20160317 lagom sf scala
- 1. Microservices and Lagom Jamie Allen Sr. Director of Global Services @jamie_allen
- 2. Agenda • What are “microservices?” • What do we want in our services? • Lagom • Questions
- 3. Traditional application architectures and platforms are obsolete. Gartner
- 4. What are we trying to achieve? • Accelerate teams • Reduce dependency nightmares • Increase application throughput Calvin and Hobbes, Bill Waterston
- 5. “Microservices” is a lousy term • Size is irrelevant Bing Images
- 6. We want isolation • At the API • In our source • For our data Wikipedia, Creative Commons, created by DFoerster
- 7. We want realistic data management • Transactions, especially distributed, will not work • Consistency is an anti-pattern at scale • CQRS and Event Sourcing, not CRUD • Distributed locks and shared data will limit you Think in terms of compensation, not prevention. Kevin Webber, Lightbend
- 8. We want asynchronous APIs • Synchronous request/response semantics are expensive • Use REST for external APIs • Stream-based interactions for inter-service communication US Postal Service
- 9. We want immutable deployments • We can bind a build of our application to a version of our configuration and always know what is currently running • You cannot edit configuration and keep running Dilbert, Scott Adams
- 10. We want to expose a “tip of the iceberg” • Users see the public API • The API hides much complexity MyBluePuzzle.org
- 11. We want DDD (but not a requirement) • Solving your pain is • In a greenfield project, Bounded Contexts and Aggregate Roots can help you to decompose the problem
- 12. We want to ACID v2 • Associativity and Commutativity are the path to scale • Idempotent and Distributed Wikipedia, Creative Commons, created by Weston.pace
- 13. We will have additional operational complexity • Proxying • Service Discovery • Stateless aggregation • Orchestration • Failure management • Versioning Complexityandotherbeasts.com
- 15. • Service API • Persistence API • Development environment • Production environment Lagom
- 16. • IO and communication • Streaming between services as a first-class concept • Higher level of resilience and scalability with no blocking • Service is a Bounded Context in DDD Lagom Service API
- 17. • Event sourced (deltas) with Cassandra backend by default • No object/relational impedance mismatch • Can always replay to determine current state • Allows you to learn more from your data later • Persistent entity is an Aggregate Root in DDD • Can be overridden for CRUD if you want Lagom Persistence API
- 18. • Create single project definition in sbt, use runAll, includes: • In-memory Cassandra with own keyspaces • A service locator • A service gateway • Overload Mode: recompile and redeploy on save Development Environment
- 19. • Deployment • Monitoring • Scaling • Can test locally with ConductR then push to production • Launch multiple instances with a single command Production Environment (Lightbend RP)
- 21. Questions?