The History of Metrics According to Me

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.

Transcript

1. The History of Metrics According to Me Stephen Day Docker, Inc. Docker Meetup, SF December 2016 v1
2. Stephen Day Docker, Inc. stephen@docker.com github.com/stevvooe @stevvooe
3. Metrics Why?
4. The Early Years
5. 5 Titration By UCL - Flickr, CC BY 2.0, https://commons.wikimedia.org/w/index.php?curid=45263025
6. Music
7. Electrical Engineering CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=392484
8. Microcontrollers
9. Human Powered Submarine
10. Graphs
11. Software Engineering
12. Software Engineering is way behind! Sort of. See http://www.itl.nist.gov/div898/handbook/ for an example
13. 13 Observability and Controllability The Problem Low Observability High Observability Guessing Informed
14. Models INFO[0012] response completed go.version=go1.6.3 http.request.host=localhost:5001 http.request.id=4db26096-a417-48e8-a759-ddd8ea66c3a0 http.request.method=GET http.request.remoteaddr=172.17.0.1:57406 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 instance.id=7926875b-d3fb-41e4-bd75-2370a3e8a03c version=v2.5.1 Record-based
15. Models Sample-based t
16. Why aren’t metrics built into everything?
17. Excuses!
18. Why aren’t metrics a part of Docker?
19. The Goal
20. Prometheus https://prometheus.io/
21. Types of Metrics - Counters: cumulative number that only increases - Gauges: value that can go up or down - Summary/Histogram: Sample of observations https://prometheus.io/docs/concepts/metric_types/
22. Format
23. Configuration
24. Architecture
25. Demo
26. What’s next? So much.
27. Road Map https://github.com/docker/docker/issues/27307
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. Externally Observable Metrics - CPU, memory usage, etc. - Replaces docker stats
30. Integrated Target Discovery - Prometheus automatically discover engine and container metric targets
31. Application Metrics - Directly proxy your metrics out of the Docker daemon - Leverage built in integrated target discovery
32. THANK YOU