Initial commit
This commit is contained in:
Zhongwei Li
12
.claude-plugin/plugin.json
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12
.claude-plugin/plugin.json
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{
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"name": "feature-flag-manager",
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"description": "ClaudeForge Enterprise Feature Flag Architect delivering comprehensive progressive rollout methodologies, A/B testing frameworks, canary deployment strategies, and experimentation platforms that transform risky releases into controlled, data-driven feature delivery systems",
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"version": "1.0.0",
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"author": {
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"name": "ClaudeForge Community",
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"url": "https://github.com/claudeforge/marketplace"
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},
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"commands": [
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"./commands"
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]
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}
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3
README.md
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3
README.md
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# feature-flag-manager
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ClaudeForge Enterprise Feature Flag Architect delivering comprehensive progressive rollout methodologies, A/B testing frameworks, canary deployment strategies, and experimentation platforms that transform risky releases into controlled, data-driven feature delivery systems
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718
commands/feature-flag-manager.md
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718
commands/feature-flag-manager.md
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---
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allowed-tools: Bash, Read, Write, Edit, Grep, Glob
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description: ClaudeForge feature flag management specialist for LaunchDarkly, Unleash, and progressive feature rollouts.
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---
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# ClaudeForge Feature Flag Manager
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ClaudeForge intelligent feature flag management system that orchestrates progressive feature rollouts, A/B testing, canary releases, and kill switches with comprehensive analytics, team coordination, and risk mitigation strategies.
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## Purpose
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Transform feature deployment from risky big-bang releases to controlled, data-driven rollouts that enable rapid iteration, minimize blast radius, and provide instant rollback capabilities across distributed systems.
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## Features
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- **Flag Lifecycle Management**: Create, configure, and retire feature flags with governance
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- **Progressive Rollouts**: Gradual feature deployment with user targeting and percentage-based distribution
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- **A/B Testing**: Experimentation framework with statistical significance tracking
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- **Kill Switches**: Emergency feature disable with instant propagation
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- **User Targeting**: Sophisticated targeting rules based on attributes, segments, and context
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- **Analytics Integration**: Real-time feature usage metrics and conversion tracking
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- **Multi-Environment Support**: Consistent flag management across dev, staging, and production
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- **Audit Trail**: Complete change history for compliance and debugging
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## Usage
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```bash
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/feature-flag-manager [command] [options]
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```
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Target: $ARGUMENTS (if specified, otherwise manage all flags in current environment)
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### Flag Management Commands
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**Create Feature Flag:**
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```bash
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/feature-flag-manager create --name=new-checkout-flow --type=release --environments=all
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```
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Creates new feature flag with:
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- Unique flag key generation
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- Default variation configuration
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- Environment-specific settings
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- Access control and permissions
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- Documentation requirements
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- Review and approval workflow
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- Integration with issue tracker
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- Automated test flag generation
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**Update Flag Configuration:**
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```bash
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/feature-flag-manager update --flag=new-checkout-flow --targeting=enabled --rules=beta-users
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```
