Exploiting Spot and Burstable Instances for Improving the Cost-efficacy of In-Memory Caches on the Public Cloud.

In order to keep the costs of operating in-memory storage on the public cloud low, we devise novel ideas and enabling modeling and optimization techniques for combining conventional Amazon EC2 instances with the cheaper spot and burstable instances. Whereas a naturally appealing way of using failure-prone spot instances is to selectively store unpopular (\"cold\") content, we show that a form of \"hot-cold mixing\" across regular and spot instances might be more cost-effective. To overcome performance degradation resulting from spot instance revocations, we employ a highly available passive backup using the recently emergent burstable instances. We show how the idiosyncratic resource allocations of burstable instances make them ideal candidates for such a backup. We implement all our ideas in an EC2-based memcached prototype. Using simulations and live experiments on our prototype, we show that (i) our hot-cold mixing, informed by our modeling of spot prices, helps improve cost savings by 50-80% compared to only using regular instances, and (ii) our burstable-based backup helps reduce performance degradation during spot revocation, e.g., the 95% latency during failure recovery improves by 25% compared to a backup based on regular instances.