senior-devops — Claude Code skill: what it does, how to install
This skill creates CI/CD pipelines, Terraform modules, and Kubernetes deployment manifests. Use it when you need repeatable infrastructure and deployment workflows.
/plugin marketplace add alirezarezvani/claude-skills
/plugin install engineering-skills@claude-code-skillsWhat senior-devops does
senior-devops includes three scripts for common DevOps work. pipeline_generator.py scaffolds CI/CD configurations for GitHub Actions or CircleCI with build, test, security scan, and deploy stages. terraform_scaffolder.py generates and validates Terraform modules for AWS, GCP, or Azure.
deployment_manager.py writes Kubernetes manifests and ordered kubectl runbooks for blue-green or rolling deployments. It adds health-check gates before traffic switches and produces rollback runbooks. The tool prints commands but does not apply changes to a cluster, so the generated changes can be reviewed first.
Install it when you need pipeline setup, infrastructure modules, or a deployment plan with explicit review. It is a poor fit for work outside CI/CD, Terraform, and Kubernetes.
What it helps with
- scaffold a GitHub Actions or CircleCI pipeline
- generate a Terraform module for AWS, GCP, or Azure
- prepare Kubernetes manifests for blue-green or rolling deployment
- write a rollback runbook for a production release
- validate and plan infrastructure before applying it
Example prompts for the agent
- Create a CI/CD pipeline for `./app` with GitHub Actions and the stages `build,test,deploy`.
- Generate a Terraform module in `./infra` for AWS using `ecs-service`.
- Prepare a `staging` deployment for image `app:1.2.3` with the `blue-green` strategy.
How to install senior-devops
1Plugin marketplace
/plugin marketplace add alirezarezvani/claude-skills/plugin install engineering-skills@claude-code-skillsThis installs the whole engineering-skills plugin with all its skills
2Skills CLI (Vercel)
npx skills add alirezarezvani/claude-skills --skill senior-devops -a claude-code3Manually: put the files in place
~/.claude/skills/senior-devops/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/senior-devops/
Manually: put the files in place
.agents/skills/senior-devops/SKILL.mdFor all projects use ~/.agents/skills/
Manually: put the files in place
.cursor/skills/senior-devops/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install alirezarezvani/claude-skills senior-devops2Manually: put the files in place
.github/skills/senior-devops/SKILL.mdPlatform CLI
gemini skills install https://github.com/alirezarezvani/claude-skills --path engineering-team/skills/senior-devopsManually: put the files in place
.devin/skills/senior-devops/SKILL.mdThe legacy .windsurf/skills/ path still works
Claude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
From the same set349
The whole set →Similar
Questions about senior-devops
How do I install senior-devops in Claude Code?
Run npx skills add alirezarezvani/claude-skills --skill senior-devops -a claude-code. The skill is placed at ~/.claude/skills/senior-devops/SKILL.md.
What does senior-devops do?
It scaffolds CI/CD pipelines, Terraform modules, Kubernetes manifests, deployment runbooks, and rollback commands.
Does the deployment manager apply changes to a cluster?
No. It writes manifests and prints the commands, leaving the changes available for human review before application.
Source text
SKILL.md · MIT
---
name: "senior-devops"
description: 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.
---
# 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 — generates deployment manifests + runbooks with rollback support
python3 scripts/deployment_manager.py deploy --env=staging --image=app:1.2.3 --strategy=blue-green --verbose --json
```
## 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
Generates Kubernetes deployment manifests and ordered kubectl runbooks for blue/green or rolling strategies, with health-check gates before traffic switches and rollback runbooks. The tool writes manifests and prints the commands — it never applies them to a cluster itself, so every change gets a human review.
**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"
```
## Multi-Cloud Cross-References
Use these companion skills for cloud-specific deep dives:
| Skill | Cloud | Use When |
|-------|-------|----------|
| **aws-solution-architect** | AWS | ECS/EKS, Lambda, VPC design, cost optimization |
| **azure-cloud-architect** | Azure | AKS, App Service, Virtual Networks, Azure DevOps |
| **gcp-cloud-architect** | GCP | GKE, Cloud Run, VPC, Cloud Build *(coming soon)* |
**Multi-cloud vs single-cloud decision:**
- **Single-cloud** (default) — lower operational complexity, deeper managed-service integration, better cost leverage with committed-use discounts
- **Multi-cloud** — required when mandated by compliance/data residency, acquiring companies on different clouds, or needing best-of-breed services across providers (e.g., AWS for compute + GCP for ML)
- **Hybrid** — on-prem + cloud; use when regulated workloads must stay on-prem while burst/non-sensitive workloads run in the cloud
> Start single-cloud. Add a second cloud only when there is a concrete business or compliance driver — not for theoretical redundancy.
---
## Cloud-Agnostic IaC
### Terraform / OpenTofu (Default Choice)
Terraform (or its open-source fork OpenTofu) is the recommended IaC tool for most teams:
- Single language (HCL) across AWS, Azure, GCP, and 3,000+ providers
- State management with remote backends (S3, GCS, Azure Blob)
- Plan-before-apply workflow prevents drift surprises
- Cross-reference **terraform-patterns** for module structure, state isolation, and CI/CD integration
### Pulumi (Programming Language IaC)
Choose Pulumi when the team strongly prefers TypeScript, Python, Go, or C# over HCL:
- Full programming language — loops, conditionals, unit tests native
- Same cloud provider coverage as Terraform
- Easier onboarding for dev teams that resist learning HCL
### When to Use Cloud-Native IaC
| Tool | Use When |
|------|----------|
| **CloudFormation** | AWS-only shop; need native AWS support (StackSets, Service Catalog) |
| **Bicep** | Azure-only shop; simpler syntax than ARM templates |
| **Cloud Deployment Manager** | GCP-only; rare — most GCP teams prefer Terraform |
> **Rule of thumb:** Use Terraform/OpenTofu unless you are 100% committed to a single cloud AND the cloud-native tool offers a feature Terraform cannot replicate (e.g., AWS Service Catalog integration).
---
## Troubleshooting
Check the comprehensive troubleshooting section in `references/deployment_strategies.md`.
© Alireza Rezvani · MIT · alirezarezvani/claude-skills