Queues: An Invisible Money Drain
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Queues introduce delays and economic costs in product development. Common queues include features waiting to be designed/developed/tested/released and bugs waiting for triage/fixing/verification. Large queues increase cycle times, variability, and require management. They also delay feedback and hurt morale. The presenter advocates reducing queues by using swarming, generalizing work across teams rather than specializing, obliterating unnecessary queues, and reducing testing batch sizes from months to weeks or even days through continuous delivery. Case studies show how these techniques helped the presenter's company ship features more quickly while maintaining quality.
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Queues: An Invisible Money Drain
- 1. Queues: An Invisible Money Drain Phil Sarin VP Engineering, GameChanger Media @philsarin http://216ways.net
- 2. “It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so. — Mark Twain
- 3. Things I once believed You shouldn’t release often because releases have high overhead. You need to track all of your bugs. Slack is bad. Your team should be busy. Specialists will always be more productive than generalists.
- 4. The Biggest Misunderstanding: We think queues are free.
- 5. What we’ll cover tonight What a queue is Identifying the queues in your organization Tactics for handling queues Some war stories
- 6. Part 1: Queues and why they matter Flickr: Jeff Turner
- 7. “Queues are the root cause of the majority of economic waste in product development.” — Donald G. Reinertsen
- 8. Examples of queues Feature Queues Waiting to get designed Waiting to get developed Waiting for testing Waiting to get released Waiting to get validated Bug Queues Waiting for triage Waiting to get fixed Waiting to get verified Waiting for release
- 9. What’s wrong with big queues? Big queues increase cycle time and delay cost Big queues increase variability Big queues require management Big queues delay feedback Big queues hurt morale
- 10. The conservative team vs The aggressive team
- 16. 1 year 3 months vs 3 months 3 months 3 months vs
- 17. Why small batches are (usually) better Realize benefits sooner Faster feedback Higher motivation Less schedule slippage
- 18. Old School: Releases are expensive so let’s batch up work for release. New School: Let’s drive down the cost of releases so that we can release more often.
- 19. Queue takeaways Queues introduce delay. Queues have economic and psychological costs. High capacity utilization drives up queue size. Small batches can reduce the cost of queues.
- 20. Part 2: How we apply this theory at GameChanger Flickr: Jeff Turner
- 22. How we’ve managed queues 1. Swarm 2. Generalize queue handling 3. Obliterate queues 4. Reduce testing batch sizes
- 23. 1. Swarm
- 25. The stages of swarming 1. Skepticism/suspension of disbelief 2. Guilt and busywork 3. Scope blows up 4. The “surge capacity effect”
- 26. Announcements Invite Tools Alerts Announcements Invite Tools Alerts vs
- 27. No silver bullet
- 28. 2. Generalize Flickr: Kaleb Fulgham
- 29. Multiple queues, 1 server each Single queue, Single server Single queue, pool of servers
- 30. Multiple queues, 1 server each Single queue, Single server Single queue, pool of servers Sustained huge queues are least likely
- 31. Pressures to specialize A specialty differentiates your business “I don’t want to touch that code!” Initial builder owns it forever. Early adopters become de-facto specialists. Some people want specialist careers.
- 32. Resisting specialist queues Outsource non-core specialties Despecialize Challenge someone Staff up
- 33. Generalist teams and morale
- 35. 4. Reduce testing batch sizes
- 36. That time we missed our deadline by four months
- 37. 2 months development 2 weeks testing 2 months development 2 weeks testing 4 months bug-driven development
- 38. 2 weeks dev test 2 weeks dev test 2 weeks dev test 2 weeks dev test 2 weeks dev test Can we reduce this batch size further? Our first batch size reduction
- 39. 2 weeks dev test 2 weeks dev test 2 weeks dev test 2 weeks dev test 2 weeks dev test Can we reduce this batch size further?
- 40. 2 weeks dev+test T 2 weeks dev+test T 2 weeks dev+test T 2 weeks dev+test T 2 weeks dev+test T 2 weeks dev+test T Continuous pre-release delivery?
- 42. It didn’t work
- 44. How we fixed it More automated test coverage Instituted small batch manual testing process Hired more testers
- 46. Release Days 5.15 21 5.14 14 5.13 26 5.12 21 5.11 23 5.10 4 5.9 66 5.8 7 5.6 21 It worked, mostly, eventually
- 47. Parting Thoughts Flickr: Jeff Turner
- 48. Things I once believed You shouldn’t release often because releases have high overhead. You need to track all of your bugs. Slack is bad. Your team should be busy. Specialists will always be more productive than generalists.
- 49. Mindset shifts Being busy vs being productive Individual vs team Rituals vs principles
- 50. Takeaways Queues are real and expensive You should know where your queues are There are a bunch of ways to reduce the cost of queues
- 51. Further Reading The Principles of Product Development Flow, Donald G. Reinertsen “Software Inventory” by Joel Spolsky: http://www.joelonsoftware.com/ items/2012/07/09.html “How we fixed more bugs by deleting our bug DB” and “Building around generalists” on my blog (216ways.net)