Blog

The Tumult blog series covers the platform end-to-end, from first principles to advanced use cases.

Post	Topic
Introducing Tumult	What Tumult is, why it was built, and how it differs from existing tools
The AI Advantage	How TOON’s token efficiency enables AI-native chaos analysis
Built-In Observability	OpenTelemetry spans and `resilience.*` attributes — always on, zero config
The Plugin System	Script plugins, native plugins, discovery order, and writing your own
The Experiment Format	Deep dive into TOON experiment structure, providers, and tolerances
The Analytics Pipeline	DuckDB + Arrow + Parquet: SQL over your chaos history
Kubernetes Chaos	`tumult-kubernetes`: pod delete, node drain, deployment scaling
Statistical Baselines	IQR, percentile, mean/stddev — replacing magic numbers with evidence
Compliance as Code	DORA, NIS2, PCI-DSS 4.0 — experiments as regulatory evidence
Chaos Under Load	Combining `tumult-network` and `tumult-loadtest` for realistic fault testing
The Full Span Waterfall	Real SigNoz traces from a live Tumult experiment — the observability proof
Load During Chaos	k6 load testing concurrent with fault injection — proving disruption in numbers
GameDay Is Here	Coordinated campaigns with resilience scoring — 4/4 PASS, Score 1.00, COMPLIANT
The Road Ahead	What’s delivered (Phases 0-8), what’s next, the full series index

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