launchdarkly-guarded-rollout
Configure guarded rollouts with progressive traffic increases, metric monitoring, and automatic rollback. Use when releasing features gradually with safety thresholds.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/launchdarkly/ai-tooling --skill launchdarkly-guarded-rollout- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads launchdarkly-guarded-rollout automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
LaunchDarkly Guarded Rollouts
You're using a skill that will guide you through configuring guarded rollouts in LaunchDarkly. Your job is to design rollout stages, select monitoring metrics, configure regression thresholds, and start the rollout.
Prerequisites
This skill requires the remotely hosted LaunchDarkly MCP server to be configured in your environment.
Required MCP tools:
start-guarded-rollout-- start a progressive rollout with monitoringget-flag-- inspect the flag and its variationslist-metrics-- find metrics to monitor during the rollout
Optional MCP tools:
stop-guarded-rollout-- halt an active rollout immediatelytoggle-flag-- ensure the flag is turned on before startingcreate-metric-- create metrics if they don't exist
Core Concepts
What Are Guarded Rollouts?
A guarded rollout progressively increases traffic to a new feature flag variation through a series of stages. At each stage, LaunchDarkly monitors selected metrics for regressions. If a regression is detected, the rollout can automatically pause and notify the team — or even roll back.
Key Components
| Component | Description |
|---|---|
| Test variation | The new variation being rolled out |
| Control variation | The existing/baseline variation |
| Stages | Steps with increasing traffic percentage and monitoring windows |
| Metrics | What to monitor for regressions (error rate, latency, etc.) |
| Regression threshold | How much a metric can degrade before triggering action |
| On regression | Whether to notify, rollback, or both when a threshold is breached |
Rollout Weight Units
Rollout weights use thousandths (basis points):
1000= 1%10000= 10%50000= 50%100000= 100%
Monitoring Window
The monitoring window is specified in milliseconds:
3600000= 1 hour86400000= 24 hours604800000= 7 days
Core Principles
- Start Small: Begin with a low percentage (1-5%) to catch issues early
- Monitor What Matters: Choose metrics that reflect user experience
- Set Realistic Thresholds: Too tight = false alarms; too loose = missed regressions
- Allow Time: Each stage needs enough monitoring time for signal to emerge
- Have a Rollback Plan: Always configure at least notification on regression
Workflow
Step 1: Prepare
Before starting a guarded rollout:
- Use
get-flagto inspect the flag — note the variation IDs for test and control - Use
list-metricsto find metrics suitable for monitoring - Ensure the flag is on in the target environment (use
toggle-flagif needed) - Confirm there's no active guarded rollout on this flag already
Step 2: Design Stages
Plan the rollout progression. A typical pattern:
| Stage | Traffic | Monitoring Window | Purpose |
|---|---|---|---|
| 1 | 1% | 1 hour | Smoke test — catch obvious crashes |
| 2 | 10% | 24 hours | Early signal on metrics |
| 3 | 50% | 24 hours | Confidence building |
| 4 | 100% | 24 hours | Full rollout with monitoring |
Step 3: Configure Metrics
Select metrics that indicate problems:
| Metric Type | Example | Threshold | Action |
|---|---|---|---|
| Error rate | api-error-rate | 0.05 (5% increase) | Rollback |
| Latency | p99-response-time | 0.2 (20% increase) | Notify |
| Conversion | checkout-completed | 0.1 (10% decrease) | Notify + Rollback |
Step 4: Start the Rollout
Use start-guarded-rollout:
{
"projectKey": "my-project",
"flagKey": "new-checkout-flow",
"environmentKey": "production",
"testVariationId": "variation-id-for-new-flow",
"controlVariationId": "variation-id-for-current-flow",
"randomizationUnit": "user",
"stages": [
{"rolloutWeight": 1000, "monitoringWindowMilliseconds": 3600000},
{"rolloutWeight": 10000, "monitoringWindowMilliseconds": 86400000},
{"rolloutWeight": 50000, "monitoringWindowMilliseconds": 86400000},
{"rolloutWeight": 100000, "monitoringWindowMilliseconds": 86400000}
],
"metrics": [
{
"metricKey": "api-error-rate",
"onRegression": {"notify": true, "rollback": true},
"regressionThreshold": 0.05
},
{
"metricKey": "checkout-completed",
"onRegression": {"notify": true, "rollback": false},
"regressionThreshold": 0.1
}
]
}
Step 5: Verify
- Use
get-flagto confirm the guarded rollout is active - Check that the flag shows the rollout configuration in the environment
- Monitor for any immediate regression notifications
Report results:
- Guarded rollout started with N stages
- M metrics being monitored
- First stage at X% traffic for Y hours
Stopping a Rollout
If issues arise or you need to halt the rollout:
{
"projectKey": "my-project",
"flagKey": "new-checkout-flow",
"environmentKey": "production"
}
This immediately stops the progressive rollout and locks the flag at its current state.
Edge Cases
| Situation | Action |
|---|---|
| Flag is off | Turn it on first with toggle-flag — rollouts require the flag to be on |
| Active rollout exists | Stop it first with stop-guarded-rollout before starting a new one |
| No suitable metrics | Create metrics first with create-metric |
| Approval required | If the environment requires approvals, the tool will return an approval URL |
What NOT to Do
- Don't start a guarded rollout on a flag that's turned off
- Don't skip the monitoring window design — rushing through stages defeats the purpose
- Don't set regression thresholds to 0 — small fluctuations are normal
- Don't forget to configure at least one metric — a rollout without monitoring is just a regular rollout
FAQ
What does the launchdarkly-guarded-rollout skill do?
Configure guarded rollouts with progressive traffic increases, metric monitoring, and automatic rollback. Use when releasing features gradually with safety thresholds.
How do I install launchdarkly-guarded-rollout?
Run npx skills add https://github.com/launchdarkly/ai-tooling --skill launchdarkly-guarded-rollout in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/launchdarkly-guarded-rollout/ (personal) or .claude/skills/launchdarkly-guarded-rollout/ (project).
Which AI agents can use launchdarkly-guarded-rollout?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is launchdarkly-guarded-rollout safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains launchdarkly-guarded-rollout?
It is published by launchdarkly in launchdarkly/ai-tooling. It has 2,727 recorded installs.
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