senior-devops

Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.

1,864 stars

Best use case

senior-devops is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.

Teams using senior-devops should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/senior-devops/SKILL.md --create-dirs "https://raw.githubusercontent.com/LeoYeAI/openclaw-master-skills/main/skills/senior-devops/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/senior-devops/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How senior-devops Compares

Feature / Agentsenior-devopsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Senior Devops

Complete toolkit for senior devops with modern tools and best practices.

## Quick Start

### Main Capabilities

This skill provides three core capabilities through automated scripts:

```bash
# Script 1: Pipeline Generator — scaffolds CI/CD pipelines for GitHub Actions or CircleCI
python scripts/pipeline_generator.py ./app --platform=github --stages=build,test,deploy

# Script 2: Terraform Scaffolder — generates and validates IaC modules for AWS/GCP/Azure
python scripts/terraform_scaffolder.py ./infra --provider=aws --module=ecs-service --verbose

# Script 3: Deployment Manager — orchestrates container deployments with rollback support
python scripts/deployment_manager.py deploy --env=production --image=app:1.2.3 --strategy=blue-green
```

## Core Capabilities

### 1. Pipeline Generator

Scaffolds CI/CD pipeline configurations for GitHub Actions or CircleCI, with stages for build, test, security scan, and deploy.

**Example — GitHub Actions workflow:**
```yaml
# .github/workflows/ci.yml
name: CI/CD Pipeline
on:
  push:
    branches: [main, develop]
  pull_request:
    branches: [main]

jobs:
  build-and-test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Set up Node.js
        uses: actions/setup-node@v4
        with:
          node-version: '20'
          cache: 'npm'
      - run: npm ci
      - run: npm run lint
      - run: npm test -- --coverage
      - name: Upload coverage
        uses: codecov/codecov-action@v4

  build-docker:
    needs: build-and-test
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Build and push image
        uses: docker/build-push-action@v5
        with:
          push: ${{ github.ref == 'refs/heads/main' }}
          tags: ghcr.io/${{ github.repository }}:${{ github.sha }}

  deploy:
    needs: build-docker
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    steps:
      - name: Deploy to ECS
        run: |
          aws ecs update-service \
            --cluster production \
            --service app-service \
            --force-new-deployment
```

**Usage:**
```bash
python scripts/pipeline_generator.py <project-path> --platform=github|circleci --stages=build,test,deploy
```

### 2. Terraform Scaffolder

Generates, validates, and plans Terraform modules. Enforces consistent module structure and runs `terraform validate` + `terraform plan` before any apply.

**Example — AWS ECS service module:**
```hcl
# modules/ecs-service/main.tf
resource "aws_ecs_task_definition" "app" {
  family                   = var.service_name
  requires_compatibilities = ["FARGATE"]
  network_mode             = "awsvpc"
  cpu                      = var.cpu
  memory                   = var.memory

  container_definitions = jsonencode([{
    name      = var.service_name
    image     = var.container_image
    essential = true
    portMappings = [{
      containerPort = var.container_port
      protocol      = "tcp"
    }]
    environment = [for k, v in var.env_vars : { name = k, value = v }]
    logConfiguration = {
      logDriver = "awslogs"
      options = {
        awslogs-group         = "/ecs/${var.service_name}"
        awslogs-region        = var.aws_region
        awslogs-stream-prefix = "ecs"
      }
    }
  }])
}

resource "aws_ecs_service" "app" {
  name            = var.service_name
  cluster         = var.cluster_id
  task_definition = aws_ecs_task_definition.app.arn
  desired_count   = var.desired_count
  launch_type     = "FARGATE"

  network_configuration {
    subnets          = var.private_subnet_ids
    security_groups  = [aws_security_group.app.id]
    assign_public_ip = false
  }

  load_balancer {
    target_group_arn = aws_lb_target_group.app.arn
    container_name   = var.service_name
    container_port   = var.container_port
  }
}
```

**Usage:**
```bash
python scripts/terraform_scaffolder.py <target-path> --provider=aws|gcp|azure --module=ecs-service|gke-deployment|aks-service [--verbose]
```

### 3. Deployment Manager

Orchestrates deployments with blue/green or rolling strategies, health-check gates, and automatic rollback on failure.

