How to be WRONG
summary
Claims that being wrong is inevitable and useful, and that chaos engineering should be repackaged as system verification with measurable objectives (for example an availability target like 99%). Provides practical approaches: run game days and automated experiments (Chaos Toolkit, ChaosIQ), surface dark debt, and prioritize fixes based on measured impact. Cites a concrete business metric — roughly $100,000 of lost value per hour of downtime — and historical evidence (Margaret Hamilton anecdote) to show why deliberate experiments work.
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chapters (35)
- 0:00Start
- 25:04What is "Wrong"?
- 26:23And why are we scared of it?
- 26:41"an injurious, unfair, or unjust act"...
- 26:52action or conduct inflicting harm without due provocation or just cause
- 27:04a violation or invasion of the legal rights of another
- 27:19When are we ever wrong?
- 27:35the state of being mistaken or incorrect
- 27:47We're wrong all the time.
- 29:08Why is wrong scary?
- 29:26Risk?
- 30:13Striving for Reliability
- 31:21Feature Velocity VS. Reliability
- 32:39But ... Microservices!?
- 33:00What about tests? gates? pipelines? isolation?
- 34:30A Story...
- 38:02And it gets worse...
- 38:26Dark Debt...
- 41:46Bad news...
- 41:59Microservices-based systems tend to look like...
- 42:10Reactions?
- 42:47Blame.
- 46:42A better reaction?
- 46:53Being wrong is a key software skill
- 49:57Make it Safe(r) to be wrong.
- 50:21Technical Robustness
- 50:49Zero Blame
- 53:49Deliberately Practice Being Wrong
- 54:17"prepare for undesirable circumstances" - John Allspaw
- 54:31Invest in Resilience
- 55:56Resilience is a Learning Loop
- 56:57"Never Let an Outage Go To Waste" - Casey Rosenthal
- 58:01Being Wrong can be a super power, if it leads to learning
- 58:11Pre-mortem, Deliberate Practice
- 58:44ChaosIQ ready for Early Access!
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