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

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