
Deployment Automation
- 428 installs
- 305 repo stars
- Updated March 4, 2026
- aj-geddes/useful-ai-prompts
deployment-automation is a Claude Code DevOps skill that designs repeatable deploy pipelines with rollbacks, environment promotion, health checks, and infrastructure-as-code for developers shipping auditable production r
About
deployment-automation is a DevOps skill from aj-geddes/useful-ai-prompts that designs repeatable deployment pipelines with rollbacks, environment promotion, health checks, and infrastructure-as-code. Developers invoke it when releases need to move from staging to production with automated verification, audit trails, and fast rollback paths instead of manual SSH deploys. The skill covers pipeline stages, promotion gates, post-deploy health probes, and IaC integration so releases stay low-drama under load. Reach for deployment-automation when formalizing CI/CD for the first time or replacing ad-hoc deploy scripts with auditable workflows.
- CI/CD pipeline scaffolding
- Blue-green or canary rollout patterns
- Infrastructure-as-code templates
- Post-deploy smoke and health gates
- Rollback and incident runbooks
Deployment Automation by the numbers
- 428 all-time installs (skills.sh)
- Ranked #281 of 1,435 DevOps & CI/CD skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 428 |
|---|---|
| repo stars | ★ 305 |
| Last updated | March 4, 2026 |
| Repository | aj-geddes/useful-ai-prompts ↗ |
How do you design repeatable deploy pipelines with rollbacks?
Design repeatable deploy pipelines with rollbacks, environment promotion, health checks, and infra-as-code so releases are fast, auditable, and low-drama.
Who is it for?
Developers formalizing production releases who need pipeline designs with rollbacks, staging promotion, and post-deploy health verification.
Skip if: Teams with mature GitOps pipelines already running who only need minor tuning rather than pipeline architecture from scratch.
When should I use this skill?
A developer needs to design or improve a deploy pipeline with rollbacks, environment promotion, health checks, and auditable release steps.
What you get
Deploy pipeline definitions with rollback procedures, environment promotion stages, health check configs, and infrastructure-as-code artifacts.
- deploy pipeline definition
- rollback runbook
- health check configuration
Files
Deployment Automation
Table of Contents
Overview
Establish automated deployment pipelines that safely and reliably move applications across development, staging, and production environments with minimal manual intervention and risk.
When to Use
- Continuous deployment to Kubernetes
- Infrastructure as Code deployment
- Multi-environment promotion
- Blue-green deployment strategies
- Canary release management
- Infrastructure provisioning
- Automated rollback procedures
Quick Start
Minimal working example:
# helm/Chart.yaml
apiVersion: v2
name: myapp
description: My awesome application
type: application
version: 1.0.0
# helm/values.yaml
replicaCount: 3
image:
repository: ghcr.io/myorg/myapp
pullPolicy: IfNotPresent
tag: "1.0.0"
service:
type: ClusterIP
port: 80
targetPort: 3000
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
autoscaling:
// ... (see reference guides for full implementation)Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| Helm Deployment Chart | Helm Deployment Chart |
| GitHub Actions Deployment Workflow | GitHub Actions Deployment Workflow |
| ArgoCD Deployment | ArgoCD Deployment |
| Blue-Green Deployment | Blue-Green Deployment |
Best Practices
✅ DO
- Use Infrastructure as Code (Terraform, Helm)
- Implement GitOps workflows
- Use blue-green deployments
- Implement canary releases
- Automate rollback procedures
- Test deployments in staging first
- Use feature flags for gradual rollout
- Monitor deployment health
- Document deployment procedures
- Implement approval gates for production
- Version infrastructure code
- Use environment parity
❌ DON'T
- Deploy directly to production
- Skip testing in staging
- Use manual deployment scripts
- Deploy without rollback plan
- Ignore health checks
- Use hardcoded configuration
- Deploy during critical hours
- Skip pre-deployment validation
- Forget to backup before deploy
- Deploy from local machines
ArgoCD Deployment
ArgoCD Deployment
# argocd/myapp-app.yaml
apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
name: myapp
namespace: argocd
spec:
project: default
source:
repoURL: https://github.com/myorg/helm-charts
targetRevision: HEAD
path: myapp
helm:
releaseName: myapp
values: |
image:
tag: v1.0.0
destination:
server: https://kubernetes.default.svc
namespace: production
syncPolicy:
automated:
prune: true
selfHeal: true
syncOptions:
- CreateNamespace=true
retry:
limit: 5
backoff:
duration: 5s
factor: 2
maxDuration: 3mBlue-Green Deployment
Blue-Green Deployment
#!/bin/bash
# Deploy green, run tests, switch traffic
helm upgrade --install myapp-green ./chart --set version=v2.0.0 --wait
kubectl run smoke-test --image=postman/newman --rm -- run tests/smoke.json
if [ $? -eq 0 ]; then
kubectl patch service myapp -p '{"spec":{"selector":{"version":"v2.0.0"}}}'
echo "✅ Traffic switched to green"
else
helm uninstall myapp-green
exit 1
fiGitHub Actions Deployment Workflow
GitHub Actions Deployment Workflow
# .github/workflows/deploy.yml
name: Deploy
on:
push:
branches: [main]
workflow_dispatch:
inputs:
environment:
description: "Environment to deploy to"
required: true
default: "staging"
type: choice
options:
- staging
- production
env:
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}
jobs:
deploy:
runs-on: ubuntu-latest
environment:
name: ${{ github.event.inputs.environment || 'staging' }}
permissions:
contents: read
packages: read
steps:
- uses: actions/checkout@v3
- name: Determine target environment
id: env
run: |
if [[ "${{ github.ref }}" == "refs/heads/main" ]]; then
echo "environment=staging" >> $GITHUB_OUTPUT
else
echo "environment=staging" >> $GITHUB_OUTPUT
fi
- name: Setup kubectl
uses: azure/setup-kubectl@v3
with:
version: "latest"
- name: Configure kubectl
run: |
mkdir -p $HOME/.kube
echo "${{ secrets.KUBE_CONFIG }}" | base64 -d > $HOME/.kube/config
chmod 600 $HOME/.kube/config
- name: Deploy with Helm
run: |
helm repo add myrepo ${{ secrets.HELM_REPO_URL }}
helm repo update
helm upgrade --install myapp myrepo/myapp \
--namespace ${{ steps.env.outputs.environment }} \
--create-namespace \
--values helm/values-${{ steps.env.outputs.environment }}.yaml \
--set image.tag=${{ github.sha }} \
--wait \
--timeout 5m
- name: Verify deployment
run: |
kubectl rollout status deployment/myapp \
-n ${{ steps.env.outputs.environment }} \
--timeout=5mHelm Deployment Chart
Helm Deployment Chart
# helm/Chart.yaml
apiVersion: v2
name: myapp
description: My awesome application
type: application
version: 1.0.0
# helm/values.yaml
replicaCount: 3
image:
repository: ghcr.io/myorg/myapp
pullPolicy: IfNotPresent
tag: "1.0.0"
service:
type: ClusterIP
port: 80
targetPort: 3000
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
autoscaling:
enabled: true
minReplicas: 2
maxReplicas: 10#!/bin/bash
# validate-config.sh - Validate infrastructure configuration
# Usage: ./validate-config.sh <config_file>
set -euo pipefail
CONFIG_FILE="${{1:?Usage: $0 <config_file>}}"
echo "Validating: $CONFIG_FILE"
# TODO: Add configuration validation logic
# - Check required fields
# - Validate syntax (YAML/JSON/HCL)
# - Verify referenced resources exist
# - Check for security best practices
echo "Validation complete."
# Infrastructure Configuration Starter
# TODO: Customize for your infrastructure setup
#
# Usage: Copy this file and modify for your environment
# --- Environment Configuration ---
environment: production
region: us-east-1
# --- Resource Definitions ---
# TODO: Add resource definitions specific to this skill's domain
# --- Security Settings ---
# TODO: Add security configuration
# --- Monitoring ---
# TODO: Add monitoring/alerting configuration
Related skills
How it compares
Pick deployment-automation over single-environment setup skills when the goal is end-to-end release pipeline design with rollbacks and promotion gates.
FAQ
What does deployment-automation help developers design?
deployment-automation helps developers design repeatable deploy pipelines with rollbacks, environment promotion, health checks, and infrastructure-as-code. The skill targets auditable releases that replace manual deploy scripts.
Does deployment-automation include rollback planning?
deployment-automation includes rollback planning as a core deliverable. Pipeline designs specify how to revert failed releases quickly while preserving health check gates and environment promotion order.