devops-iac-engineer

davila7/claude-code-templates · updated Apr 8, 2026

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$npx skills add https://github.com/davila7/claude-code-templates --skill devops-iac-engineer
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summary

Cloud infrastructure design, provisioning, and operations using IaC, Kubernetes, and DevOps best practices.

  • Covers Terraform, Kubernetes, and multi-cloud platforms (AWS, Azure, GCP) with structured workflows for architecture design, implementation, and validation
  • Includes CI/CD pipeline design, GitOps patterns, and deployment strategies (blue/green, canary) with automated testing and rollback procedures
  • Provides observability frameworks with SLI/SLO/SLA definitions, logging, metrics,
skill.md

DevOps IaC Engineer

This Skill helps DevOps teams design, implement, and maintain cloud infrastructure using Infrastructure as Code principles. Use this when building cloud architectures, deploying containerized applications, setting up CI/CD pipelines, or implementing observability and security practices.

Quick Navigation

  • Terraform & IaC: See terraform.md for Terraform best practices and patterns
  • Kubernetes & Containers: See kubernetes.md for container orchestration
  • Cloud Platforms: See cloud_platforms.md for AWS, Azure, GCP guidance
  • CI/CD Pipelines: See cicd.md for pipeline design and GitOps
  • Observability: See observability.md for monitoring and logging
  • Security: See security.md for DevSecOps practices
  • Templates & Tools: See templates.md for ready-to-use templates

Core Principles

Key DevOps Terminology (Consistent Throughout)

  • Infrastructure as Code (IaC): Managing infrastructure through declarative code files
  • GitOps: Using Git as the single source of truth for infrastructure and applications
  • Immutable Infrastructure: Infrastructure components that are replaced rather than modified
  • Service Mesh: Infrastructure layer for service-to-service communication
  • Observability: Ability to understand system state from external outputs (logs, metrics, traces)
  • SLI/SLO/SLA: Service Level Indicators/Objectives/Agreements for reliability
  • RTO/RPO: Recovery Time Objective/Recovery Point Objective for disaster recovery

Workflow: Infrastructure Implementation

When implementing infrastructure, follow this structured approach:

  1. Understand Requirements

    • What is the business need? (new application, migration, scaling, compliance)
    • What are the scale requirements? (traffic, data, geographic distribution)
    • What are the constraints? (budget, timeline, regulatory)
    • What are the dependencies? (existing systems, data sources)
  2. Design Architecture

    • Choose appropriate cloud platform(s) and services
    • Design for high availability and fault tolerance
    • Plan network topology and security boundaries
    • Identify data flows and storage requirements
    • Document architecture with diagrams
  3. Select IaC Tools

    • Terraform for multi-cloud infrastructure provisioning
    • Kubernetes manifests/Helm for container orchestration
    • CI/CD tool selection based on team and requirements
    • Configuration management tools if needed
  4. Implement Infrastructure

    • Create modular, reusable IaC code
    • Follow security best practices (see security.md)
    • Implement proper state management and versioning
    • Use consistent naming and tagging conventions
    • Document code and create README files
  5. Set Up Observability

    • Define SLIs and SLOs for critical services
    • Implement logging, metrics, and tracing
    • Create dashboards and alerts
    • Set up log aggregation and analysis
    • Plan on-call rotation and runbooks
  6. Implement CI/CD

    • Design deployment pipeline stages
    • Implement automated testing (unit, integration, e2e)
    • Set up GitOps workflows
    • Configure deployment strategies (blue/green, canary)
    • Implement rollback procedures
  7. Test & Validate

    • Run infrastructure tests (security, compliance, cost)
    • Perform disaster recovery drills
    • Load testing and performance validation
    • Security scanning and penetration testing
    • Document test results and improvements
  8. Deploy & Monitor

    • Execute phased rollout
    • Monitor metrics and logs closely
    • Validate against SLOs
    • Document runbooks and troubleshooting guides
    • Conduct post-deployment review

Decision Framework: Tool Selection

Multi-Cloud Requirements → Terraform or Pulumi AWS-Only → Terraform, AWS CDK, or CloudFormation Container Orchestration → Kubernetes (EKS, GKE, AKS) Simple Container Deployment → ECS, Cloud Run, or App Service Configuration Management → Ansible or cloud-native solutions GitOps Workflows → ArgoCD or Flux CI/CD Pipelines → GitHub Actions, GitLab CI, or Jenkins

Common Challenges & Solutions

Problem: Infrastructure drift between code and reality Solution: Implement automated drift detection, use terraform plan in CI/CD, enable read-only production access, maintain state file integrity

Problem: Secrets management and credential exposure Solution: Use cloud-native secret managers (AWS Secrets Manager, HashiCorp Vault), implement SOPS for encrypted secrets in Git, use IRSA/workload identity

Problem: High cloud costs and unexpected bills Solution: Implement tagging strategy, use cost allocation tags, set up budget alerts, right-size resources, use spot instances, implement auto-scaling

Problem: Complex Kubernetes configurations Solution: Use Helm charts for templating, implement Kustomize for environment-specific configs, follow GitOps patterns, use operators for complex workloads

Collaboration Tips

  • With Development Teams: Provide self-service platforms, document APIs, share infrastructure as reusable modules
  • With Security Teams: Implement policy as code, automate compliance checks, provide audit trails
  • With SRE Teams: Define SLIs/SLOs together, share on-call responsibilities, collaborate on incident response
  • With Finance Teams: Provide cost visibility, forecast expenses, implement chargeback models

Next Steps

  1. Start with terraform.md if you're implementing infrastructure as code
  2. Use kubernetes.md for container orchestration
  3. Reference templates.md for ready-to-use configurations
  4. Check observability.md to set up monitoring

Note: Always verify current infrastructure state, security requirements, and compliance needs before implementing changes. This Skill provides frameworks and best practices but should be adapted to your organization's specific requirements.

how to use devops-iac-engineer

How to use devops-iac-engineer on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add devops-iac-engineer
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/davila7/claude-code-templates --skill devops-iac-engineer

The skills CLI fetches devops-iac-engineer from GitHub repository davila7/claude-code-templates and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/devops-iac-engineer

Reload or restart Cursor to activate devops-iac-engineer. Access the skill through slash commands (e.g., /devops-iac-engineer) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.651 reviews
  • Shikha Mishra· Dec 24, 2024

    devops-iac-engineer has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Kaira Wang· Dec 24, 2024

    Useful defaults in devops-iac-engineer — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Kaira Martinez· Dec 24, 2024

    I recommend devops-iac-engineer for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Tariq Ghosh· Dec 20, 2024

    devops-iac-engineer reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • William Huang· Dec 16, 2024

    We added devops-iac-engineer from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Rahul Santra· Nov 15, 2024

    devops-iac-engineer reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Yuki Iyer· Nov 15, 2024

    Solid pick for teams standardizing on skills: devops-iac-engineer is focused, and the summary matches what you get after install.

  • Olivia Tandon· Nov 7, 2024

    devops-iac-engineer fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Hassan Iyer· Nov 7, 2024

    Registry listing for devops-iac-engineer matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Fatima Khanna· Oct 26, 2024

    devops-iac-engineer has been reliable in day-to-day use. Documentation quality is above average for community skills.

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