Microservices Design Patterns for Java Application
summary
Claims that microservices work at Netflix scale: an edge API handles ~15 billion incoming calls a day that fan out into many more internal requests, with ~95% success, and the architecture tolerates failures by degrading gracefully. Practical patterns shown are aggregator, proxy, chain (and branch) with each service owning its own database and cache. Implementations use ZooKeeper (with Curator), Consul options, Maven modules, WildFly and Docker containers; service discovery, CI/CD, 100% automation and incremental refactor from modular WARs are required and real migrations can take years.
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chapters (28)
- 0:00Introduction and speaker background
- 1:34Monolithic applications explained
- 4:23Disadvantages of monolithic apps
- 6:09Microservices definition and benefits
- 8:18Conway's law and team structure
- 10:06Well-defined interfaces in microservices
- 11:31Netflix example and responsibility
- 13:40Handling failures in microservices
- 15:04Polyglot persistence and tools
- 17:07Automation and DevOps culture
- 18:10Synchronous vs asynchronous communication
- 20:17Microservices vs SOA comparison
- 22:06Containers and scalability
- 23:08Decomposing monoliths into microservices
- 26:41Aggregator and proxy design patterns
- 29:11Chain and branch design patterns
- 31:00Data migration challenges
- 32:22DZone ref card and resources
- 33:03Advantages of microservices
- 37:17Innovation and technology flexibility
- 37:59Challenges of migrating to microservices
- 39:03Design principles for monoliths
- 42:11YAGNI and simplicity in design
- 42:32Monolith to microservices refactor demo
- 44:30Code structure and service discovery
- 48:18Microservices as silver bullet?
- 49:00Real-world migration insights
- 49:41Resources and conclusion
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