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Updates flag configuration including:
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- Targeting rules and prerequisites
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- User segment assignments
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- Percentage rollout adjustments
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- Variation value modifications
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- Fallback configuration
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- Environment synchronization
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- Change tracking and audit
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- Team notification system
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**Delete Feature Flag:**
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```bash
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/feature-flag-manager delete --flag=old-feature --check-usage --archive
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```
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Safely removes feature flags:
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- Usage analysis across codebase
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- Dependent feature detection
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- Staged deletion process
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- Code cleanup suggestions
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- Archive for audit trail
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- Team notification
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- Technical debt tracking
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- Migration guide generation
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### Rollout Strategies
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**Percentage Rollout:**
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```bash
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/feature-flag-manager rollout --flag=new-ui --percentage=25 --increment=25 --interval=1h
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```
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Implements progressive rollout:
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- Initial percentage deployment
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- Automated incremental increases
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- Monitoring-based progression
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- Error rate threshold checks
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- Automatic pause on issues
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- Rollback triggers
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- User consistency (sticky assignments)
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- Schedule-based progression
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**Targeted Rollout:**
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```bash
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/feature-flag-manager rollout --flag=premium-features --segment=enterprise-users --context=subscription-tier
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```
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Deploys to specific user segments:
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- User attribute-based targeting
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- Custom segment definitions
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- Multi-condition rule sets
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- Geographic targeting
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- Device/platform targeting
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- Account-level overrides
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- Test user exclusions
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- Gradual segment expansion
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**Ring Deployment:**
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```bash
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/feature-flag-manager rollout --flag=api-v2 --strategy=rings --rings="internal,beta,ga"
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```
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Implements ring-based deployment:
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- Internal team ring (5% of users)
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- Beta user ring (20% of users)
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- General availability ring (100% of users)
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- Automated progression gates
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- Ring-specific monitoring
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- Quality gates between rings
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- Fast ring rollback capability
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- Documentation updates per ring
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### A/B Testing
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**Create Experiment:**
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```bash
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/feature-flag-manager experiment create --name=checkout-optimization --variants=A,B --split=50/50 --duration=14d
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```
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Sets up A/B test with:
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- Variant definition and allocation
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- Statistical power calculation
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- Sample size requirements
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- Success metric definition
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- Control group preservation
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- Random assignment algorithm
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- Consistent user experience
