name: shipping-and-launch

description: 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.

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

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:

// 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: