Richardrodger microxchgio-feb-2015-final
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This document discusses measuring microservices by monitoring message flow rates and patterns. It suggests measuring: - Message flow rates after deploying new services to detect any breaks - Common message patterns like actor, subscriber, chain, and tree to validate expected behavior - Invariants like the relationship between add-item and sales-tax messages to ensure the system is functioning correctly Measuring these things provides visibility into the health and risks of the distributed system.
Richardrodger microxchgio-feb-2015-final
- 1. Measuring Micro-services Richard Rodger @rjrodger nearform.com
- 2. Pulse. Temperature. Blood Pressure. Micro-service systems have emergent properties too.
- 3. nearForm & micro-services 50+ production systems. The good, the bad, and the ugly.
- 4. What are micro-services? Independent processes that exchange messages.
- 5. Messages are fundamental. Message behavior has emergent properties.
- 6. Message flow rate. Easy to measure. Tells you a lot. Independent of services.
- 7. Deploy a new micro-service. Does the new version break anything?
- 8. To measure changes to services, measure changes to message flow rates.
- 9. Micro-service message patterns. What to measure? Here’s what we’ve found useful…
- 10. Actor. A pool of services share message load evenly (round-robin, say).
- 11. Subscriber. Many services all listen for the same set of message types.
- 12. Chain. An initial message causes a chain of serial message steps.
- 13. Tree. An initial message causes a flowering of child messages.
- 14. Why? It's the risk, stupid! Monoliths put everybody in danger.
- 15. Risk. Reduction can be measured. Leave elimination to Machiavelli.
- 16. Our "best practices" for risk. Unit tests; code reviews; standards. Do we have good measures?
- 17. We've just made things worse! Microservices also have emergent failure modes.
- 18. Let's attack both sides. And we'll find a way to connect both attacks. Formal Methods “Best Practices” Measurement
- 19. Dynamic measurement. Measure health of the system. Exposes unknown unknowns.
- 20. Formal methods. Correctness proofs are impractical. Incomplete execution traces? FTW! * http://research.microsoft.com/en-us/um/people/lamport/tla/tla.html TLA+ Leslie Lamport *
- 21. Invariants. Some things should never change. Measure them to make sure!
- 22. Example. E-commerce shopping cart. add-item msgs == sales-tax msgs
- 23. Be practical! Finding invariants is hard. Use the microservice patterns to cheat.
- 24. Actor. n actors means each actor sees 1⧸nof the messages.
- 25. Subscriber. n subscribers means each sees n messages.
- 26. Chain. n inbound messages over k links means nk chained messages.
- 27. Tree. n inbound messages over k leaves means nk leaf messages.
- 28. Look for cause/effect relationships. These are by design! Validate your message patterns in production. “ask not what can go wrong, ask what must go right…” Chris Newcombe, AWS* * http://research.microsoft.com/en-us/um/people/lamport/tla/amazon.html
- 29. When should you rollback? Invariants should be the same before and after deployment.
- 30. Is the system correct? Business rules are invariants too! Express as message relationships.
- 31. Are you about to be blindsided? Combine individual indicators to get a deeper measure of risk.
- 32. Measure what counts. Find invariants. Measure them. Follow: senecajs.org
- 33. Thank You! Richard Rodger @rjrodger nearform.com