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- Early stopping criteria
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**Analyze Results:**
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```bash
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/feature-flag-manager experiment analyze --name=checkout-optimization --metrics=conversion,revenue
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```
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Provides statistical analysis:
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- Conversion rate comparison
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- Statistical significance testing
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- Confidence interval calculation
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- Revenue impact analysis
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- User engagement metrics
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- Segment-based breakdowns
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- Visualization and reporting
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- Winner recommendation
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**Graduate Experiment:**
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```bash
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/feature-flag-manager experiment graduate --name=checkout-optimization --winner=B --cleanup-code
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```
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Completes experiment lifecycle:
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- Winner deployment to 100%
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- Loser variant removal
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- Code cleanup automation
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- A/B test flag removal
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- Documentation updates
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- Team communication
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- Learning documentation
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- Next iteration planning
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### Kill Switch Operations
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**Emergency Disable:**
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```bash
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/feature-flag-manager kill-switch --flag=problematic-feature --immediate --notify-team
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```
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Instantly disables feature:
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- Zero-downtime flag flip
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- Immediate CDN/cache invalidation
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- Real-time client notification
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- Automatic team alerts
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- Incident documentation
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- Rollback verification
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- Impact assessment
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- Root cause investigation trigger
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**Scheduled Disable:**
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```bash
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/feature-flag-manager schedule disable --flag=holiday-promotion --date=2024-12-26 --time=00:00:00
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```
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Plans feature deactivation:
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- Scheduled flag changes
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- Timezone-aware execution
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- Pre-execution notifications
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- Automated verification
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- Rollback plan preparation
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- Communication automation
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- Metric baseline capture
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- Post-disable monitoring
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## Integration Platforms
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### LaunchDarkly Integration
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**Configuration:**
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```javascript
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// launchdarkly-config.js
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import * as LaunchDarkly from 'launchdarkly-node-server-sdk';
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const ldClient = LaunchDarkly.init(process.env.LAUNCHDARKLY_SDK_KEY, {
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sendEvents: true,
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allAttributesPrivate: false,
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stream: true,
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offline: false
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});
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await ldClient.waitForInitialization();
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export async function evaluateFlag(flagKey, user, defaultValue) {
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try {
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const context = {
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kind: 'user',
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key: user.id,
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email: user.email,
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custom: {
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accountTier: user.subscription,
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signupDate: user.createdAt,
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region: user.region
