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Scaling Web Applications using Cache Farms and Read Pools

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Michael Nygard, author and No Fluff Just Stuff speaker, recently wrote on two alternative approaches to scaling web application performance and scalability: Cache Farms and Read Pools.

The idea behind Cache Farms is that application nodes in a cluster share an external cache instead of each maintaining their own. This eliminates redundancy and gives back heap space to the application server:

By moving the cache out of the app server process, you can access the same cache from multiple instances, reducing duplication. Getting those objects out of the heap, You can make the app server heap smaller, which will also reduce garbage collection pauses. If you make the cache distributed, as well as external, then you can reduce duplication even further.

Read Pools take advantage of the fact that most data driven applications perform many more read operations than writes. By having the reads performed against a dedicated set of read only replicated databases, you can relieve the burden on the write operation databases:

How do you create a read pool? Good news! It uses nothing more than built-in replication features of the database itself. Basically, you just configure the write master to ship its archive logs (or whatever your DB calls them) to the read pool databases.

Michael points out that updating the read hosts may not happen in real time depending on what database you are using, but notes that this might be a perfectly acceptable tradeoff. MySQL users can take advantage of Read/Write Splitting with MySQL-Proxy.

Michael concludes:

The reflexive answer to scaling is, "Scale out at the web and app tiers, scale up in the data tier." I hope this shows that there are other avenues to improving performance and capacity.

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