Runtime Measurements in the Cloud: Observing, Analyzing, and Reducing Variance

One of the main reasons why cloud computing has gained so much popularity is due to its ease of use and its ability to scale computing resources on demand. As a result, users can now rent computing nodes on large commercial clusters through several vendors, such as Amazon and rackspace. However, despite the attention paid by Cloud providers, performance unpredictability is a major issue in Cloud computing for (1) database researchers performing wall clock experiments, and (2) database applications providing servicelevel agreements. In this paper, we carry out a study of the performance variance of the most widely used Cloud infrastructure (Amazon EC2) from different perspectives. We use established microbenchmarks to measure performance variance in CPU, I/O, and network. And, we use a multi-node MapReduce application to quantify the impact on real dataintensive applications. We collected data for an entire month and compare it with the results obtained on a local cluster. Our results...

• Type: Journal
• Year: 2010
• Where: PVLDB
• Authors: Jörg Schad, Jens Dittrich, Jorge-Arnulfo Quiané-Ruiz
• Keywords: Cloud, Performance, Performance Variance, PVLDB 2010