Implement — Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deploymen
Scanned 9/8/2026
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---
name: "senior-devops"
description: "Implement — Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deploymen"
executor: HYBRID
skill_id: engineering.cs-engineering-team.senior-devops
status: ADOPTED
security: {level: standard, pii: false, approval_required: false}
anchors:
- engineering
- cloud
- deployment
- automation
tier: 2
input_schema:
- name: code_or_task
type: string
description: "Code snippet, script, or task description to process"
required: true
output_schema:
- name: result
type: string
description: "Generated or refactored code output"
- name: explanation
type: string
description: "Explanation of changes or implementation decisions"
---
# 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
python3 scripts/deployment_manager.py ./deploy --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
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"
```
## 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`.
---
## Why This Skill Exists
Implement — Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deploymen
<!-- SR_40: auto-generated from frontmatter `purpose`/`description` (OPP-Phase3). Expand with domain-specific rationale. -->
## When to Use
Use this skill when the task requires senior devops capabilities.
<!-- SR_40: auto-generated from frontmatter `when`/`description` (OPP-Phase3). -->
## What If Fails
If this skill fails to produce the expected output: (1) verify input completeness, (2) retry with more specific context, (3) fall back to the parent workflow without this skill.
<!-- SR_40: auto-generated from frontmatter `what_if_fails` (OPP-Phase3). -->
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