Performance Insulation: More Predictable Shared Storage

Carnegie Mellon University School of Computer Science Ph.D. Dissertation CMU-CS-11-134.
September 2011.

Matthew Wachs

School of Computer Science
Carnegie Mellon University
Pittsburgh, PA 15213


Many storage workloads do not need the performance afforded by a dedicated storage system, but do need the predictability and controllability that comes from one. Unfortunately, inter-workload interference, such as a reduction of locality when multiple request streams are interleaved, can result in dramatic loss of efficiency and performance.

Performance insulation is a system property where each workload sharing the system is assigned a fraction of resources (such as disk time) and receives nearly that fraction of its standalone (dedicated system) performance. Because there is usually some overhead caused by sharing, there could be a drop in efficiency; but a system providing performance insulation provides a bound on efficiency loss at all times, called the R-value. We have built a storage server called Argon that achieves performance insulation in practice for R-values of 0.8-0.9. This means that, running together with other workloads on Argon, workloads lose, at most, only 10-20% of the efficiency they receive on a dedicated system.

While performance insulation provides a useful limit on loss of efficiency, many storage workloads also need performance guarantees. To ensure performance guarantees are consistently met, the appropriate allocation of resources needs to be determined and reserved, and later reevaluated if the workload changes in behavior or if the interference between workloads affects their ability to use resources effectively. If the resources assigned to a workload need to be increased to maintain its guarantee, but adequate resources are not available, violations will result.

Though intrinsic workload variability is fundamental, storage systems with the property of performance insulation strictly limit inter-workload interference, another source of variability. Such interference is the major source of "artificial" complexity in maintaining performance guarantees. We design and evaluate a storage system called Cesium that limits interference and thus avoids the class of guarantee violations arising from it. Workloads running on Cesium only suffer from those violations caused by their own variability and not those due to the activities of other workloads. Realistic and challenging workloads may experience an order of magnitude fewer violations running under Cesium. Performance insulation thus results in more reliable and efficient bandwidth guarantees.

KEYWORDS: Storage systems, shared storage, clustered storage, efficiency, quality of service, performance isolation, performance insulation, bandwidth guarantees.





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