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vignesh2027/ai-agent-skills/deployment-strategy
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PublishedSeptember 28, 2026 at 09:24 AM
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version: "1.0.0" name: deployment-strategy description: Deploy with rollback plans, staged rollouts, and feature flags difficulty: senior domains: [general]


Overview

Deployments fail. The question is not whether, but whether you can recover quickly. This skill makes deployments reversible, observable, and gradual.

When to Use

  • Before every production deployment
  • When designing a deployment pipeline
  • When a deployment caused a production incident
  • As part of the /ship workflow

Process

Step 1: Write the rollback procedure first

Before deploying, document how to roll back. If you can't write the rollback procedure, you're not ready to deploy.

Step 2: Define the rollout stages

1% → 10% → 50% → 100% for high-risk changes. 10% → 100% for low-risk changes. Never: 0% → 100% for anything that touches user-visible behavior.

Step 3: Choose a deployment strategy

  • Blue/green: spin up new environment, switch traffic, keep old environment warm for rollback
  • Canary: route a percentage of traffic to new version, measure, expand
  • Feature flags: deploy code dark, flip flag to enable for users
  • Rolling: replace instances one by one, abort if errors spike

Choose based on: how reversible is the change? How quickly can you detect problems?

Step 4: Define the deployment success criteria

Before deploying: what metrics must hold for the deployment to be considered successful?

  • Error rate stays below X%
  • p99 latency stays below Y ms
  • No new error types in logs
  • Key business metric (signups, orders) not regressing

Step 5: Bake time

After deploying to a stage: wait before expanding. Minimum bake time:

  • 1% stage: 15 minutes
  • 10% stage: 1 hour
  • 50% stage: 4 hours

High-risk changes need longer bake times.

Step 6: Database migrations

  • Migrations must be backward compatible (old code + new schema must work)
  • Deploy migration before new code; keep old code running
  • Never delete a column in the same release that stops using it
  • Test rollback of the migration

Step 7: Automate the deployment gate

Success criteria from Step 4 must be checked automatically. If they fail, the deployment halts. Not: "someone watches the dashboard." Automatic.

Step 8: Post-deployment monitoring

After a deployment: watch the golden signals for 24 hours. Document any anomalies.

Anti-Rationalizations

"It's a small change — we can deploy to 100%" "Small" changes cause production incidents. All production changes go through staged rollout.

"We can roll back if there's a problem" "Can roll back" means the rollback procedure is written, tested, and can be executed in under 5 minutes. Otherwise, you don't have a rollback plan; you have a hope.

Verification Requirements

  • [ ] Rollback procedure written before deployment starts
  • [ ] Deployment stages defined (not 0% → 100%)
  • [ ] Success criteria defined and automated
  • [ ] Bake time defined at each stage
  • [ ] Database migrations are backward compatible
  • [ ] Post-deployment monitoring planned
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