Chaos as a step
Experiments run through a connector such as Litmus as a governed stage in your pipeline.
Quality
Resilience Testing
Prove your services recover before your users find out
Run chaos experiments through a connector such as Litmus to prove your services actually recover from failure, then gate releases on that resilience evidence. You see how a service behaves under stress before it ships. This is an emerging capability orchestrated through a connector.
- Proof that a service recovers from induced failure before it ships
- A recorded history of resilience behavior tied to every release
- A consistent recovery standard applied across services through policy as code
The problem
You test your services before shipping, but testing that a service handles load is not the same as proving it recovers when something underneath it fails. Without a chaos step in the pipeline, you find out about recovery gaps when your users do, not before.
Without IntegraCI
- Chaos experiments run ad hoc, outside the pipeline
- No gate stops a fragile service from shipping
- Recovery behavior undocumented and hard to verify
- Each team decides for itself whether to test resilience
With IntegraCI
- Chaos experiments run as a governed step in your pipeline
- Releases advance only when recovery evidence meets your tolerances
- Each experiment leaves a record of how the service behaved
- Policy as code defines the recovery standard, applied the same way every time
What you get
Gate on recovery
Releases advance only when a service demonstrates it recovers within your tolerances.
Evidence you keep
Each experiment leaves a record of how the service behaved under induced failure.
Connector-orchestrated
IntegraCI drives the chaos tool you connect rather than running failures on its own.
How it works
- 1
Connect a chaos tool
Link a connector such as Litmus to define the experiments your services should survive.
- 2
Run the experiment
The platform triggers the chaos run as a step and collects the recovery evidence.
- 3
Gate on resilience
You release only when the evidence shows the service recovers as expected.
How it stays governed
The same gates everyone passes, applied here.
Gated by policy
Recovery standards are expressed as policy as code. Before a release may advance, the platform evaluates the evidence returned by the chaos experiment against the tolerances you define. A service that does not demonstrate recovery within those bounds is blocked, and the same rule applies every time the experiment runs.
Recorded, tamper-evident
Each chaos experiment writes its outcome once to a tamper-evident audit trail, recording what was induced, how the service behaved, and whether it met the recovery standard. That record travels with the release so you can show, at any point, what evidence backed a decision to ship.
Works with your stack
Connect the tools you already run.
Chaos tools such as Litmus connect through the connector framework; the experiment runs as a pipeline step alongside your existing CI/CD and observability tooling.
- Akuity
- Amazon Web Services
- Buildkite
- CircleCI
- CNCF Tekton
- Drone CI
- Harness
- Jenkins
- Better Stack
- Datadog
- Grafana
- OpenCost
- OpenTelemetry
- Pixie
- Polar Signals
- Sentry
- Appium project
- Chaos Mesh
- +7 more
Who it’s for
Where teams reach for it.
Gate a critical service release on recovery proof
Before a payment or authentication service ships, the pipeline runs a chaos experiment and holds the release until the service demonstrates it recovers within the defined window. A fragile build cannot reach production by accident.
Build an evidence trail for regulated environments
Teams in regulated industries need to show auditors that services were tested for failure scenarios, not just functional correctness. Each chaos experiment leaves a tamper-evident record that maps directly to the release it covered.
Standardize resilience expectations across services
When different teams set their own informal standards for what counts as acceptable recovery, the bar drifts. Expressing tolerances as policy as code gives every service the same baseline and makes gaps visible before they reach production.
Questions, answered.
Does IntegraCI replace my chaos engineering tool?
No. IntegraCI connects to the chaos tool you already run, such as Litmus, and drives it as a governed step in your pipeline. Your tool runs the experiments; IntegraCI collects the evidence and decides whether a release may proceed.
Which chaos tools does this work with?
IntegraCI orchestrates chaos tools through its connector framework. Litmus is the reference connector for this capability. Any tool that can be reached through a connector and return recovery evidence can be wired into the gate.
Is this capability ready for production use?
Resilience testing is an emerging capability in IntegraCI. The orchestration and gate mechanics are in place, and the connector framework is live. The right question is whether your connected chaos tool and your recovery tolerances are defined, not whether the platform can drive them.
Who defines what counts as a passing recovery?
You do. The recovery tolerances are expressed as policy as code, so your team decides what the service must demonstrate before a release is allowed to advance. IntegraCI enforces whatever standard you set, consistently, on every run.
Put Resilience Testing on your stack.
Request a demo, or read the docs to see how it fits the tools you already run.