Distributed applications using Hazelcast
summary
Explains how Hazelcast turns a JVM heap into an in‑memory datagrid, demonstrates a tiny web app that starts multiple Hazelcast instances with one line, writes and reads a distributed map across nodes, and shows autoscaling and failure behavior: distributed map partitioning moves partitions across members, backup-count behavior creates primaries and backups so reads survive node crashes. Covers executor service, data aggregation across members, monitoring with Management Center, licensing tradeoffs (OSS vs Enterprise) and practical performance and GC caveats.
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chapters (10)
- 0:00Introduction to Hazelcast
- 3:31Top features of Hazelcast
- 13:06Hazelcast vs other solutions
- 29:27Hazelcast In-Memory Data Grid
- 33:51Distributed data with Hazelcast
- 42:13Hazelcast Executor Service
- 45:05Hazelcast transactions
- 48:18Hazelcast monitoring and security
- 51:03Hazelcast in production
- 55:07Q&A and closing remarks
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