From daffy0208-ai-dev-standards
Ship features safely with progressive rollouts, feature flags, and canary deployments. Use when deploying risky features or need gradual rollouts.
npx claudepluginhub joshuarweaver/cascade-content-creation-misc-1 --plugin daffy0208-ai-dev-standardsThis skill uses the workspace's default tool permissions.
Ship features safely with progressive rollouts.
Creates isolated Git worktrees for feature branches with prioritized directory selection, gitignore safety checks, auto project setup for Node/Python/Rust/Go, and baseline verification.
Executes implementation plans in current session by dispatching fresh subagents per independent task, with two-stage reviews: spec compliance then code quality.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
Ship features safely with progressive rollouts.
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 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 />
)}
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
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
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
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
Internal:
- Slack announcement
- Deploy log updated
- Engineering team notified
External:
- Changelog updated
- Email to power users (if major)
- Blog post (if significant)
Safe releases: