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/deployment-automation

Automate deployments across environments using Helm, Terraform, and ArgoCD. Implement blue-green deployments, canary releases, and rollback strategies.

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useful-ai-prompts
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Install
$ npx -y skills add aj-geddes/useful-ai-prompts --skill deployment-automation --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/deployment-automation

Context preview

The summary Claude sees to decide when to auto-load this skill.

Automate deployments across environments using Helm, Terraform, and ArgoCD. Implement blue-green deployments, canary releases, and rollback strategies.

SKILL.md

deployment-automation.SKILL.md
name: deployment-automation
description: >
  Automate deployments across environments using Helm, Terraform, and ArgoCD.
  Implement blue-green deployments, canary releases, and rollback strategies.

Deployment Automation

Table of Contents

  • [Overview](#overview)
  • [When to Use](#when-to-use)
  • [Quick Start](#quick-start)
  • [Reference Guides](#reference-guides)
  • [Best Practices](#best-practices)

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](references/helm-deployment-chart.md) | Helm Deployment Chart | | [GitHub Actions Deployment Workflow](references/github-actions-deployment-workflow.md) | GitHub Actions Deployment Workflow | | [ArgoCD Deployment](references/argocd-deployment.md) | ArgoCD Deployment | | [Blue-Green Deployment](references/blue-green-deployment.md) | 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
Read more
Ships withuseful-ai-prompts

488 production-ready AI prompts, all following a standardized template with validated quality gates. Transform ChatGPT, Claude, and other AI assistants into expert consultants.

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