DevOps Chicago - The Game Of Operations and the Operation of Games

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Operating online games is fun and challenging. Games are some of the spikiest workloads around, and real-time really means *real-time*. Randy shares many of the DevOps techniques he has been putting into practice at KIXEYE, including migrating to the cloud, organizing around services, and focusing on automation. He illustrates his points with war stories from operating large-scale services at Google and eBay.

Please see companion video at https://vimeo.com/95841677.

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DevOps Chicago - The Game Of Operations and the Operation of Games

  1. 1. The Game of Operations and The Operation of Games Randy Shoup @randyshoup linkedin.com/in/randyshoup DevOps Chicago Meetup, May 19 2014
  2. 2. Background CTO at KIXEYE • Real-time strategy games for web and mobile Director of Engineering for Google App Engine • World’s largest Platform-as-a-Service Chief Engineer at eBay • Multiple generations of eBay’s real-time search infrastructure
  3. 3. Real-Time Strategy Games are … • Real-time • Spiky • Computationally- intensive • Constantly evolving • Constantly pushing boundaries  Technically and operationally demanding
  4. 4. Operating Games: Goals Player Fun • If players aren’t playing, we don’t have a business • If players aren’t having fun, we don’t have a business for long • Fun includes game mechanics, feature set, quality, performance Studio Velocity • 8 *highly independent* game studios • Different tech stacks, tool chains, phases of development Developer Productivity and Satisfaction • We are a vendor; the studios are our customers • Must be *strictly better* than the alternatives of build, buy, borrow Cost Efficiency • More output for less
  5. 5. The Game of Operations Cloud • All studios and services moving to AWS • Strong focus on automation Services • Small, focused teams • Clean, well-defined interface to customers DevOps • Developers behave like Ops • Ops behaves like Developers
  6. 6. The Game of Operations Cloud Services DevOps
  7. 7. Why Cloud? (The Obvious) Provisioning Speed • Minutes, not weeks • Autoscaling in response to load Near-Infinite Capacity • No need to predict and plan for growth • No need to defensively overprovision Pay For What You Use • No “utilization risk” from owning / renting • If it’s not in use, spin it down
  8. 8. Why Cloud? (The Less Obvious) Instance Optimization Opportunities • Instance shapes to fit most parts of the solution space (compute-intensive, IO- intensive, etc.) • If the shape does not fit, try another Service Quality • Amazon and Google know how to run data centers • Battle-tested and highly automated • World-class networking, both cluster fabric and external peering
  9. 9. Why Cloud? (The Fundamentals) Right Side of History • Almost impossible to beat Google / Amazon buying power or operating efficiencies • 2010s in computing are like 1910s in electric power • Soon it will be just as common to run your own data center as it is to run your own electric power generation (!) Easy and Fun • It Just Works ™ • Makes it easy to fall in love with infrastructure 
  10. 10. Autoscaling Games are very spiky • Very unpredictable • Huge variability between peak and trough • Hits are self-reinforcing Services and clients have to “flex” • Clients back off in response to latency • Services grow / shrink based on load Service Cluster == AWS Auto-Scale Group • Scale up or down based on predefined metrics, thresholds
  11. 11. Automation Work at KIXEYE Build / Deploy Pipeline • One button • Puppet -> Packer -> AMI -> Asgard • No-downtime red-black deployment • Futures: canarying, auto-rollback Manageability • Flume -> ElasticSearch / Kibana for logging • Shinken -> PagerDuty for monitoring and alerting
  12. 12. The Game of Operations Cloud Services DevOps
  13. 13. Service Teams • Give teams autonomy • Freedom to choose technology, methodology, working environment • Responsibility for the results of those choices • Hold them accountable for *results* • Give a team a goal, not a solution • Let team own the best way to achieve the goal
  14. 14. KIXEYE Service Chassis • Goal: Produce a “chassis” for building scalable game services • Minimal resources, minimal direction • 3 people x 1 month • Consider building on open source projects  Team exceeded expectations • Co-developed chassis, transport layer, service template, build pipeline, red-black deployment, etc. • Operability and manageability from the beginning • Heavy use of Netflix open source projects • 15 minutes from no code to running service in AWS (!) • Plan to open-source several parts of this work
  15. 15. Micro-Services Simple Well-defined interface Single-purpose Modular and independent Small teams Autonomy and responsibility A C D E B
  16. 16. Transition to Building Services Common Chassis • Make it trivially easy to build and maintain a service Define Service Interface (Formally!) • Propose, Discuss, Agree Prototype Implementation • Simplest thing that could possibly work • Client can integrate with prototype • Implementor can learn what works and what does not Real Implementation • Throw away the prototype (!)  Rinse and Repeat
  17. 17. Transition to Service Relationships Vendor – Customer Relationship • Friendly and cooperative, but structured • Clear ownership and division of responsibility • Customer can choose to use service or not (!) Service-Level Agreement (SLA) • Promise of service levels by the service provider • Customer needs to be able to rely on the service, like a utility Charging and Cost Allocation • Charge customers for *usage* of the service • Aligns economic incentives of customer and provider • Motivates both sides to optimize
  18. 18. The Game of Operations Cloud Services DevOps
  19. 19. Instrumentation and Measurement Instrument Everything • Machine / instance stats: CPU, memory, I/O • Software infrastructure stats: database, message queue • Application stats: game client, game server, services Make It Easy to Do the Right Thing ™ • Easy, reliable, low-latency • Auto-tagged and searchable Why? • Measurement beats intuition every time; my own intuition is usually wrong  • If you need to ssh into a box, instrumentation failed you
  20. 20. One Team (!) • Act as one team across development, product, operations, etc. • Solve problems instead of blaming and pointing fingers • Political games are not as fun as real-time strategy games 
  21. 21. Everyone Is Responsible for Prod Everyone’s incentives are aligned Everyone is strongly motivated to have solid instrumentation and monitoring
  22. 22. Organization: Learning Culture Learn from mistakes and improve • What did you do -> What did you learn • Take emotion and personalization out of it Encourage iteration and velocity • “Failure is not falling down but refusing to get back up” – Theodore Roosevelt
  23. 23. Google Blame-Free Post- Mortems Post-mortem After Every Incident • Document exactly what happened • What went right • What went wrong Open and Honest Discussion • What contributed to the incident? • What could we have done better? Engineers compete to take personal responsibility (!)
  24. 24. Transition to DevOps Organization • Studios make user-visible games • Services provide common endpoints Training / Retraining • Common bootcamp • Train devs as Ops, Ops as devs You Build It, You Run It • Transition on-call • Use primary / secondary on-call as apprenticeship
  25. 25. Recap: The Game of Operations Cloud Services DevOps
  26. 26. Come Join Us! KIXEYE is hiring in SF, Seattle, Victoria, Brisbane, Amsterdam @randyshoup rshoup@kixeye.com linkedin.com/in/randyshoup slideshare.net/randyshoup

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