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
Chaos-Test Your AI Agent Deterministic and live-proxy fault injection for agent clients
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 Current capability boundaries, verification policy, priorities, and non-goals
MCP over HTTP Streamable HTTP transport for container and fleet integrations
Tumult 1.0 Historical release context for the first stable release
Bring Your Own Agent tumult recommend --agent: Claude Code / Codex enhance recommendations and propose validated experiments
Chaos Without Root tumult-net: a userspace TCP chaos proxy; latency, throttling, corruption, and connection kills with no root, no tc, no docker
Your Agent Is Now a First-Class Tumult Operator The MCP server grows to 24 tools with annotations, structured output schemas, tumult:// resources; and a run→ingest→recommend loop that closes over MCP
ChaosGraph: Your Agent Stops Re-Reading Journals A typed knowledge graph over chaos data, built from journals on ingest and served to agents over MCP; a targeted answer stays bounded while journal-reading grows every run (~8× more compact per run, ~20× on store-wide queries)
Agentic Trajectories: Chaos Engineering for Agents That Think in Steps Multi-turn agent-graph fault modeling; inject a fault at one step and watch it cascade across a trajectory, with whole-trajectory contracts and four agentic subscores. The failure modes single-call testing can’t see
Native Windows Faults in Tumult 2.12 Scope, verification model, and limitations for process-kill, CPU-stress, and firewall-blackhole faults
Where Compliance Breaks: Lineage on the Service Map declared service topology + compliance lineage: see where controls break on the map, which fault caused it, and where the recommender says to inject next; three live proof runs from the demo stack
Autopilot: Decisions With an Audit Trail Deterministic recommendations, the 14-rule safety gate, earned autonomy, lineage, and evidence storage
Get Started with the Tumult Web UI The governance half: tumultd bootstrap, RBAC login, registry → approvals → run → e-stop → audit, the authoring wizard, schedules, GameDays, webhooks
Get Started with Krönika The analytics half: OTLP ingest, the single-writer DuckDB lake, parquet export, semantic metrics, compliance reports, and Grafana/SigNoz alongside

Table of contents

Tumult is open source under the Apache-2.0 license.