QCon NewYork 2016: The Verification of a Distributed System

QCon NewYork 2016: The Verification of a Distributed System

Distributed Systems are difficult to build and test for two main reasons: partial failure & asynchrony. These two realities of distributed systems must be addressed to create a correct system, and often times the resulting systems have a high degree of complexity. Because of this complexity, testing and verifying these systems is critically important. In this talk we will discuss strategies for proving a system is correct, like formal methods, and less strenuous methods of testing which can help increase our confidence that our systems are doing the right thing.

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Caitie McCaffrey

June 14, 2016
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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

  3. None
  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

  7. None
  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. “Formal methods deal with models of systems, not the systems

    themselves” Use of Formal Methods at Amazon Web Services
  16. 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+
  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. Scala Types Are Not Testing A Short Counter Example

  26. TCP Doesn’t Care About Your Type System

  27. Integration Tests Testing of integrated modules to verify combined functionality

  28. Three nodes or less can reproduce 98% of failures Simple

    Testing can Prevent Most Critical Failures
  29. Property Based Testing

  30. 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:
  31. ScalaCheck Examples

  32. Fault Injection Introducing faults into the system under test

  33. -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”
  34. Netflix Simian Army • Chaos Monkey: kills instances • Latency

    Monkey: artificial latency induced • Chaos Gorilla: simulates outage of entire availability zone.
  35. 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
  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. CAUTION: Passing Tests Does Not Ensure Correctness

  38. GAME DAYS Resilience Engineering: Learning to Embrace Failure Breaking your

    services on purpose
  39. 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
  40. 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`
  41. TESTING IN PRODUCTION Some thoughts on

  42. Monitoring Testing is not

  43. CANARIES “Verification” in production

  44. Verification Wild in the Unit & Integration Tests Property Based

    Testing Fault Injection Canaries
  45. 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 Towards Property Based Consistency Verification
  46. ‘Cause I’m Strong Enough POPL 2016

  47. ‘Cause I’m Strong Enough: Reasoning About Consistency Choices in Distributed

    Systems
  48. Conclusion Use Formal Verification on Critical Components Unit Tests &

    Integration Tests find a multitude of Errors Increase Confidence via Property Testing & Fault Injection
  49. Camille Fournier “Enjoy the ride, have fun, and test your

    freaking code”
  50. Thank You Peter Alvaro Kyle Kingsbury Christopher Meiklejohn Alex Rasmussen

    Ines Sombra Nathan Taylor Alvaro Videla
  51. Questions @caitie http://github.com/CaitieM20/ TheVerificationOfDistributedSystem Resources: