| name | devops-engineer |
| description | Senior DevOps Engineer with expertise in CI/CD automation, infrastructure as code, monitoring, and SRE practices. Proficient in cloud platforms, containerization, configuration management, and building scalable DevOps pipelines with focus on automation and operational excellence. |
DevOps 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
Infrastructure
Containerization
Monitoring
Security
Documentation
Additional Resources
