Data in Motion: A Beginner’s Guide to Caching and Queuing

The difference between a system that buckles under load and one that stays fast and dependable usually comes down to two skills: keeping data close (caching) and moving work reliably in the background (queuing). Data in Motion teaches both, honestly and one clear step at a time, the way a patient mentor would.

This hands-on handbook takes you across eight parts: the foundations (why data in motion matters, and the fundamentals of caching, messaging, and queuing); caching with Ehcache and Redis (data structures, persistence, replication, and production patterns); messaging with RabbitMQ (exchanges, routing, and reliability); streaming with Apache Kafka (partitions, consumer groups, delivery guarantees, Connect, Streams, and schemas); choosing and combining the right tools; running in production (configuration, observability, performance and capacity planning, and security); bringing it all together through real failure and success scenarios; and a practical career roadmap.

You won't just read — you'll build. Step-by-step labs guide you to talk to Redis, send and safely receive a message, produce and consume from a Kafka topic, build a rate limiter, and finally wire a cache and a queue into one complete system of your own. A single running example, TicketHive, makes every idea concrete, while candid "Hard Truth" and anti-pattern notes spare you the mistakes that sink real systems.

A rich reference section — patterns and command cheat-sheets for Redis, RabbitMQ, and Kafka, a glossary, checklists, decision guides, and a 30-day learning plan — makes this a book you'll keep returning to. No prior experience needed. By the final page, caching and queuing will feel less like mysteries and more like a craft you can practise with confidence.