Building Disaster Recovery via Resilience Engineering (SV Chaos Engineering Meetup 2018)

How often have you heard stories where someone thought they had a disaster strategy, never tested it and it fails when you need it the most? LinkedIn has evolved from serving live traffic out of one data center to four data centers spread geographically. Serving live traffic from four data centers at the same time has taken the company from a disaster recovery model to a disaster avoidance model, where an unhealthy data center can be taken out of rotation and its traffic redistributed to the healthy data centers within minutes, with virtually no visible impact to users.

As LinkedIn transitioned from big monolithic applications to microservices, it was difficult to determine capacity constraints of individual services to handle extra load during disaster scenarios. Stress testing individual services using artificial load in a complex microservices architecture wasn’t sufficient to provide enough confidence in data center’s capacity. To solve this problem, LinkedIn moves live traffic to services site-wide by shifting traffic between datacenters to simulate a disaster every business day!

Michael Kehoe will discuss how LinkedIn shifts traffic between its data centers to chaos/ disaster test site-wide services for improved disaster recovery preparation.

Transcript

1. Building Disaster Recovery via
   Resilience Engineering
   Michael Kehoe
   Staff SRE - LinkedIn
   

   View Slide

2. Tonight’s
   agenda
   1 Introductions
   2 What is Resilience Engineering
   3 The Problem Statement
   4 Project Overview
   5 Testing Process
   6 Project Outcomes
   7 Key Takeaways
   8 Q&A
   

   View Slide

3. Introduction
   

   View Slide

4. Michael Kehoe
   /USR/BIN/WHOAMI
   • Staff Site Reliability Engineer @ LinkedIn
   • Production-SRE Team
   • Funny accent = Australian + 4 years American
   • Former Network Engineer at the University of
   Queensland
   

   View Slide

5. Who are we?
   PRODUCTION-SRE TEAM AT LINKEDIN
   • Disaster Recovery Planning and Automation
   • Incident Response and Automation
   • Visibility Engineering
   • Reliability Principles
   

   View Slide

6. LinkedIn
   EVOLUTION OF THE INFRASTRUCTURE
   2003 2010 2011 2013 2014 2015
   Active &
   Passive
   Active &
   Active
   Multi-colo 3-
   way Active &
   Active
   Multi-colo n-
   way Active &
   Active
   

   View Slide

7. LinkedIn
   2018
   4 Data Centers 21 PoPs 1000+ services
   

   View Slide

8. What is Resilience
   Engineering?
   

   View Slide

9. What is Resilience Engineering?
   • Projects that directly demand increased
   resilience from our applications and
   infrastructure.
   • Application Injection Failure
   • Infrastructure Injection Failure
   • Full Disaster-Recovery Tests
   

   View Slide

10. Problem Statement
    

    View Slide

11. How often have you heard stories where someone thought
    they had a disaster strategy, never tested it and it fails when
    you need it the most?
    

    View Slide

12. Problem Statement
    • How do we ensure that we always have
    disaster recovery ability without incident?
    • How do we consistently test for disaster
    recovery ability without disrupting the
    company?
    

    View Slide

13. Project Overview
    

    View Slide

14. Project Overview
    1
    • Build a process (with Automation) to facilitate disaster recovery
    • Operate the process on regular cadence
    • Provide reporting on outcomes of tests with engineering executives
    

    View Slide

15. Testing Process
    

    View Slide

16. What is Load Testing?
    5x a week Peak hour traffic Fixed SLA
    

    View Slide

17. LinkedIn Traffic-Tier
    Border
    Router IPVS ATS ATS Frontend
    EDGE FABRIC
    Stickyrouting
    

    View Slide

18. LinkedIn Traffic-Tier
    Fabric
    Buckets
    1
    91
    2 3 10
    92 93 100
    

    View Slide

19. LinkedIn Traffic-Tier
    EDGE FABRIC
    DC1
    DC2
    DC1 in Cookie
    Got DC2 as secondary fabric
    Gets secondary
    fabric for user
    Stickyrouting
    

    View Slide

20. TrafficShift Architecture
    Web
    application
    Salt master
    Stickyrouting
    Service
    Couchbase
    Backend Worker
    Processes
    FABRIC
    BUCKETS
    

    View Slide

21. Load Testing
    FABRIC
    DC3
    DC1 DC2
    60%
    Traffic
    Percentage
    

    View Slide

22. Load Testing
    22
    

    View Slide

23. Project Outcomes
    

    View Slide

24. Benefits of Load-testing
    Capacity Planning Identify Bugs Confidence
    

    View Slide

25. Benefits of Load-testing
    CAPACITY PLANNING
    • Through this process, we continuously validate our infrastructure
    capacity
    • This is the best signal we can possibly get since we’re simulating a real
    disaster
    

    View Slide

26. Benefits of Load-testing
    IDENTIFY BUGS
    2
    • Some bugs are only found at high load (under duress)
    • Helps find inefficiency’s that otherwise may not be found until it’s too late
    • Gives us clues on how to make our code more resilient to potential failure
    

    View Slide

27. Benefits of Load-testing
    CONFIDENCE
    2
    • Through load-testing, we’ve built confidence in our disaster recovery
    strategy
    • We understand exactly:
    • What process to follow
    • How long it takes to avert disaster
    • What are the risks associated with a disaster incident
    

    View Slide

28. Key Takeaways
    

    View Slide

29. Key Takeaways
    • Resilience Engineering is a must for LinkedIn
    • Design infrastructure to facilitate disaster
    recovery
    • Disaster-test regularly to avoid surprises
    • Automate your testing/ process to reduce
    engagement time
    

    View Slide

30. Q&A
    

    View Slide

31. View Slide