abstract

Energy costs for data centers continue to rise, already exceeding $15 billion yearly. Sadly much of this power is wasted. Servers are only busy 10--30% of the time on average, but they are often left on, while idle, utilizing 60% or more of peak power when in the idle state.

We introduce a dynamic capacity management policy, AutoScale, that greatly reduces the number of servers needed in data centers driven by unpredictable, time-varying load, while meeting response time SLAs. AutoScale scales the data center capacity, adding or removing servers as needed. AutoScale has two key features: (i) it autonomically maintains just the right amount of spare capacity to handle bursts in the request rate; and (ii) it is robust not just to changes in the request rate of real-world traces, but also request size and server efficiency.

We evaluate our dynamic capacity management approach via implementation on a 38-server multi-tier data center, serving a web site of the type seen in Facebook or Amazon, with a key-value store workload. We demonstrate that AutoScale vastly improves upon existing dynamic capacity management policies with respect to meeting SLAs and robustness.

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          • Published in

            cover image ACM Transactions on Computer Systems
            ACM Transactions on Computer Systems  Volume 30, Issue 4
            November 2012
            136 pages
            ISSN:0734-2071
            EISSN:1557-7333
            DOI:10.1145/2382553
            Issue’s Table of Contents

            Copyright © 2012 ACM

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 1 November 2012
            • Accepted: 1 September 2012
            • Revised: 1 August 2012
            • Received: 1 April 2012
            Published in tocs Volume 30, Issue 4

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