daffy0208/ai-dev-standards/release-manager

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Ship features safely with progressive rollouts, feature flags, and canary deployments. Use when deploying risky features or need gradual rollouts.

Install

npx vskill@latest install daffy0208/ai-dev-standards/release-manager

SKILL.md

Release Manager

Ship features safely with progressive rollouts.

Progressive Rollout Strategy

yaml
Phase 1 - Internal (Day 1):
- 100% to internal team
- Test thoroughly
- Fix critical bugs
Phase 2 - Beta (Day 2-3):
- 5% to beta users
- Monitor errors/performance
- Collect feedback
Phase 3 - Gradual (Day 4-7):
- 25% of users
- Watch metrics closely
- 50% of users if good
- 100% if still good
Phase 4 - Full Release:
- 100% of users
- Remove feature flag
- Announce publicly

Feature Flags

typescript
// Feature flag implementation
const featureFlags = {
newDashboard: {
enabled: true,
rollout: 0.25, // 25% of users
userGroups: ['beta-testers'], // Always on for beta
}
}
function isFeatureEnabled(feature, user) {
const flag = featureFlags[feature]
// Check user group
if (user.groups.some(g => flag.userGroups.includes(g))) {
return true
}
// Check rollout percentage
const hash = hashUserId(user.id)
return (hash % 100) < (flag.rollout * 100)
}
// Usage
{isFeatureEnabled('newDashboard', user) ? (
<NewDashboard />
) : (
<OldDashboard />
)}

Deployment Strategies

Blue-Green Deployment
yaml
Process: 1. Deploy to "green" environment
2. Test green thoroughly
3. Switch traffic to green
4. Keep blue as rollback
Pros: Instant rollback
Cons: 2x infrastructure cost
Canary Deployment
yaml
Process: 1. Deploy to 5% of servers
2. Monitor for 1 hour
3. If good, deploy to 25%
4. Monitor for 1 hour
5. If good, deploy to 100%
Pros: Gradual, safe
Cons: Slower rollout

Rollback Plan

yaml
Criteria for Rollback:
- Error rate > 1%
- Performance degradation > 20%
- Critical bug discovered
- Negative user feedback
Rollback Process: 1. Disable feature flag immediately
2. Notify team
3. Investigate issue
4. Fix and redeploy

Release Checklist

Pre-Release
  • [ ] Code reviewed
  • [ ] Tests passing
  • [ ] Staging tested
  • [ ] Feature flag configured
  • [ ] Rollback plan ready
  • [ ] Monitoring alerts set
During Release
  • [ ] Deploy to 5% first
  • [ ] Watch error rate
  • [ ] Monitor performance
  • [ ] Check user feedback
  • [ ] Gradually increase
Post-Release
  • [ ] Monitor for 24 hours
  • [ ] Collect feedback
  • [ ] Remove feature flag
  • [ ] Document learnings

Monitoring

yaml
Key Metrics During Release:
- Error rate
- Response time p95
- CPU/memory usage
- User-reported issues
Alerts:
- Error rate > 1% → Pause rollout
- Response time > 2s → Investigate
- Memory spike > 90% → Rollback

Communication

yaml
Internal:
- Slack announcement
- Deploy log updated
- Engineering team notified
External:
- Changelog updated
- Email to power users (if major)
- Blog post (if significant)

Summary

Safe releases:

  • ✅ Start small (5%)
  • ✅ Monitor closely
  • ✅ Rollback readily
  • ✅ Feature flags everywhere
  • ✅ Document process

Security

  • Security scanPassed, 96 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

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Source

Popularity

Repository stars
23
Repository forks
6
7-day trend score
16

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 10 Apr 2026, 6 months ago.

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