Warming Up Storage-Level Caches with Bonfire
Yiying Zhang, University of Wisconsin—Madison; Gokul Soundararajan, Mark W. Storer, Lakshmi N. Bairavasundaram, and Sethuraman Subbiah, NetApp; Andrea C. Arpaci-Dusseau and Remzi H. Arpaci-Dusseau, University of Wisconsin—Madison
Large caches in storage servers have become essential for meeting service levels required by applications. These caches need to be warmed with data often today due to various scenarios including dynamic creation of cache space and server restarts that clear cache contents. When large storage caches are warmed at the rate of application I/O, warmup can take hours or even days, thus affecting both application performance and server load over a long period of time.
We have created Bonfire, a mechanism for accelerating cache warmup. Bonfire monitors storage server workloads, logs important warmup data, and efficiently preloads storage-level caches with warmup data. Bonfire is based on our detailed analysis of block-level data-center traces that provides insights into heuristics for warmup as well as the potential for efficient mechanisms. We show through both simulation and trace replay that Bonfire reduces both warmup time and backend server load significantly, compared to a cache that is warmed up on demand.
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