Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/2aMHtV7. Matt Ranney talks about Uber’s growth and how they’ve embraced microservices. This has led to an explosion of new services, crossing over 1,000 production services in early March 2016. He “acknowledges the pain” in growing the architecture at an explosive growth company, and he describes how we might benefit from their pain points and learn from one of the fastest growing software companies. Filmed at qconnewyork.com. Matt Ranney is Chief Systems Architect at Uber, where he's helping build and scale everything he can. Previously, Ranney was a founder and CTO of Voxer, probably the largest and busiest deployment of Node.js.

1. WHATIWISHIKNEW
BEFORESCALINGUBER
TO1,000SERVICES
MATT RANNEY

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synchronization on InfoQ.com!
https://www.infoq.com/presentations/
uber-scalability-services

3. Presented at QCon New York
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4. WHATIWISHIKNEW
BEFORESCALINGUBER
TO1,000SERVICES
MATT RANNEY

7. As of June 2016:
Uber Cities Worldwide: 400+
Countries: 70
Employees: 7,000-

8. LIFE LESSONS

10. WHY MICROSERVICES?
Move and Release Independently
Own your Uptime
Use the “Best” tool for the job

11. WHAT ARE THE COSTS?
Now you have a distributed system
What if it breaks?
Operational complexity

12. MICROSERVICES
Immutable?
Append Only?

13. LESS OBVIOUS COSTS
Everything is a tradeoff
You can build around problems
Might trade complexity for politics
You get to keep your biases

14. LANGUAGES
Hard to share code
Hard to move between teams
WIWIK: Fragments the culture

15. RPC
HTTP/REST gets complicated
JSON needs a schema
RPCs are slower than PCs
WIWIK: servers are not browsers

16. HOW MANY REPOS

18. APRIL 2016
MAY 2016
JUNE 2016

19. OPERATIONAL
What happens when things break?
Can other teams release your service?
Understand a service in the larger context

20. PERFORMANCE
Depends on language tools

25. PERFORMANCE
Doesn’t matter until it does
Probably want at least simple perf requirements
WIWIK: “good” not required, but “known” is

26. overall latency ≥ latency of slowest
1ms avg, 1000ms p99
use 1: 1% at least 1000ms
use 100: 63% at least 1000ms
1.0 - 0.99^100 = 0.634 = 63.4%
FANOUT

27. requeststhatareslow
0%
25%
50%
75%
100%
Processes Used
1 2 4 8 16 32 64 128 256 512 1024
p95 p99 p99.9

28. TRACING
Lots of ways to get this
Best way to understand fanout

32. TRACING
Probably want sampling
WIWIK: cross-lang context propagation

34. LOGGING
Need consistent, structured logging
Multiple languages makes this hard
Logs are not for humans

37. LOGGING
Logging floods can amplify problems
WIWIK: Accounting

38. LOAD TESTING
Need to test against production
Without breaking metrics
Preferably all the time
WIWIK: all systems need to handle “test” traffic

39. FAILURE TESTING
WIWIK: people won’t like it

40. MIGRATIONS
Old stuff still has to work
What happened to immutable?
WIWIK: mandates are bad

41. OPEN SOURCE
Build/buy tradeoff is hard
Commoditization
WIWIK: this will make people sad

42. POLITICS
Services allow people to play politics
Company > Team > Self

43. TRADEOFFS
Everything is a tradeoff
Try to make them intentionally

44. THANKS

45. Watch the video with slide
synchronization on InfoQ.com!
https://www.infoq.com/presentations/
uber-scalability-services