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Configure guarded rollouts with progressive traffic increases, metric monitoring, and automatic rollback. Use when releasing features gradually with safety thresholds.

Use this Skill: https://skilld.dev/gh/launchdarkly/agent-skills/launchdarkly-guarded-rollout

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SKILL.md

≈49 tokens always: the name and description. ≈1.5k when used: this file.

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 monitoring
  • get-flag -- inspect the flag and its variations
  • list-metrics -- find metrics to monitor during the rollout

Optional MCP tools:

  • stop-guarded-rollout -- halt an active rollout immediately
  • toggle-flag -- ensure the flag is turned on before starting
  • create-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 hour
  • 86400000 = 24 hours
  • 604800000 = 7 days

Core Principles

  1. Start Small: Begin with a low percentage (1-5%) to catch issues early
  2. Monitor What Matters: Choose metrics that reflect user experience
  3. Set Realistic Thresholds: Too tight = false alarms; too loose = missed regressions
  4. Allow Time: Each stage needs enough monitoring time for signal to emerge
  5. Have a Rollback Plan: Always configure at least notification on regression

Workflow

Step 1: Prepare

Before starting a guarded rollout:

  1. Use get-flag to inspect the flag — note the variation IDs for test and control
  2. Use list-metrics to find metrics suitable for monitoring
  3. Ensure the flag is on in the target environment (use toggle-flag if needed)
  4. 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

  1. Use get-flag to confirm the guarded rollout is active
  2. Check that the flag shows the rollout configuration in the environment
  3. 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

Source: SKILL.md on GitHub

No alerts3mo3 checks · Risk SAFE
  • Gen Agent Trust Hub3mo

    This skill provides structural guidance and workflow instructions for managing feature flag rollouts through LaunchDarkly. It uses a series of specialized tools to monitor metrics and adjust traffic percentages progressively. No security risks or malicious behaviors were found.

  • Socket3mo

    No alerts

  • Snyk3mo

    Risk: LOW · No issues

Signed by skilld at 8cecc56. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 2 days ago.

Activeupdated 5 months ago
compatibility
Requires the remotely hosted LaunchDarkly MCP server
metadata
{
  "author": "launchdarkly",
  "version": "0.1.0"
}
  • launchdarkly
  • feature-flags
  • rollouts
  • monitoring
  • regression-detection
  • progressive-delivery
  • metrics

README badge

README badge for launchdarkly/agent-skills/launchdarkly-guarded-rollout

Configures progressive feature flag rollouts in LaunchDarkly with staged traffic increases, metric monitoring, and automatic rollback on regression detection. Useful for safely releasing features to production by starting at low traffic, monitoring key metrics like error rate or latency, and advancing through stages only when thresholds hold.

Generated from the current SKILL.md.

Does this skill work with LaunchDarkly flags that are currently off?
No. The flag must be turned on in the target environment before starting a guarded rollout. Use the `toggle-flag` tool to enable it first.
Can I run multiple guarded rollouts on the same flag at the same time?
No. You must stop any active guarded rollout with `stop-guarded-rollout` before starting a new one on the same flag.
What happens if a regression is detected during a rollout?
The rollout either pauses and notifies the team, automatically rolls back, or both — depending on the `onRegression` configuration for each metric. You can also stop it manually with `stop-guarded-rollout`.
What metrics can I monitor during a rollout?
You can monitor any metric already in LaunchDarkly (error rate, latency, conversion rate, etc.) using `list-metrics`. If a suitable metric doesn't exist, create it first with `create-metric`.
Does this skill require the LaunchDarkly MCP server?
Yes. The skill requires the remotely hosted LaunchDarkly MCP server to be configured in your environment to access tools like `start-guarded-rollout` and `get-flag`.

Generated from the current SKILL.md. These answers refresh after source changes.