# Shipping And Launch

> Prepares production launches. Use when preparing to deploy to production. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.

- Skill: `kevinke93/shipping-and-launch` (Agent Skill)
- Install (CLI): `npx skillmds@latest add kevinke93/shipping-and-launch`
- Raw SKILL.md: https://api.skillmd.com/api/skills/kevinke93/shipping-and-launch/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: KevinKE93 (https://skillmd.com/u/kevinke93)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/kevinke93/shipping-and-launch

---


# Shipping and Launch

## Overview

Ship with confidence. The goal is not just to deploy — it's to deploy safely, with monitoring in place, a rollback plan ready, and a clear understanding of what success looks like. Every launch should be reversible, observable, and incremental.

## When to Use

- Deploying a feature to production for the first time
- Releasing a significant change to users
- Migrating data or infrastructure
- Opening a beta or early access program
- Any deployment that carries risk (all of them)

## The Pre-Launch Checklist

### Code Quality

- [ ] All tests pass (unit, integration, e2e)
- [ ] Build succeeds with no warnings
- [ ] Lint and type checking pass
- [ ] Code reviewed and approved
- [ ] No TODO comments that should be resolved before launch
- [ ] No `console.log` debugging statements in production code
- [ ] Error handling covers expected failure modes

### Security

- [ ] No secrets in code or version control
- [ ] `npm audit` shows no critical or high vulnerabilities
- [ ] Input validation on all user-facing endpoints
- [ ] Authentication and authorization checks in place
- [ ] Security headers configured (CSP, HSTS, etc.)
- [ ] Rate limiting on authentication endpoints
- [ ] CORS configured to specific origins (not wildcard)

### Performance

- [ ] Core Web Vitals within "Good" thresholds
- [ ] No N+1 queries in critical paths
- [ ] Images optimized (compression, responsive sizes, lazy loading)
- [ ] Bundle size within budget
- [ ] Database queries have appropriate indexes
- [ ] Caching configured for static assets and repeated queries

### Accessibility

- [ ] Keyboard navigation works for all interactive elements
- [ ] Screen reader can convey page content and structure
- [ ] Color contrast meets WCAG 2.1 AA (4.5:1 for text)
- [ ] Focus management correct for modals and dynamic content
- [ ] Error messages are descriptive and associated with form fields
- [ ] No accessibility warnings in axe-core or Lighthouse

### Infrastructure

- [ ] Environment variables set in production
- [ ] Database migrations applied (or ready to apply)
- [ ] DNS and SSL configured
- [ ] CDN configured for static assets
- [ ] Logging and error reporting configured
- [ ] Health check endpoint exists and responds
- [ ] Production verification is read-only or rejection-only; any write-path
      smoke ran in test/staging and has cleanup evidence

### Documentation

- [ ] README updated with any new setup requirements
- [ ] API documentation current
- [ ] ADRs written for any architectural decisions
- [ ] Changelog updated
- [ ] User-facing documentation updated (if applicable)

## Feature Flag Strategy

Ship behind feature flags to decouple deployment from release:

```typescript
// Feature flag check
const flags = await getFeatureFlags(userId);

if (flags.taskSharing) {
  // New feature: task sharing
  return <TaskSharingPanel task={task} />;
}

// Default: existing behavior
return null;
```

**Feature flag lifecycle:**

```
1. DEPLOY with flag OFF     → Code is in production but inactive
2. ENABLE for team/beta     → Internal testing in production environment
3. GRADUAL ROLLOUT          → 5% → 25% → 50% → 100% of users
4. MONITOR at each stage    → Watch error rates, performance, user feedback
5. CLEAN UP                 → Remove flag and dead code path after full rollout
```

**Rules:**
- Every feature flag has an owner and an expiration date
- Clean up flags within 2 weeks of full rollout
- Don't nest feature flags (creates exponential combinations)
- Test both flag states (on and off) in CI

## Staged Rollout

### The Rollout Sequence

```
1. DEPLOY to staging
   └── Full test suite in staging environment
   └── Manual smoke test of critical flows

2. DEPLOY to production (feature flag OFF)
   └── Verify deployment succeeded (health check)
   └── Check error monitoring (no new errors)

3. ENABLE for team (flag ON for internal users)
   └── Team uses the feature in production
   └── 24-hour monitoring window

4. CANARY rollout (flag ON for 5% of users)
   └── Monitor error rates, latency, user behavior
   └── Compare metrics: canary vs. baseline
   └── 24-48 hour monitoring window
   └── Advance only if all thresholds pass (see table below)

5. GRADUAL increase (25% -> 50% -> 100%)
   └── Same monitoring at each step
   └── Ability to roll back to previous percentage at any point

6. FULL rollout (flag ON for all users)
   └── Monitor for 1 week
   └── Clean up feature flag
```

### Rollout Decision Thresholds

Use these thresholds to decide whether to advance, hold, or roll back at each stage:

| Metric | Advance (green) | Hold and investigate (yellow) | Roll back (red) |
|--------|-----------------|-------------------------------|-----------------|
| Error rate | Within 10% of baseline | 10-100% above baseline | >2x baseline |
| P95 latency | Within 20% of baseline | 20-50% above baseline | >50% above baseline |
| Client JS errors | No new error types | New errors at <0.1% of sessions | New errors at >0.1% of sessions |
| Business metrics | Neutral or positive | Decline <5% (may be noise) | Decline >5% |

