How to make technical decisions?
summary
Teams use four concrete metrics — design, learning curve, runtime and support — and rely on measurable signals like five years of community maturity, GitHub/Stack Overflow popularity, TechEmpower benchmarks, static code analysis and open-vulnerability lists. Practical tooling includes Google Trends, AWS pricing calculator, Tech Radar and Architecture Decision Records; feature toggles, A/B tests and parallel set-based experiments let choices be deferred. Example decisions favor Docker Compose vs Kubernetes for quick delivery; an availability graph is used for uptime math and a strict 1–1.5 month timebox prevents over-investigation.
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chapters (13)
- 0:00Introduction
- 1:07Why technical decisions matter
- 3:32War stories of bad choices
- 5:40Consequences of wrong choices
- 8:29Metrics for good selection
- 12:03Measuring technology fit
- 14:51Picking a container orchestrator
- 16:18Advanced decision techniques
- 19:50Collaborative decision-making
- 22:23Psychology of decisions
- 25:36Recipe for decisions
- 27:22Summary
- 28:38Q&A
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