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}
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};
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return await ldClient.variation(flagKey, context, defaultValue);
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} catch (error) {
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console.error('Flag evaluation error:', error);
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return defaultValue;
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}
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}
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```
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**React Integration:**
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```javascript
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import { withLDProvider, useFlags, useLDClient } from 'launchdarkly-react-client-sdk';
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function App() {
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const { newCheckoutFlow, premiumFeatures } = useFlags();
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const ldClient = useLDClient();
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useEffect(() => {
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// Track feature usage
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if (newCheckoutFlow) {
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ldClient?.track('checkout-flow-viewed', {
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version: 'new'
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});
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}
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}, [newCheckoutFlow, ldClient]);
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return (
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<div>
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{newCheckoutFlow ? <NewCheckout /> : <LegacyCheckout />}
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{premiumFeatures && <PremiumSection />}
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</div>
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);
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}
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export default withLDProvider({
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clientSideID: process.env.REACT_APP_LD_CLIENT_ID,
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user: {
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key: userId,
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email: userEmail,
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custom: {
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subscriptionTier: userTier
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}
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}
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})(App);
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```
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### Unleash Integration
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**Server Configuration:**
|
||||
```javascript
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// unleash-config.js
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const { initialize } = require('unleash-client');
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|
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const unleash = initialize({
|
||||
url: 'https://unleash.example.com/api',
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appName: 'my-application',
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instanceId: process.env.INSTANCE_ID,
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environment: process.env.NODE_ENV,
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customHeaders: {
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Authorization: process.env.UNLEASH_API_TOKEN
|
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},
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strategies: [
|
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{
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||||
name: 'gradualRollout',
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||||
implementation: gradualRolloutStrategy
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},
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{
|
||||
name: 'userWithId',
|
||||
implementation: userTargetingStrategy
|
||||
}
|
||||
]
|
||||
});
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||||
|
||||
unleash.on('ready', () => {
|
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console.log('Unleash client ready');
|
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});
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||||
|
||||
unleash.on('error', (error) => {
|
||||
console.error('Unleash error:', error);
|
||||
});
|
||||
|
||||
function isFeatureEnabled(flagName, context = {}) {
|
||||
return unleash.isEnabled(flagName, context, (name, enabled) => {
|
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// Track feature evaluations
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trackFeatureEvaluation(name, enabled, context);
|
||||
});
|
||||
}
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||||
|
||||
module.exports = { unleash, isFeatureEnabled };
|
||||
```
|
||||
|
||||
**Custom Strategies:**
|
||||
```javascript
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||||
// Custom rollout strategy
|
||||
const gradualRolloutStrategy = {
|
||||
name: 'gradualRollout',
|
||||
execute: (context, parameters) => {
|
||||
const userId = context.userId;
|
||||
const percentage = parseInt(parameters.percentage, 10);
|
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|
||||
// Consistent hashing for user assignment
|
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const hash = murmurhash(userId + parameters.groupId);
|
||||
const bucket = hash % 100;
|
||||
|
||||
return bucket < percentage;
|
||||
}
|
||||
};
|
||||
|
||||
// User segment strategy
|
||||
const segmentStrategy = {
|
||||
name: 'userSegment',
|
||||
