About devops-engineer
devops-engineer is a skill that provides guidance on CI/CD, infrastructure as code, container orchestration, monitoring, and operational practices. It is for teams designing deployment and cloud operations, with workflows and checklists covering areas such as Kubernetes, Terraform, and release strategies.
Key features
- 01Design CI/CD pipelines and release workflows
- 02Plan infrastructure as code
- 03Guide Kubernetes and Docker deployments
- 04Set up monitoring and observability practices
- 05Apply operational, security, and documentation checklists
Use cases
- 01Designing a CI/CD pipeline for a new project
- 02Managing cloud resources with Terraform
- 03Deploying applications to Kubernetes
- 04Reviewing monitoring, security, and operational readiness
Install
Copy the command and run it in a terminal.
$
npx skills add https:/After installing, type/devops-engineerin Claude Code to confirm it loaded.
Bundled filesEXAMPLES.mdREFERENCE.md
Details
From the project READMEDevOps Engineer
Purpose
Provides senior-level DevOps engineering expertise for CI/CD automation, infrastructure as code, container orchestration, and operational excellence. Specializes in building scalable deployment pipelines, cloud infrastructure automation, monitoring systems, and SRE practices across AWS, Azure, and GCP platforms.
When to Use
- Designing end-to-end CI/CD pipelines from requirements to production
- Implementing infrastructure as code (Terraform, Ansible, CloudFormation, Bicep)
- Building container orchestration systems (Kubernetes, Docker, Helm)
- Setting up monitoring and observability platforms (Prometheus, Grafana, ELK)
- Automating deployment workflows and release management
- Optimizing cloud infrastructure costs and performance
- Implementing GitOps workflows and continuous delivery practices
Quick Start
Invoke this skill when:
- Designing end-to-end CI/CD pipelines from requirements to production
- Implementing infrastructure as code (Terraform, Ansible, CloudFormation)
- Building container orchestration systems (Kubernetes, Docker, Helm)
- Setting up monitoring and observability platforms (Prometheus, Grafana, ELK)
- Automating deployment workflows and release management
- Optimizing cloud infrastructure costs and performance
Do NOT invoke when:
- Simple script automation exists (use backend-developer instead)
- Only code review needed without DevOps context
- Pure infrastructure architecture decisions (use cloud-architect for strategy)
- Database-specific operations (use database-administrator)
- Application-level debugging (use debugger skill)
Core Workflows Summary
Workflow 1: Build Complete CI/CD Pipeline from Scratch
Use case: Greenfield project needs full DevOps automation
Requirements Gathering Checklist:
- Deployment Frequency (hourly/daily/weekly)
- Tech Stack (language/framework, database, frontend)
- Infrastructure (cloud provider, auto-scaling needs)
- Testing (unit, integration, security scans)
- Compliance (audit logging, approval gates, secrets management)
Workflow 2: Infrastructure as Code
Use case: Manage cloud resources declaratively with Terraform
Key Components:
- State management (S3 backend with DynamoDB locking)
- Module composition (VPC, EKS, RDS)
- Environment separation (dev/staging/production)
- Tagging strategy for cost allocation
Workflow 3: Container Orchestration
Use case: Deploy applications to Kubernetes
Key Components:
- Helm charts for templating
- Deployments with rolling updates
- Services and Ingress configuration
- ConfigMaps and Secrets management
- Resource limits and health checks
Decision Framework
GitOps Workflow Selection
Deployment Strategy Selection
├─ Small team (<5 developers)
│ └─ Push-based CI/CD (GitHub Actions, GitLab CI)
│ • Simpler to set up
│ • Direct kubectl/helm in pipeline
│
├─ Medium team (5-20 developers)
│ └─ GitOps with ArgoCD
│ • Git as single source of truth
│ • Automatic sync with self-heal
│ • Audit trail for all changes
│
└─ Large enterprise (20+ developers)
└─ GitOps with ArgoCD + ApplicationSets
• Multi-cluster management
• Environment promotion
• Tenant isolation
Deployment Strategy Selection
| Strategy | Rollback Speed | Risk | Complexity | Use Case |
|---|---|---|---|---|
| Rolling Update | Medium (minutes) | Low | Low | Standard deployments |
| Blue-Green | Instant | Very Low | Medium | Zero-downtime critical apps |
| Canary | Fast | Very Low | High | Gradual rollout with metrics |
| Recreate | N/A | High | Low | Dev/test environments only |
Quality Checklist
CI/CD Pipeline
- Build stage completes in <5 minutes
- All tests pass (unit, integration, security scans)
- Automated rollback on failure
- Deployment notifications configured (Slack/email)
- Pipeline as code (version controlled)
Infrastructure
- All infrastructure defined as code (Terraform/CloudFormation)
- Multi-environment support (dev/staging/production)
- Auto-scaling policies configured
- Disaster recovery tested (RTO/RPO documented)
- Cost monitoring and budget alerts active
Containerization
- Multi-stage Dockerfiles (optimized image size)
- Security scanning passed (Trivy, Snyk)
- Resource limits defined for all containers
- Health checks implemented (liveness + readiness)
- Runs as non-root user
Monitoring
- Metrics collection configured (Prometheus/CloudWatch)
- Dashboards created for key services
- Alerts defined with runbooks
- Log aggregation working (ELK/Loki)
- Distributed tracing enabled (Jaeger/X-Ray)
Security
- Secrets stored in vault (not in code)
- RBAC configured (least privilege)
- Network policies defined (zero trust)
- Vulnerability scanning automated
- Audit logging enabled
Documentation
- Architecture diagrams created
- Runbooks documented for common issues
- Onboarding guide for new team members
- Disaster recovery procedures tested
- CI/CD pipeline documented
Additional Resources
- Detailed Technical Reference: See REFERENCE.md
- Code Examples & Patterns: See EXAMPLES.md
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