trying to solve IT problems

JBoss World Boston notes, Using Infinispan for high availability, extreme performance, Manik Surtani & Galder Zamarreño

Infinispan as…
in memory object cache
… clustering/high availability toolkit
… clustered in-memory cache
… in-memory data grid
… cloud ready data store

Local, in-memory object cache
- performance booster
- good when data is hard to calculate, expensive to retrieve or frequently accessed

Better than hashmap
- better concurrency
- built-in eviction
- overflow to disk
- warm start, preloading
- events, notifications
- highly configurable locking strategies
- JTA compatible
- JMX monitoring

Tips and tricks
- use eviction, low-cost boudnedd container, recency based: LIRS
- tune for read-heavy, use lock-striping, READ_COMMITTED is often sufficient
- pre-loading can be expensive

Clustering toolkit
- High availability
- fail-over
- scale-out
- uses self-discovery, self-healing

Tips and tricks
- strive for session affinity, very valid optimization, will allow fo async communication
- replicated mode vs distribution? Depend on cluster size
- distribution: co-locate related state
- pre-loading, state transfer not necessary, use a ClusterCacheLoader

Clustered in-memory cache
- performance booster
- similar to local cache
- cluster-aware
- more shared-cache space

Writing data in cache, use putForeExternalRead() vs put()
- update cache state vs update “real” state
- fail-fast instead of lock
- fail quietly instead of throw exception
- does not affect transaction

Tips and tricks
- same as local cache
- putForExternalRead() API
- use invalidation clustered mode
– very efficient: only keys on the wire
– async communication helps even more
- replication can be used
– if cluster is small and data cached is small
– overall data volume can be contained in a single node

In-memory data grid
- multiple access mechanisms
- embedded: P2P
- client/server: REST, memcached, HotRod
- familiar APIs
– cache API
– upcoming JPA-like API
- Queryability

FADE: Fast, Available, Distributed, Elactic

Tips and tricks
- session affinity is nice to have
- async communication and eventual consistency
- use distributed mode, replicated will work to a limit
- tune performance vs durability, numOwners
- dedicated data tier helps you build stateless, elastic application tier
- HotRod: most efficient endpoint

Cloud-ready data store
- RDBMS in inelastic, single point of failure
- data grid deals with transience, is elastic, scalable, distributed
- API is key

Tips and tricks
- asme as data grids
- REST: use load balancer
- use a transport that does not use multicast (not supported on something like EC2)