devops-engineer

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Translated

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.

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Added on2026-02-07

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SKILL.md Content

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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

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