**Example — Kubernetes blue/green deployment (blue-slot specific elements):**
```yaml
# k8s/deployment-blue.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: app-blue
  labels:
    app: myapp
    slot: blue      # slot label distinguishes blue from green
spec:
  replicas: 3
  selector:
    matchLabels:
      app: myapp
      slot: blue
  template:
    metadata:
      labels:
        app: myapp
        slot: blue
    spec:
      containers:
        - name: app
          image: ghcr.io/org/app:1.2.3
          readinessProbe:       # gate: pod must pass before traffic switches
            httpGet:
              path: /healthz
              port: 8080
            initialDelaySeconds: 10
            periodSeconds: 5
          resources:
            requests:
              cpu: "250m"
              memory: "256Mi"
            limits:
              cpu: "500m"
              memory: "512Mi"
```

**Usage:**
```bash
python scripts/deployment_manager.py deploy \
  --env=staging|production \
  --image=app:1.2.3 \
  --strategy=blue-green|rolling \
  --health-check-url=https://app.example.com/healthz

python scripts/deployment_manager.py rollback --env=production --to-version=1.2.2
python scripts/deployment_manager.py --analyze --env=production   # audit current state
```

## Resources

- Pattern Reference: `references/cicd_pipeline_guide.md` — detailed CI/CD patterns, best practices, anti-patterns
- Workflow Guide: `references/infrastructure_as_code.md` — IaC step-by-step processes, optimization, troubleshooting
- Technical Guide: `references/deployment_strategies.md` — deployment strategy configs, security considerations, scalability
- Tool Scripts: `scripts/` directory

## Development Workflow

### 1. Infrastructure Changes (Terraform)

```bash
# Scaffold or update module
python scripts/terraform_scaffolder.py ./infra --provider=aws --module=ecs-service --verbose

# Validate and plan — review diff before applying
terraform -chdir=infra init
terraform -chdir=infra validate
terraform -chdir=infra plan -out=tfplan

# Apply only after plan review
terraform -chdir=infra apply tfplan

# Verify resources are healthy
aws ecs describe-services --cluster production --services app-service \
  --query 'services[0].{Status:status,Running:runningCount,Desired:desiredCount}'
```

### 2. Application Deployment

```bash
# Generate or update pipeline config
python scripts/pipeline_generator.py . --platform=github --stages=build,test,security,deploy

# Build and tag image
docker build -t ghcr.io/org/app:$(git rev-parse --short HEAD) .
docker push ghcr.io/org/app:$(git rev-parse --short HEAD)

# Deploy with health-check gate
python scripts/deployment_manager.py deploy \
  --env=production \
  --image=app:$(git rev-parse --short HEAD) \
  --strategy=blue-green \
  --health-check-url=https://app.example.com/healthz

# Verify pods are running
kubectl get pods -n production -l app=myapp
kubectl rollout status deployment/app-blue -n production

# Switch traffic after verification
kubectl patch service app-svc -n production \
  -p '{"spec":{"selector":{"slot":"blue"}}}'
```

### 3. Rollback Procedure

```bash
# Immediate rollback via deployment manager
python scripts/deployment_manager.py rollback --env=production --to-version=1.2.2

# Or via kubectl
kubectl rollout undo deployment/app -n production
kubectl rollout status deployment/app -n production

# Verify rollback succeeded
kubectl get pods -n production -l app=myapp
curl -sf https://app.example.com/healthz || echo "ROLLBACK FAILED — escalate"
```

## Troubleshooting

Check the comprehensive troubleshooting section in `references/deployment_strategies.md`.

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