Thursday, December 26, 2013

Best Practices for App Engine Memcache

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This article outlines some best practices for using the Google App Engine Memcache feature. The main issues discussed are concurrency, performance, and migration. Developers using Memcache will benefit by becoming aware of pitfalls and considerations for making code more robust.

Memcache is an App Engine feature that provides in-memory, temporary storage. It is provided primarily as a cache for rapid retrieval of data that is backed by some form of persistent storage, such as Google Cloud Datastore. Ideal use cases for Memcache include caching published data like blogs, news feeds, and other content that is read but not modified. Data stored in Memcache can be evicted at any time, so applications should be structured in a way that does not depend on the presence of entries. Memcache can serve concurrent requests to multiple, remote clients accessing the same data. For this reason, data consistency should be kept in mind. Memcache statistics, including hit rate, are shown on the App Engine console, and can aid in optimizing performance.

There are two classes of Memcache service, shared and dedicated. Shared Memcache is a no-cost, best-effort service, and data stored with this service can be evicted at any time. Dedicated Memcache is a paid service that enables you to reserve memory for an application. This provides developers with a more predictable level of service. However, data may still be evicted if more data needs to be stored than space reserved in Memcache, since keys are evicted when the cache is full. In addition, data may be evicted if the Memcache service is restarted for planned or unplanned maintenance. The API signatures and usage are identical for both shared and dedicated Memcache. The difference in use is a configuration change in the App Engine Administration Console. Dedicated Memcache allows for a specific quantity of memory to be allocated for the application.

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