This article is a follow up to Getting started: Infinispan as remote cache cluster

Out of the box Infinispan configuration works great for low to medium number of GET/PUT operations. But in distributed mode and for heavy  GET/PUT operations, you may frequently see locking failures like this one:

2013-03-22 00:14:20,033 [DEBUG] org.infinispan.server.hotrod.HotRodDecoder HotRodClientMaster-63 - Exception caught
org.infinispan.server.hotrod.HotRodException: org.infinispan.util.concurrent.TimeoutException: Unable to acquire lock after [10 seconds] on key [ByteArrayKey{data=ByteArray{size=18, hashCode=48079ac7, array=0x033e0f3134354065..}}] for requestor [Thread[HotRodClientMaster-63,5,main]]! Lock held by [(another thread)]
        at org.infinispan.server.hotrod.HotRodDecoder.createServerException(HotRodDecoder.scala:214)
        at org.infinispan.server.core.AbstractProtocolDecoder.decode(AbstractProtocolDecoder.scala:75)
        at org.infinispan.server.core.AbstractProtocolDecoder.decode(AbstractProtocolDecoder.scala:45)

Infinispan uses locking to maintain cache consistency. Optimizing locking settings can help improve overall performance. Here are some configuration tips to avoid locking issues and improve concurrency:

    <default>
        <locking concurrencylevel="1000" isolationlevel="READ_COMMITTED" lockacquisitiontimeout="500" uselockstriping="false">
        <jmxstatistics enabled="true" />
        <!-- Configure a asynchronous distributed cache -->
        <clustering mode="distribution">
            <async/>
            <hash numowners="2"></clustering>
        </locking>
    </default>

Explanation:

• Concurrency level: Adjust this value according to the number of concurrent threads interacting with Infinispan.
• lockAcquisitionTimeout: Maximum time to attempt a particular lock acquisition. Set this based on your application needs.
• useLockStriping: If true, a pool of shared locks is maintained for all entries that need to be locked. Otherwise, a lock is created per entry in the cache. Lock striping helps control memory footprint but may reduce concurrency in the system.

Another configuration worth looking at it Level 1 (L1) cache. An L1 cache prevents unnecessary remote fetching of entries mapped to remote caches by storing them locally for a short time after the first time they are accessed. Read more here.