Launchdarkly Guarded Rollout

launchdarkly/ai-tooling/skills/feature-flags/launchdarkly-guarded-rollout

作者 launchdarkly2fc544d3140fApache-2.026 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫昨天更新

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

僅含說明DevOps & Cloud
AI 產生的概覽

指導設定 LaunchDarkly 受控發布,包含分階段放量、指標監控與回滾門檻。

功能
此技能引導代理在 LaunchDarkly 中設定受控發布:檢查功能旗標、選擇測試與對照變體,並設計帶有監控視窗的漸進式流量階段。它協助挑選監控指標與回歸門檻,接著呼叫受控發布工具啟動發布並進行驗證。它也涵蓋停止進行中的發布,以及處理旗標未開啟或缺少指標等邊界情況。
適用情境
適用於逐步發布功能,並希望設定安全門檻以便在出現回歸時暫停、通知或回滾的情況。適合已使用 LaunchDarkly 功能旗標、需要規劃分階段放量與監控的團隊。
執行需求
需要在環境中設定遠端託管的 LaunchDarkly MCP 伺服器,並提供 start-guarded-rollout、get-flag、list-metrics 等工具,以及選用的 stop-guarded-rollout、toggle-flag、create-metric。不包含指令碼,僅為說明文件。

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

ComponentDescription
Test variationThe new variation being rolled out
Control variationThe existing/baseline variation
StagesSteps with increasing traffic percentage and monitoring windows
MetricsWhat to monitor for regressions (error rate, latency, etc.)
Regression thresholdHow much a metric can degrade before triggering action
On regressionWhether 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:

StageTrafficMonitoring WindowPurpose
11%1 hourSmoke test — catch obvious crashes
210%24 hoursEarly signal on metrics
350%24 hoursConfidence building
4100%24 hoursFull rollout with monitoring

Step 3: Configure Metrics

Select metrics that indicate problems:

Metric TypeExampleThresholdAction
Error rateapi-error-rate0.05 (5% increase)Rollback
Latencyp99-response-time0.2 (20% increase)Notify
Conversioncheckout-completed0.1 (10% decrease)Notify + Rollback

Step 4: Start the Rollout

Use start-guarded-rollout:

json
{  "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:

json
{  "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

SituationAction
Flag is offTurn it on first with toggle-flag — rollouts require the flag to be on
Active rollout existsStop it first with stop-guarded-rollout before starting a new one
No suitable metricsCreate metrics first with create-metric
Approval requiredIf 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

來源與署名

來源:launchdarkly/ai-tooling位於skills/feature-flags/launchdarkly-guarded-rollout提交2fc544d

授權條款: Apache-2.0

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

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