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Senior devops

Skill mouadja02/skills/skills/devops/senior-devops

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npx -y skills add mouadja02/skills --skill senior-devops

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What its author says it does

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Comprehensive DevOps — CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring

SKILL.md

7.9 KB, ~1.9k tokens by cl100k_base, as published. Nobody here has run it

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:

# 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:

# .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:

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:

# 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:

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):

# 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:

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)

# 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

# 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

# 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.

What ships with it: 7 files

14.5 KB alongside SKILL.md, 3 of them executable

Gives 0 of the 12 instructions most containers cloud skills give in ~1.9k tokens

Counted across 607 of the 657 authors here whose files we hold, read 2026-08-07

  • Run containers as a non-root userin 66 of 607, across 46 files
  • Use multi-stage buildsin 53 of 607, across 44 files
  • Use Promise.all for independent operationsin 47 of 607, across 13 files
  • Import directly instead of barrel filesin 46 of 607, across 12 files
  • Use ternary instead of AND for conditionalsin 45 of 607, across 12 files
  • Use Set or Map for O(1) lookupsin 42 of 607, across 10 files
  • Create a .dockerignore filein 41 of 607, across 31 files
  • Read individual rule files for detailsin 39 of 607, across 9 files
  • Copy dependency files before source codein 36 of 607, across 23 files
  • Authenticate server actions like API routesin 35 of 607, across 7 files
  • Use next/dynamic for heavy componentsin 34 of 607, across 9 files
  • Use React.cache for per-request deduplicationin 34 of 607, across 10 files

Said here and by no other author read

  • verify resources are healthy after applying infrastructure
  • include health-check gates during application deployment
  • verify deployment status before switching traffic
  • verify rollback success via health check

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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