Caching Authentication Data

I'm currently implementing a REST web service using CouchDB and RESTlet. The RESTlet layer is mainly for authentication and some minor filtering of the JSON data served by CouchDB:

Clients <= HTTP => [ RESTlet <= HTTP => CouchDB ]

I'm using CouchDB also to store user login data, because I don't want to add an additional database server for that purpose. Thus, each request to my service causes two CouchDB requests conducted by RESTlet (a开发者_Python百科uth data + "real" request). In order to keep the service as efficent as possible, I want to reduce the number of requests, in this case redundant requests for login data.

My idea now is to provide a cache (i.e.LRU-Cache via LinkedHashMap) within my RESTlet application that caches login data, because HTTP caching will probabily not be enough. But how do I invalidate the cache data, once a user changes the password, for instance. Thanks to REST, the application might run on several servers in parallel, and I don't want to create a central instance just to cache login data.

Currently, I save requested auth data in the cache and try to auth new requests by using them. If a authentication fails or there is now entry available, I'll dispatch a GET request to my CouchDB storage in order to obtain the actual auth data. So in a worst case, users that have changed their data will perhaps still be able to login with their old credentials. How can I deal with that?

Or what is a good strategy to keep the cache(s) up-to-date in general?

Thanks in advance.

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To me it looks like you've grown up far enough to use some "professional" cache solution (e.g. EHCache). All distributed caches allow new data replication & invalidation among different nodes so your problem is already solved.

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A distributed in-memory cache like memcached might be what you are looking for. You can configure object age, cache size and also expose callbacks to remove specific objects from the cache (like when the information is stale).