Elastic Provisioning of Cloud Caches: a Cost-aware TTL Approach

TL;DR

This paper presents a cost-aware, dynamic TTL cache provisioning algorithm for cloud in-memory caches, reducing overall costs by approximately 17% based on real-world Akamai data.

Contribution

It introduces a novel, low-complexity, dynamic TTL caching algorithm that adapts to traffic patterns to minimize total costs including storage and miss penalties.

Findings

Achieved 17% cost reduction over static configurations.

Demonstrated practical implementation with constant overhead per request.

Validated effectiveness using real-world Akamai traces.

Abstract

We consider elastic resource provisioning in the cloud, focusing on in-memory key-value stores used as caches. Our goal is to dynamically scale resources to the traffic pattern minimizing the overall cost, which includes not only the storage cost, but also the cost due to misses. In fact, a small variation on the cache miss ratio may have a significant impact on user perceived performance in modern web services, which in turn has an impact on the overall revenues for the content provider that uses those services. We propose and study a dynamic algorithm for TTL caches, which is able to obtain close-to-minimal costs. Since high-throughput caches require low complexity operations, we discuss a practical implementation of such a scheme requiring constant overhead per request independently from the cache size. We evaluate our solution with real-world traces collected from Akamai, and show that we are able to obtain a 17% decrease in the overall cost compared to a baseline static configuration.