Leveraging Caching For Cloud Native Applications
summary
Argues caching is not just for latency but for data sharing and cloud-native synchronization, with hands-on demos using Hazelcast and Apache Ignite plus RabbitMQ. Shows four topologies (in-memory grid, in-memory DB, replicated cache, distributed and near cache), claims replicated reads/writes hit nanoseconds, distributed hits milliseconds, and replication syncs in ~0.1s. Builds microservices, a data pump/writer/reader pipeline to persist on‑prem; demo keeps a wishlist usable when the product service crashes and the design works with eventual consistency and archive eviction.
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chapters (9)
- 0:00Introduction to caching
- 1:54Caching topologies overview
- 9:01Choosing the right cache
- 15:09Data sharing with caches
- 22:12Demo: replicated cache in action
- 33:12Cloud data synchronization
- 41:26Demo: space-based architecture
- 49:42Archiving data in caches
- 51:51Q&A and summary
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