execute: (context, parameters) => {
|
||||
const userSegment = context.properties?.segment;
|
||||
const allowedSegments = parameters.segments.split(',');
|
||||
|
||||
return allowedSegments.includes(userSegment);
|
||||
}
|
||||
};
|
||||
```
|
||||
|
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### Split.io Integration
|
||||
|
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**TypeScript Configuration:**
|
||||
```typescript
|
||||
// splitio-config.ts
|
||||
import { SplitFactory } from '@splitsoftware/splitio';
|
||||
|
||||
interface UserContext {
|
||||
id: string;
|
||||
email: string;
|
||||
attributes: Record<string, any>;
|
||||
}
|
||||
|
||||
class FeatureFlagService {
|
||||
private client: any;
|
||||
private isReady: boolean = false;
|
||||
|
||||
async initialize() {
|
||||
const factory = SplitFactory({
|
||||
core: {
|
||||
authorizationKey: process.env.SPLIT_API_KEY!,
|
||||
key: 'customer-id'
|
||||
},
|
||||
scheduler: {
|
||||
impressionsRefreshRate: 60
|
||||
}
|
||||
});
|
||||
|
||||
this.client = factory.client();
|
||||
|
||||
await new Promise((resolve) => {
|
||||
this.client.on(this.client.Event.SDK_READY, () => {
|
||||
this.isReady = true;
|
||||
resolve(true);
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
getTreatment(
|
||||
flagKey: string,
|
||||
user: UserContext,
|
||||
attributes?: Record<string, any>
|
||||
): string {
|
||||
if (!this.isReady) {
|
||||
return 'control';
|
||||
}
|
||||
|
||||
return this.client.getTreatment(
|
||||
user.id,
|
||||
flagKey,
|
||||
{ ...user.attributes, ...attributes }
|
||||
);
|
||||
}
|
||||
|
||||
getTreatmentWithConfig(
|
||||
flagKey: string,
|
||||
user: UserContext
|
||||
): { treatment: string; config: any } {
|
||||
const result = this.client.getTreatmentWithConfig(
|
||||
user.id,
|
||||
flagKey,
|
||||
user.attributes
|
||||
);
|
||||
|
||||
return {
|
||||
treatment: result.treatment,
|
||||
config: result.config ? JSON.parse(result.config) : null
|
||||
};
|
||||
}
|
||||
|
||||
track(
|
||||
eventType: string,
|
||||
user: UserContext,
|
||||
value?: number,
|
||||
properties?: Record<string, any>
|
||||
): boolean {
|
||||
return this.client.track(
|
||||
user.id,
|
||||
'user',
|
||||
eventType,
|
||||
value,
|
||||
properties
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
export const featureFlagService = new FeatureFlagService();
|
||||
```
|
||||
|
||||
## Advanced Targeting Rules
|
||||
|
||||
### User Attribute Targeting
|
||||
|
||||
**Complex Rule Configuration:**
|
||||
```json
|
||||
{
|
||||
"flag": "premium-dashboard",
|
||||
"targeting": {
|
||||
"enabled": true,
|
||||
"rules": [
|
||||
{
|
||||
"id": "enterprise-users",
|
||||
"conditions": [
|
||||
{
|
||||
"attribute": "subscription_tier",
|
||||
"operator": "equals",
|
||||
"value": "enterprise"
|
||||
},
|
||||
{
|
||||
"attribute": "account_age_days",
|
||||
"operator": "greater_than",
|
||||
"value": 30
|
||||
}
|
||||
],
|
||||
"variation": "enabled"
|
||||
},
|
||||
{
|
||||
"id": "beta-testers",
|
||||
"conditions": [
|
||||
{
|
||||
"attribute": "user_id",
|
||||
"operator": "in_segment",
|
||||
"value": "beta-testers-segment"
|
||||
}
|
||||
],
|
||||
"variation": "enabled",
|
||||
"rollout": {
|
||||
"percentage": 50
|
||||
}
|
||||
}
|
||||
],
|
||||
"defaultVariation": "disabled"
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Geographic Targeting
|
||||
|
||||
**Region-Based Rollout:**
|
||||
```javascript
|
||||
const geoTargetingRules = {
|
||||
flag: 'new-payment-provider',
|
||||
rules: [
|
||||
{
|
||||
name: 'US-East-Rollout',
|
||||
conditions: [
|
||||
{ attribute: 'country', operator: 'equals', value: 'US' },
|
||||
{ attribute: 'region', operator: 'in', value: ['us-east-1', 'us-east-2'] }
|
||||
],
|
||||
variation: 'new-provider',
|
||||
percentage: 100
|
||||
},
|
||||
{
|
||||
name: 'US-West-Canary',
|
||||
conditions: [
|
||||
{ attribute: 'country', operator: 'equals', value: 'US' },
|
||||
{ attribute: 'region', operator: 'in', value: ['us-west-1', 'us-west-2'] }
|
||||
],
|
||||
variation: 'new-provider',
|
||||
percentage: 10
|
||||
},
|
||||
{
|
||||
name: 'EU-Regions',
|
||||
conditions: [
|
||||
{ attribute: 'country', operator: 'in', value: ['DE', 'FR', 'GB', 'IT', 'ES'] }
|
||||
],
|
||||
variation: 'old-provider',
|
||||
percentage: 100
|
||||
}
|
||||
],
|
||||
defaultVariation: 'old-provider'
|
||||
};
|
||||
```
|
||||
|
||||
### Time-Based Targeting
|
||||
|
||||
**Scheduled Feature Activation:**
|
||||
```javascript
|
||||
function evaluateTimeBasedFlag(flagConfig, currentTime) {
|
||||
const schedule = flagConfig.schedule;
|
||||
|
||||
// Check if current time is within activation window
|
||||
if (schedule.startDate && currentTime < new Date(schedule.startDate)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
if (schedule.endDate && currentTime > new Date(schedule.endDate)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Check day of week restrictions
|
||||
if (schedule.daysOfWeek) {
|
||||
const currentDay = currentTime.getDay();
|
||||
if (!schedule.daysOfWeek.includes(currentDay)) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
// Check time of day restrictions
|
||||
if (schedule.timeRange) {
|
||||
const currentHour = currentTime.getHours();
|
||||
const startHour = schedule.timeRange.start;
|
||||
const endHour = schedule.timeRange.end;
|
||||
|
||||
if (currentHour < startHour || currentHour >= endHour) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
return true;
|
||||
}
|
||||
|
||||
// Example usage
|
||||
const blackFridayFlag = {
|
||||
name: 'black-friday-deals',
|
||||
schedule: {
|
||||
startDate: '2024-11-29T00:00:00Z',
|
||||
endDate: '2024-12-02T23:59:59Z',
|
||||
daysOfWeek: [5, 6, 0], // Friday, Saturday, Sunday
|
||||
timeRange: { start: 0, end: 24 }
|
||||
}
|
||||
};
|
||||
```
|
||||
|
||||
## Monitoring and Analytics
|
||||
|
||||
### Feature Usage Metrics
|
||||
|
||||
**Analytics Integration:**
|
||||
```javascript
|
||||
import { trackFeatureUsage } from './analytics';
|
||||
|
||||
class FeatureFlagAnalytics {
|
||||
constructor(analyticsClient) {
|
||||
this.analytics = analyticsClient;
|
||||
this.flagEvaluations = new Map();
|
||||
}
|
||||
|
||||
