Deployment Plan

Deployment Plan

Purpose

Design a complete deployment strategy covering environment progression, pipeline stages, zero-downtime releases, rollback procedures, and feature flag management. Produces actionable deployment runbooks and pipeline configurations.

Inputs

• Feature or service being deployed
• Current infrastructure (hosting provider, container orchestration, CI/CD tooling)
• Existing deployment process (if any)
• Availability requirements (SLA/SLO targets, maintenance window constraints)

Process

Step 1: Define Deployment Environments

Map the environment progression and configuration strategy:

• Environment chain: dev → staging → production (add preview/QA if needed)
• Environment-specific configs: Feature flags, API endpoints, database connections, third-party service keys
• Environment parity: What differs between environments and why — minimize drift
• Access controls: Who can deploy to which environment, approval requirements

Step 2: Design Deployment Pipeline

Define the build-test-deploy stages:

• Build stage: Compilation, dependency resolution, asset bundling, Docker image creation
• Test stage: Unit tests, integration tests, E2E smoke tests, security scans
• Deploy stages: Per-environment deployment steps with promotion gates
• Approval gates: Automatic promotion vs manual approval between environments
• Artifact management: Image tagging strategy, artifact retention policy

Step 3: Plan Zero-Downtime Strategy

Select and design the deployment strategy:

• Blue-green: Two identical environments, instant traffic switch, simple rollback
• Rolling update: Gradual instance replacement, reduced resource overhead, longer rollout
• Canary: Progressive traffic shifting (1% → 10% → 50% → 100%), metric-gated promotion
• Feature flags: Deploy dark, enable progressively, decouple deploy from release
• Choose strategy based on risk tolerance, infrastructure capabilities, and rollback speed requirements

Step 4: Define Rollback Procedures

Plan for every failure scenario:

• Automated rollback triggers: Health check failures, error rate spikes, latency thresholds
• Manual rollback steps: Exact commands or UI steps to revert to previous version
• Data rollback considerations: Can database changes be reversed? Forward-fix vs rollback
• Rollback testing: How and when rollback procedures are verified
• Communication protocol: Who is notified during rollback, status page updates

Step 5: Design Feature Flag Strategy

Plan feature flag lifecycle:

• Flag types: Release flags (temporary), ops flags (kill switches), experiment flags (A/B), permission flags (entitlements)
• Flag lifecycle: Creation → testing → rollout → full-release → cleanup
• Cleanup schedule: Maximum flag age, review cadence, stale flag detection
• Flag management: Tooling choice, naming conventions, flag ownership

Step 6: Specify Health Checks

Define verification at every stage:

• Readiness probes: Is the new version ready to receive traffic? Dependency checks, warmup completion
• Liveness probes: Is the running instance healthy? Memory, deadlock detection, heartbeat
• Smoke tests: Post-deploy verification of critical paths — login, core API, key user flows
• Synthetic monitoring: Continuous external checks simulating user behavior

Step 7: Plan Database Migration Coordination

Coordinate schema changes with deployments:

• Migration ordering: Run migrations before deploy (expand), after deploy (contract), or both (expand-contract pattern)
• Backward-compatible migrations: Additive changes only during rollout — no column drops, no renames
• Rollback scripts: Reverse migration for every forward migration
• Data backfill: Strategy for populating new columns or transforming existing data
• Migration testing: Run against production-like data volume before deploying

Output Format

# Deployment Plan: [Feature/Service Name]

## Environment Matrix

| Environment | Purpose | URL | Deploy Method | Approval |
|-------------|---------|-----|---------------|----------|
| dev         | Development testing | ... | Auto on merge to dev | None |
| staging     | Pre-production validation | ... | Auto on merge to main | None |
| production  | Live traffic | ... | Promotion from staging | Manual |

## Pipeline Diagram

[commit] → [build] → [test] → [deploy:dev] → [deploy:staging] → [approve] → [deploy:prod] ↓ [smoke tests]

## Deployment Strategy

**Method**: [Blue-green / Rolling / Canary / Feature flag]

[Strategy-specific details: traffic percentages, timing, promotion criteria]

## Rollback Checklist

- [ ] Trigger: [condition that initiates rollback]
- [ ] Command: [exact rollback command or procedure]
- [ ] Verify: [how to confirm rollback succeeded]
- [ ] Database: [migration rollback steps if applicable]
- [ ] Notify: [who to inform and how]

## Feature Flag Plan

| Flag Name | Type | Default | Rollout Plan | Cleanup Date |
|-----------|------|---------|--------------|--------------|
| ... | release | off | 1% → 10% → 100% | [date] |

## Health Checks

| Check | Type | Endpoint/Method | Interval | Failure Threshold |
|-------|------|-----------------|----------|-------------------|
| Readiness | probe | /health/ready | 5s | 3 consecutive |
| Liveness | probe | /health/live | 10s | 5 consecutive |
| Smoke | post-deploy | [test suite] | on deploy | any failure |

## Database Migration Plan

| Migration | Type | Reversible | Run When | Dependencies |
|-----------|------|------------|----------|--------------|
| ... | expand | yes | pre-deploy | none |

Quality Checks

• Every environment has defined configuration and access controls
• Pipeline includes automated tests before each promotion
• Zero-downtime strategy is specified with rollback speed estimate
• Rollback procedures are documented with exact commands
• Feature flags have defined lifecycle and cleanup dates
• Health checks cover readiness, liveness, and post-deploy smoke tests
• Database migrations are backward-compatible during rollout
• Communication plan covers both deploy and rollback scenarios

Evolution Notes

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