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'The History of Metrics According to me' by Stephen Day


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Metrics and monitoring are a time honored tradition for any engineering discipline. It is how we ensure the systems we use are working the way we expect. If this is a time honored tradition, why is it not a built into every piece of software we create, from the ground up? With software engineering, usually the trick to solving anything is to make it easier. By solving the hard parts of application metrics in Docker, we should make it more likely that metrics are a part of your services from the start.

Published in: Technology

'The History of Metrics According to me' by Stephen Day

  1. 1. The History of Metrics According to Me Stephen Day Docker, Inc. Docker Meetup, SF December 2016 v1
  2. 2. Stephen Day Docker, Inc. @stevvooe
  3. 3. Metrics Why?
  4. 4. The Early Years
  5. 5. 5 Titration By UCL - Flickr, CC BY 2.0,
  6. 6. Music
  7. 7. Electrical Engineering CC BY-SA 3.0,
  8. 8. Microcontrollers
  9. 9. Human Powered Submarine
  10. 10. Graphs
  11. 11. Software Engineering
  12. 12. Software Engineering is way behind! Sort of. See for an example
  13. 13. 13 Observability and Controllability The Problem Low Observability High Observability Guessing Informed
  14. 14. Models INFO[0012] response completed go.version=go1.6.3 http.request.method=GET http.request.remoteaddr= http.request.uri=/v2/ http.request.useragent=curl/7.49.1 http.response.contenttype=application/json; charset=utf-8 http.response.duration=5.4388ms http.response.status=200 http.response.written=2 version=v2.5.1 Record-based
  15. 15. Models Sample-based t
  16. 16. Why aren’t metrics built into everything?
  17. 17. Excuses!
  18. 18. Why aren’t metrics a part of Docker?
  19. 19. The Goal
  20. 20. Prometheus
  21. 21. Types of Metrics - Counters: cumulative number that only increases - Gauges: value that can go up or down - Summary/Histogram: Sample of observations
  22. 22. Format
  23. 23. Configuration
  24. 24. Architecture
  25. 25. Demo
  26. 26. What’s next? So much.
  27. 27. Road Map
  28. 28. - For Contributors and Maintainers to better understand performance - For Users to better understand behavior of the daemon in their infrastructure - Implemented in 1.13 Docker Engine Metrics
  29. 29. Externally Observable Metrics - CPU, memory usage, etc. - Replaces docker stats
  30. 30. Integrated Target Discovery - Prometheus automatically discover engine and container metric targets
  31. 31. Application Metrics - Directly proxy your metrics out of the Docker daemon - Leverage built in integrated target discovery
  32. 32. THANK YOU