EAGER: Elastic Multi-layer Memcached Tiers

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Facebook and YouTube have massive databases containing many objects.Objects (e.g., pictures, videos) are read from these databases and presentedto users. These databases use slower and cheaper I/O devices. Repeateddatabase queries are also slow, so companies cache popular objects involatile memory (RAM). As RAM is about 1000x faster than I/O, queries topopular objects are serviced faster. A single computer cannot efficientlyuse too much RAM, so a distributed memory caching system called "Memcached"is utilized. Memcached creates a cluster of nodes, forming a key-valuedatabase in faster memory.Memcached's simple architecture led to its popularity, but is also itsAchilles' heel. When loads increase, more caching nodes are needed, but itis difficult to add new nodes and redistribute the cached data to morenodes. Similarly, when loads reduce, it is harder to shut down some nodesand migrate their cached data to fewer nodes; scaling down the cluster helpsreduce the large energy costs they consume. Any changes to the number ofMemcached nodes result in throwing out most cached data, leading to lengthyperiods where the distributed caches have to be slowly re-warmed up from thebackend database.This EArly-concept Grants for Exploratory Research (EAGER) project investigates techniques to scale Memcached clusterssmoothly, without any transient performance degradations. The project alsointroduces an intermediate Flash-based storage tier between the memory nodesand the backend database, to help reduce high latencies to the backenddatabase and help the smooth scaling of the Memcached cluster.