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.

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