Implementing Microservices with Scale and Akka

on YouTube ↗51m

" summary

Shows how Scala and Akka Persistence + CQRS implement microservices as bounded contexts owning an event journal and a separate read model, with aggregates as persistent actors and process managers for multi-step flows. Recommends publishing domain events to a central topics bus (Kafka/RabbitMQ or REST feed) and turning events into local commands instead of directly calling other services. Demonstrates Play for HTTP endpoints, cites 12–20 ms responsive command roundtrips, a 2400‑node Akka cluster example, and a practical deployment of 35–50 microservices from bounded contexts.

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" chapters (28)

1. 0:00Intro
2. 1:48INDUSTRY OF EXTREMES
3. 2:31WHY ACID? HOW DID BUSINESS WORK BEFORE
4. 4:41EXTREME: SERVICE SIZE MONOLITH MICRO
5. 9:44THINK INFRA- STRUCTURE
6. 10:15PRACTICAL?
7. 11:35BUILDING MICROSERVICES
8. 12:22WHAT IS THE SIZE OF A BOUNDED CONTEXT?
9. 12:33SHOULD IT HAVE JUST ONE ENTITY TYPE?
10. 13:03ASK YOUR UBIQUITOUS LANGUAGE
11. 14:41LINGUISTIC COMPONENTS ARE COHESIVE
12. 17:27LARGER THAN ONE ENTITY FAR SMALLER THAN A MONOLITH
13. 17:50UBIQUITOUS LANGUAGE IS GREATER THAN ENTITY NAMES
14. 18:08UBIQUITOUS LANGUAGE INCLUDES ENTITIES / COMMAND MESSAGES / EVENT MESSAGES
15. 19:28MICROSERVICE DATABASE(S)
16. 20:46QUERY MODEL
17. 21:27ACTORS ARE ASYNCHRONOUS SERVICES
18. 24:19RAPIDS: PUBLISH EVERY EVENT
19. 25:26HIGH-PERFORMANCE BUS REST (ATOM) KAFKA RABBITMO
20. 28:25PONDS: AGGREGATE ACTOR STATES
21. 28:56ACTORS EMIT EVENTS TO RAPIDS
22. 31:18RESILIENT PARENT CRASH DETECTION, NOT CLIENT
23. 33:14MESSAGE DRIVEN ACTORS ARE MESSAGE DRIVEN RAPIDS ARE MESSAGE DRIVEN
24. 33:32HOW TO IMPLEMENT MICROSERVICES SCALA & AKKA
25. 35:50SERVICE START UP (THE CODE)
26. 39:55PROCESS MANAGER WHEN NEEDED. OTHERWISE DON'T
27. 43:44ACTOR AGGREGATE (THE CODE)
28. 45:06TOPICS FEEDER (THE CODE)

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