### When to Roll Back

Roll back immediately if:
- Error rate increases by more than 2x baseline
- P95 latency increases by more than 50%
- User-reported issues spike
- Data integrity issues detected
- Security vulnerability discovered

## Monitoring and Observability

### What to Monitor

```
Application metrics:
├── Error rate (total and by endpoint)
├── Response time (p50, p95, p99)
├── Request volume
├── Active users
└── Key business metrics (conversion, engagement)

Infrastructure metrics:
├── CPU and memory utilization
├── Database connection pool usage
├── Disk space
├── Network latency
└── Queue depth (if applicable)

Client metrics:
├── Core Web Vitals (LCP, INP, CLS)
├── JavaScript errors
├── API error rates from client perspective
└── Page load time
```

### Error Reporting

```typescript
// Set up error boundary with reporting
class ErrorBoundary extends React.Component {
  componentDidCatch(error: Error, info: React.ErrorInfo) {
    // Report to error tracking service
    reportError(error, {
      componentStack: info.componentStack,
      userId: getCurrentUser()?.id,
      page: window.location.pathname,
    });
  }

  render() {
    if (this.state.hasError) {
      return <ErrorFallback onRetry={() => this.setState({ hasError: false })} />;
    }
    return this.props.children;
  }
}

// Server-side error reporting
app.use((err: Error, req: Request, res: Response, next: NextFunction) => {
  reportError(err, {
    method: req.method,
    url: req.url,
    userId: req.user?.id,
  });

  // Don't expose internals to users
  res.status(500).json({
    error: { code: 'INTERNAL_ERROR', message: 'Something went wrong' },
  });
});
```

### Post-Launch Verification

In the first hour after launch:

```
1. Check health endpoint returns 200
2. Check error monitoring dashboard (no new error types)
3. Check latency dashboard (no regression)
4. Verify critical production surfaces with read-only/rejection-only checks
5. Verify logs are flowing and readable
6. Confirm rollback mechanism works (dry run if possible)
```

Do not run write smoke tests in production or formal environments. A smoke that
logs in, creates users or sessions, accepts a webhook, syncs billing, uploads
files, or writes business records belongs in test/staging. If a canary write is
unavoidable, require explicit user approval, a named canary account, and a
cleanup/retention plan before execution.

## Rollback Strategy

Every deployment needs a rollback plan before it happens:

```markdown
## Rollback Plan for [Feature/Release]

### Trigger Conditions
- Error rate > 2x baseline
- P95 latency > [X]ms
- User reports of [specific issue]

### Rollback Steps
1. Disable feature flag (if applicable)
   OR
1. Deploy previous version: `git revert <commit> && git push`
2. Verify rollback: health check, error monitoring
3. Communicate: notify team of rollback

### Database Considerations
- Migration [X] has a rollback: `npx prisma migrate rollback`
- Data inserted by new feature: [preserved / cleaned up]

### Time to Rollback
- Feature flag: < 1 minute
- Redeploy previous version: < 5 minutes
- Database rollback: < 15 minutes
```
## See Also

- For security pre-launch checks, see `references/security-checklist.md`
- For performance pre-launch checklist, see `references/performance-checklist.md`
- For accessibility verification before launch, see `references/accessibility-checklist.md`

## Common Rationalizations

| Rationalization | Reality |
|---|---|
| "It works in staging, it'll work in production" | Production has different data, traffic patterns, and edge cases. Monitor after deploy. |
| "We don't need feature flags for this" | Every feature benefits from a kill switch. Even "simple" changes can break things. |
| "Monitoring is overhead" | Not having monitoring means you discover problems from user complaints instead of dashboards. |
| "We'll add monitoring later" | Add it before launch. You can't debug what you can't see. |
| "Rolling back is admitting failure" | Rolling back is responsible engineering. Shipping a broken feature is the failure. |

## Red Flags

- Deploying without a rollback plan
- No monitoring or error reporting in production
- Big-bang releases (everything at once, no staging)
- Feature flags with no expiration or owner
- No one monitoring the deploy for the first hour
- Production environment configuration done by memory, not code
- "It's Friday afternoon, let's ship it"

## Verification

Before deploying:

- [ ] Pre-launch checklist completed (all sections green)
- [ ] Feature flag configured (if applicable)
- [ ] Rollback plan documented
- [ ] Monitoring dashboards set up
- [ ] Team notified of deployment
- [ ] `<project-name>/.dev-agent/ship/LAUNCH.md` records the go/no-go decision, rollback plan, owners, and follow-up notes
- [ ] `bin/dev-flow ship-check <project-name>` passes

After deploying:

- [ ] Health check returns 200
- [ ] Error rate is normal
- [ ] Latency is normal
- [ ] Critical user flow works
- [ ] Logs are flowing
- [ ] Rollback tested or verified ready