trackEvaluation(flagKey, variation, user) {
|
||||
// Track flag evaluation
|
||||
this.analytics.track('Feature Flag Evaluated', {
|
||||
flag: flagKey,
|
||||
variation: variation,
|
||||
userId: user.id,
|
||||
timestamp: Date.now()
|
||||
});
|
||||
|
||||
// Update evaluation counter
|
||||
const key = `${flagKey}:${variation}`;
|
||||
const count = this.flagEvaluations.get(key) || 0;
|
||||
this.flagEvaluations.set(key, count + 1);
|
||||
}
|
||||
|
||||
trackConversion(flagKey, variation, user, eventType, value) {
|
||||
// Track feature conversion event
|
||||
this.analytics.track('Feature Conversion', {
|
||||
flag: flagKey,
|
||||
variation: variation,
|
||||
eventType: eventType,
|
||||
value: value,
|
||||
userId: user.id,
|
||||
timestamp: Date.now()
|
||||
});
|
||||
}
|
||||
|
||||
getEvaluationStats() {
|
||||
const stats = {};
|
||||
for (const [key, count] of this.flagEvaluations) {
|
||||
const [flag, variation] = key.split(':');
|
||||
if (!stats[flag]) stats[flag] = {};
|
||||
stats[flag][variation] = count;
|
||||
}
|
||||
return stats;
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### A/B Test Analytics
|
||||
|
||||
**Statistical Analysis:**
|
||||
```javascript
|
||||
class ABTestAnalyzer {
|
||||
calculateSignificance(controlMetrics, variantMetrics) {
|
||||
// Calculate conversion rates
|
||||
const controlRate = controlMetrics.conversions / controlMetrics.impressions;
|
||||
const variantRate = variantMetrics.conversions / variantMetrics.impressions;
|
||||
|
||||
// Calculate pooled standard error
|
||||
const pooledRate = (controlMetrics.conversions + variantMetrics.conversions) /
|
||||
(controlMetrics.impressions + variantMetrics.impressions);
|
||||
|
||||
const standardError = Math.sqrt(
|
||||
pooledRate * (1 - pooledRate) *
|
||||
(1 / controlMetrics.impressions + 1 / variantMetrics.impressions)
|
||||
);
|
||||
|
||||
// Calculate z-score
|
||||
const zScore = (variantRate - controlRate) / standardError;
|
||||
|
||||
// Calculate p-value (two-tailed test)
|
||||
const pValue = 2 * (1 - this.normalCDF(Math.abs(zScore)));
|
||||
|
||||
// Calculate confidence interval
|
||||
const marginOfError = 1.96 * standardError;
|
||||
const lift = ((variantRate - controlRate) / controlRate) * 100;
|
||||
|
||||
return {
|
||||
controlRate: (controlRate * 100).toFixed(2) + '%',
|
||||
variantRate: (variantRate * 100).toFixed(2) + '%',
|
||||
lift: lift.toFixed(2) + '%',
|
||||
pValue: pValue.toFixed(4),
|
||||
significant: pValue < 0.05,
|
||||
confidenceInterval: [
|
||||
((variantRate - marginOfError) * 100).toFixed(2) + '%',
|
||||
((variantRate + marginOfError) * 100).toFixed(2) + '%'
|
||||
],
|
||||
sampleSize: {
|
||||
control: controlMetrics.impressions,
|
||||
variant: variantMetrics.impressions
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
normalCDF(x) {
|
||||
// Approximation of cumulative normal distribution
|
||||
const t = 1 / (1 + 0.2316419 * Math.abs(x));
|
||||
const d = 0.3989423 * Math.exp(-x * x / 2);
|
||||
const prob = d * t * (0.3193815 + t * (-0.3565638 + t * (1.781478 + t * (-1.821256 + t * 1.330274))));
|
||||
return x > 0 ? 1 - prob : prob;
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Real-Time Dashboard
|
||||
|
||||
**Metrics Visualization:**
|
||||
```javascript
|
||||
// Feature flag dashboard metrics
|
||||
const dashboardMetrics = {
|
||||
flags: [
|
||||
{
|
||||
key: 'new-checkout-flow',
|
||||
status: 'active',
|
||||
rollout: 45,
|
||||
evaluations: 125430,
|
||||
variations: {
|
||||
enabled: { count: 56444, percentage: 45 },
|
||||
disabled: { count: 68986, percentage: 55 }
|
||||
},
|
||||
metrics: {
|
||||
conversionRate: {
|
||||
enabled: 12.4,
|
||||
disabled: 10.8,
|
||||
lift: 14.8
|
||||
},
|
||||
errorRate: {
|
||||
enabled: 0.02,
|
||||
disabled: 0.03
|
||||
},
|
||||
avgResponseTime: {
|
||||
enabled: 245,
|
||||
disabled: 298
|
||||
}
|
||||
},
|
||||
lastModified: '2024-03-15T14:32:00Z',
|
||||
modifiedBy: 'john.doe@example.com'
|
||||
}
|
||||
]
|
||||
};
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
**ClaudeForge Feature Flag Manager** - Enterprise-grade feature management with progressive rollouts, A/B testing, and comprehensive analytics for data-driven product development.
|
||||
45
plugin.lock.json
Normal file
45
plugin.lock.json
Normal file
@@ -0,0 +1,45 @@
|
||||
{
|
||||
"$schema": "internal://schemas/plugin.lock.v1.json",
|
||||
"pluginId": "gh:claudeforge/marketplace:plugins/commands/feature-flag-manager",
|
||||
"normalized": {
|
||||
"repo": null,
|
||||
"ref": "refs/tags/v20251128.0",
|
||||
"commit": "6e293c4842d6f4148aabbeb5ed09fb0fe5ef620c",
|
||||
"treeHash": "b99730d94216291a3de50c5808a38062ed879f5c5f25e76d164dba9bf0a58fa4",
|
||||
"generatedAt": "2025-11-28T10:15:30.036672Z",
|
||||
"toolVersion": "publish_plugins.py@0.2.0"
|
||||
},
|
||||
"origin": {
|
||||
"remote": "git@github.com:zhongweili/42plugin-data.git",
|
||||
"branch": "master",
|
||||
"commit": "aa1497ed0949fd50e99e70d6324a29c5b34f9390",
|
||||
"repoRoot": "/Users/zhongweili/projects/openmind/42plugin-data"
|
||||
},
|
||||
"manifest": {
|
||||
"name": "feature-flag-manager",
|
||||
"description": "ClaudeForge Enterprise Feature Flag Architect delivering comprehensive progressive rollout methodologies, A/B testing frameworks, canary deployment strategies, and experimentation platforms that transform risky releases into controlled, data-driven feature delivery systems",
|
||||
"version": "1.0.0"
|
||||
},
|
||||
"content": {
|
||||
"files": [
|
||||
{
|
||||
"path": "README.md",
|
||||
"sha256": "ab86ffead68dcb44fd9903b22aa5f8654dff5b9ce85ac6a56ab85a66bb996119"
|
||||
},
|
||||
{
|
||||
"path": ".claude-plugin/plugin.json",
|
||||
"sha256": "da365e8fcbbaeb6623aca112e156119e7b7b79db4e0c710e6ea27fdda15a7eaa"
|
||||
},
|
||||
{
|
||||
"path": "commands/feature-flag-manager.md",
|
||||
"sha256": "badd5628d51fd0bfd26fc6c2c372044f74e61ea60e380684c36a1667f32a1c9a"
|
||||
}
|
||||
],
|
||||
"dirSha256": "b99730d94216291a3de50c5808a38062ed879f5c5f25e76d164dba9bf0a58fa4"
|
||||
},
|
||||
"security": {
|
||||
"scannedAt": null,
|
||||
"scannerVersion": null,
|
||||
"flags": []
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user