Debugging Your Services with Distributed Tracing

on YouTube ↗34m

" summary

Concrete account of rolling out distributed tracing at Heroku: proven white‑box tracing using Zipkin on Heroku, instrumentation via rack middleware + Faraday to propagate trace/parent IDs and timestamp annotations, transport done out‑of‑band with a threaded client (sucker_punch), practical sampling (start near 0.1 sample rate), run time was a few months part‑time, Zipkin uses a test Cassandra and needs auth via reverse proxy, language support and host‑agent requirements determine whether the solution is viable.

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" chapters (39)

1. 0:00Start
2. 2:16A Simple Use Case
3. 3:24Microservices!
4. 4:01Why do we need distributed tracing?
5. 4:27Internal services look like external APIs
6. 5:25How do you tell the story?
7. 5:54What's Stopping You?
8. 6:08Outside the Ruby Wheelhouse
9. 6:42Fractured Ecosystem
10. 7:04Theory - Practice
11. 7:17The Basics
12. 7:56Why might this not work for you?
13. 9:07White Box Tracing
14. 9:20Metadata Propagation
15. 9:43History Lesson
16. 9:56Dapper
17. 11:58Tracing Requests
18. 14:10A Trace is many Parent - Child Relationships
19. 16:09Transporting the Data
20. 16:55Viewing the Data
21. 21:48Tracing Outgoing Requests
22. 22:18More Middleware!
23. 24:09Buy, Build, or Adopt
24. 24:55Adopt an OSS Solution?
25. 25:38What about Open Tracing?
26. 26:05Standardizes Instrumentation
27. 26:41Where is Open Tracing at today?
28. 27:17Interoperability is Still Messy
29. 27:42Language Support
30. 28:42What are other folks doing?
31. 29:06Infra Requirements and Limitations
32. 30:02Installing a Separate Agent
33. 30:36Missing Authentication & Authorization
34. 30:47Client Authorization
35. 31:07Browser Authentication
36. 31:25Giving people access
37. 31:41Custom Instrumentation
38. 32:06What happens when data leaks?
39. 32:46Get it on the Roadmap

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