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Scaling For Planned Events

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Brian Akins
September 25, 2014

Scaling For Planned Events

Theory, Practice, and Aftermath

Brian Akins

September 25, 2014

Transcript

16 slides
  1. About @bakins • OmniTI - Senior Principal Architect • Horrible

    public speaker • Old school C guy • Operations and Development • Wife and four kids in Atlanta, Georgia
  2. What is a “Planned Event” • Event on existing site

    • Single or repeating • Immovable dates • Elections, sporting events, etc.
  3. Ideally • Event handled via normal site operations • Business

    goals clearly defined • Clearly defined schedule • Realistic traffic/capacity models
  4. Reality • Competing business goals • Heroic scaling efforts often

    needed • Last minute feature additions • Real money tied to sponsorships • Can’t be tested in production until the event
  5. Cache Everything? • If possible… • Introduce caching layer in

    proxy mode early • Is your site really “dynamic”? • Need buy-in from all parties: dev, biz, ops, etc
  6. Feature Creep • Company X will give us $Y is

    we do feature Z • Deals are usually signed late • Competing priorities • Testing schedule compressed - or eliminated
  7. Degradation Planning • Decide before the event - you only

    get one chance • What features are most “important”? • Most impactful • Playbook: if/when X, then Y • Feature flags • “Benevolent dictator”
  8. Dependencies • Know your dependencies • Direct • Indirect •

    Third party • Find the bottlenecks • Include these services in your planning
  9. Event Operations • Physical and virtual “war rooms” • Business

    liaison • Do a post-mortem, good or bad • Archive metrics
  10. Easy One • Sports site using PHP-platform • Once a

    year event • Poor cache-invalidation methods • increase TTL before event, etc
  11. “Waiting Room” • “Legacy” video delivery services • Capacity reservations

    • Do not return an error to user • “Distract” the user
  12. Unexpected ending • Last episode of popular TV show •

    Fragile stack • “Controversial” ending to show • Two orders of magnitude more traffic on site than expected

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