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Monitoring Microservices

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Monitoring Microservices

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By Tom Wilkie, delivered at London Microservices User Group on 2/12/15

The rise of microservice-based applications has had many knock-on effects, not least on the complexity of monitoring your application. Order-of-magnitude increase in the number of moving parts and rate of change of the application require us to reassess traditional monitoring techniques.

In this talk we will discuss some different approaches to monitoring, visualising and tracing containerised, microservices-based applications. We’ll present different techniques to some of the emergent problems, and try not to rant too much.

By Tom Wilkie, delivered at London Microservices User Group on 2/12/15

The rise of microservice-based applications has had many knock-on effects, not least on the complexity of monitoring your application. Order-of-magnitude increase in the number of moving parts and rate of change of the application require us to reassess traditional monitoring techniques.

In this talk we will discuss some different approaches to monitoring, visualising and tracing containerised, microservices-based applications. We’ll present different techniques to some of the emergent problems, and try not to rant too much.

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Monitoring Microservices

  1. 1. Monitoring Microservices tom@weave.works @tom_wilkie
  2. 2. VisualisationMonitoring Tracing 0 25 50 75 100
  3. 3. Monitoring 0 25 50 75 100
  4. 4. Traditional 3-tier architecture Incoming traffic Load balancers Application servers Database & replica
  5. 5. Microservice architecture Public APIWeb UI NoSQL serversDatabase Message Broker Services
  6. 6. Microservices should be treated like cattle not pets
  7. 7. USE Method* - for every resource, check: • utilization, • saturation, and • errors RED Method - for every service, check request: • rate, • error (rate), and • duration (distributions) are within SLO/A * http://www.brendangregg.com/usemethod.html An alternative view
  8. 8. Monitoring 0 25 50 75 100
  9. 9. Visualisation
  10. 10. Weave Scope
  11. 11. Connection Tracking # cat /proc/net/tcp # conntrack -E -p tcp
  12. 12. Matrix
  13. 13. Connection Tracking all connections from /proc conntrack
  14. 14. Demo time
  15. 15. Visualisation
  16. 16. Tracing
  17. 17. Distributed Tracing
  18. 18. Not a new topic • Lots of literature • Existing open source projects • e.g. Zipkin, originally from Twitter
  19. 19. • Challenge: detecting causality between incoming and outgoing requests • Existing solutions require propagation of some unique ID (dapper, zipkin) • This requires application-specific modifications some service incoming request outgoing requests ?
  20. 20. Can this be done without application modifications?
  21. 21. Demo time
  22. 22. Tracing
  23. 23. VisualisationMonitoring Tracing 0 25 50 75 100
  24. 24. @weaveworks github.com/weaveworks Questions? http://weave.works/product/scope tom@weave.works @tom_wilkie

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