Deployment Procedures

Deployment principles and decision-making for safe production releases.

Learn to THINK, not memorize scripts.

⚠️ How to Use This Skill

This skill teaches deployment principles, not bash scripts to copy.

• Every deployment is unique

• Understand the WHY behind each step

• Adapt procedures to your platform

1. Platform Selection

Decision Tree

What are you deploying?

│

├── Static site / JAMstack

│   └── Vercel, Netlify, Cloudflare Pages

│

├── Simple web app

│   ├── Managed → Railway, Render, Fly.io

│   └── Control → VPS + PM2/Docker

│

├── Microservices

│   └── Container orchestration

│

└── Serverless

    └── Edge functions, Lambda

Each Platform Has Different Procedures

Platform

Deployment Method

Vercel/Netlify

Git push, auto-deploy

Railway/Render

Git push or CLI

VPS + PM2

SSH + manual steps

Docker

Image push + orchestration

Kubernetes

kubectl apply

2. Pre-Deployment Principles

The 4 Verification Categories

Category

What to Check

Code Quality

Tests passing, linting clean, reviewed

Build

Production build works, no warnings

Environment

Env vars set, secrets current

Safety

Backup done, rollback plan ready

Pre-Deployment Checklist

• All tests passing

• Code reviewed and approved

• Production build successful

• Environment variables verified

• Database migrations ready (if any)

• Rollback plan documented

• Team notified

• Monitoring ready

3. Deployment Workflow Principles

The 5-Phase Process

1. PREPARE

   └── Verify code, build, env vars

2. BACKUP

   └── Save current state before changing

3. DEPLOY

   └── Execute with monitoring open

4. VERIFY

   └── Health check, logs, key flows

5. CONFIRM or ROLLBACK

   └── All good? Confirm. Issues? Rollback.

Phase Principles

Phase

Principle

Prepare

Never deploy untested code

Backup

Can't rollback without backup

Deploy

Watch it happen, don't walk away

Verify

Trust but verify

Confirm

Have rollback trigger ready

4. Post-Deployment Verification

What to Verify

Check

Why

Health endpoint

Service is running

Error logs

No new errors

Key user flows

Critical features work

Performance

Response times acceptable

Verification Window

• First 5 minutes: Active monitoring

• 15 minutes: Confirm stable

• 1 hour: Final verification

• Next day: Review metrics

5. Rollback Principles

When to Rollback

Symptom

Action

Service down

Rollback immediately

Critical errors

Rollback

Performance >50% degraded

Consider rollback

Minor issues

Fix forward if quick

Rollback Strategy by Platform

Platform

Rollback Method

Vercel/Netlify

Redeploy previous commit

Railway/Render

Rollback in dashboard

VPS + PM2

Restore backup, restart

Docker

Previous image tag

K8s

kubectl rollout undo

Rollback Principles

• Speed over perfection: Rollback first, debug later

• Don't compound errors: One rollback, not multiple changes

• Communicate: Tell team what happened

• Post-mortem: Understand why after stable

6. Zero-Downtime Deployment

Strategies

Strategy

How It Works

Rolling

Replace instances one by one

Blue-Green

Switch traffic between environments

Canary

Gradual traffic shift

Selection Principles

Scenario

Strategy

Standard release

Rolling

High-risk change

Blue-green (easy rollback)

Need validation

Canary (test with real traffic)

7. Emergency Procedures

Service Down Priority

• Assess: What's the symptom?

• Quick fix: Restart if unclear

• Rollback: If restart doesn't help

• Investigate: After stable

Investigation Order

Check

Common Issues

Logs

Errors, exceptions

Resources

Disk full, memory

Network

DNS, firewall

Dependencies

Database, APIs

8. Anti-Patterns

❌ Don't

✅ Do

Deploy on Friday

Deploy early in week

Rush deployment

Follow the process

Skip staging

Always test first

Deploy without backup

Backup before deploy

Walk away after deploy

Monitor for 15+ min

Multiple changes at once

One change at a time

9. Decision Checklist

Before deploying:

• Platform-appropriate procedure?

• Backup strategy ready?

• Rollback plan documented?

• Monitoring configured?

• Team notified?

• Time to monitor after?

10. Best Practices

• Small, frequent deploys over big releases

• Feature flags for risky changes

• Automate repetitive steps

• Document every deployment

• Review what went wrong after issues

• Test rollback before you need it

Remember: Every deployment is a risk. Minimize risk through preparation, not speed.

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

• Use this skill only when the task clearly matches the scope described above.

• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.

• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.