The Verification of a Distributed System

YOW 2016: Melbourne
References: https://github.com/CaitieM20/Talks/tree/master/TheVerificationOfADistributedSystem

Transcript

1. The Verification of a Distributed System A Practitioner’s Guide to Increasing Confidence in System Correctness
2. Distributed Systems Engineer Caitie McCaffrey caitiem.com @caitie
4. LESLIE LAMPORT “A Distributed System is one in which the failure of a computer you didn’t even know existed can render your own computer unusable”
5. Service Service Service We Are All Building Distributed Systems
6. Twitter Services
8. Overview Formal Verification Provably Correct Systems Testing in the Wild Increase Confidence in System Correctness Research A New Hope
9. References
10. Provably Correct Formal Verification
11. Formal Specifications Written description of what a system is supposed to do TLA+ Coq
12. Hour Clock Specification ————————————— MODULE HourClock ———————————————— EXTENDS Naturals VARIABLE hr HCini == hr \in (1 .. 12) HCnxt == hr’ = IF hr # 12 THEN hr + 1 ELSE 1 HC == HCini /\ [][HCnxt] _hr ————————————————————————————————————————————- THEOREM HC => []HCini ============================================= Leslie Lamport, Specifying Systems TLA+
13. Use of Formal Methods at Amazon Web Services TLA+
14. “Formal Methods Have Been a Big Success” S3 & 10+ Core Pieces of Infrastructure Verified 2 Serious Bugs Found Increased Confidence to make Optimizations Use of Formal Methods at Amazon Web Services TLA+
15. Leslie Lamport, Specifying Systems “Its a good idea to understand a system before building it, so its a good idea to write a specification of a system before implementing it” TLA+
16. “Formal methods deal with models of systems, not the systems themselves” Use of Formal Methods at Amazon Web Services
17. Program Extraction
18. POPL 2016 “Our Verified Implementation is extracted to OCaml & runs on real networks” Program Extraction COQ
19. POPL 2016 “We have developed & checked our framework in Coq, extracted it to OCaml, and built executable stores” Program Extraction COQ
20. Distributed Systems Testing in the Wild “Seems Pretty Legit”
21. Unit Tests Testing of Individual Software Components or Modules
22. Simple Testing Can Prevent Most Critical Failures
23. 77% of Production failures can be reproduced by a Unit Test Simple Testing can Prevent Most Critical Failures
24. Error Handling Code is simply empty or only contains a Log statement Error Handler aborts cluster on an overly general exception Error Handler contains comments like FIXME or TODO 35% of Catastrophic Failures Simple Testing can Prevent Most Critical Failures
25. Testing error handling code could have prevented 58% of catastrophic failures Simple Testing can Prevent Most Critical Failures
26. Scala Types Are Not Testing A Short Counter Example
27. TCP Doesn’t Care About Your Type System
28. Integration Tests Testing of integrated modules to verify combined functionality
29. Three nodes or less can reproduce 98% of failures Simple Testing can Prevent Most Critical Failures
30. Property Based Testing
31. QuickCheck ScalaCheck Haskell Erlang Scala Java & & C, C++, Clojure, Common Lisp, Elm, F#, C#, Go, JavaScript, Node.js, Objective-C, OCaml, Perl, Prolog, PHP, Python, R, Ruby, Rust, Scheme, Smalltalk, StandardML , Swift Languages with Quick Check Ports:
32. ScalaCheck Examples
33. Fault Injection Introducing faults into the system under test
34. -The Verification of a Distributed System “Without explicitly forcing a system to fail, it is unreasonable to have any confidence it will operate correctly in failure modes”
35. Netflix Simian Army • Chaos Monkey: kills instances • Latency Monkey: artificial latency induced • Chaos Gorilla: simulates outage of entire availability zone.
36. Kyle has used this tool to show us that many of the Distributed Systems we know seem stable but are really just this. (cut to tire fire photo) JEPSEN credit: @aphyr Fault Injection Tool that simulates network partitions in the system under test
37. Kyle has used this tool to show us that many of the Distributed Systems we know seem stable but are really just this. (cut to tire fire photo) JEPSEN credit: @aphyr Fault Injection Tool that simulates network partitions in the system under test
38. CAUTION: Passing Tests Does Not Ensure Correctness
39. GAME DAYS Resilience Engineering: Learning to Embrace Failure Breaking your services on purpose
40. How to Run a GameDay 1. Notify Engineering Teams that Failure is Coming 2. Induce Failures 3. Monitor Systems Under Test 4. Observing Only Team Monitors Recovery Processes & Systems, Files Bugs 5. Prioritize Bugs & Get Buy-In Across Teams Resilience Engineering: Learning to Embrace Failure
41. Game Day at Stripe “During a recent game day, we tested failing over a Redis cluster by running kill -9 on its primary node, and ended up losing all data in the cluster” Game Day Exercises at Stripe: Learning from `kill -9`
42. TESTING IN PRODUCTION Some thoughts on
43. Monitoring Testing is not
44. CANARIES “Verification” in production
45. Verification Wild in the Unit & Integration Tests Property Based Testing Fault Injection Canaries
46. Research Improving the Verification of Distributed Systems Lineage Driven Fault Injection ‘Cause I’m Strong Enough: Reasoning about Consistency Choices in Distributed Systems IronFleet: Proving Practical Distributed Systems Correct
47. ‘Cause I’m Strong Enough POPL 2016
48. ‘Cause I’m Strong Enough: Reasoning About Consistency Choices in Distributed Systems
49. Conclusion Use Formal Verification on Critical Components Unit Tests & Integration Tests find a multitude of Errors Increase Confidence via Property Testing & Fault Injection
50. Camille Fournier “Enjoy the ride, have fun, and test your freaking code”
51. Thank You Peter Alvaro Kyle Kingsbury Christopher Meiklejohn Alex Rasmussen Ines Sombra Nathan Taylor Alvaro Videla
52. Questions @caitie https://github.com/CaitieM20/ Talks/tree/master/ TheVerificationOfADistributedSystem Resources: