senior-devops

Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.

104 stars

byyezannnnn

View on GitHub Installation ↓

Best use case

senior-devops is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Teams using senior-devops should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/senior-devops/SKILL.md --create-dirs "https://raw.githubusercontent.com/yezannnnn/agentGroup/main/jarvis/skills/engineering-team/senior-devops/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/senior-devops/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How senior-devops Compares

Feature / Agent	senior-devops	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

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SKILL.md Source

# Senior Devops

Complete toolkit for senior devops with modern tools and best practices.

## Quick Start

### Main Capabilities

This skill provides three core capabilities through automated scripts:

```bash
# Script 1: Pipeline Generator
python scripts/pipeline_generator.py [options]

# Script 2: Terraform Scaffolder
python scripts/terraform_scaffolder.py [options]

# Script 3: Deployment Manager
python scripts/deployment_manager.py [options]
```

## Core Capabilities

### 1. Pipeline Generator

Automated tool for pipeline generator tasks.

**Features:**
- Automated scaffolding
- Best practices built-in
- Configurable templates
- Quality checks

**Usage:**
```bash
python scripts/pipeline_generator.py <project-path> [options]
```

### 2. Terraform Scaffolder

Comprehensive analysis and optimization tool.

**Features:**
- Deep analysis
- Performance metrics
- Recommendations
- Automated fixes

**Usage:**
```bash
python scripts/terraform_scaffolder.py <target-path> [--verbose]
```

### 3. Deployment Manager

Advanced tooling for specialized tasks.

**Features:**
- Expert-level automation
- Custom configurations
- Integration ready
- Production-grade output

**Usage:**
```bash
python scripts/deployment_manager.py [arguments] [options]
```

## Reference Documentation

### Cicd Pipeline Guide

Comprehensive guide available in `references/cicd_pipeline_guide.md`:

- Detailed patterns and practices
- Code examples
- Best practices
- Anti-patterns to avoid
- Real-world scenarios

### Infrastructure As Code

Complete workflow documentation in `references/infrastructure_as_code.md`:

- Step-by-step processes
- Optimization strategies
- Tool integrations
- Performance tuning
- Troubleshooting guide

### Deployment Strategies

Technical reference guide in `references/deployment_strategies.md`:

- Technology stack details
- Configuration examples
- Integration patterns
- Security considerations
- Scalability guidelines

## Tech Stack

**Languages:** TypeScript, JavaScript, Python, Go, Swift, Kotlin
**Frontend:** React, Next.js, React Native, Flutter
**Backend:** Node.js, Express, GraphQL, REST APIs
**Database:** PostgreSQL, Prisma, NeonDB, Supabase
**DevOps:** Docker, Kubernetes, Terraform, GitHub Actions, CircleCI
**Cloud:** AWS, GCP, Azure

## Development Workflow

### 1. Setup and Configuration

```bash
# Install dependencies
npm install
# or
pip install -r requirements.txt

# Configure environment
cp .env.example .env
```

### 2. Run Quality Checks

```bash
# Use the analyzer script
python scripts/terraform_scaffolder.py .

# Review recommendations
# Apply fixes
```

### 3. Implement Best Practices

Follow the patterns and practices documented in:
- `references/cicd_pipeline_guide.md`
- `references/infrastructure_as_code.md`
- `references/deployment_strategies.md`

## Best Practices Summary

### Code Quality
- Follow established patterns
- Write comprehensive tests
- Document decisions
- Review regularly

### Performance
- Measure before optimizing
- Use appropriate caching
- Optimize critical paths
- Monitor in production

### Security
- Validate all inputs
- Use parameterized queries
- Implement proper authentication
- Keep dependencies updated

### Maintainability
- Write clear code
- Use consistent naming
- Add helpful comments
- Keep it simple

## Common Commands

```bash
# Development
npm run dev
npm run build
npm run test
npm run lint

# Analysis
python scripts/terraform_scaffolder.py .
python scripts/deployment_manager.py --analyze

# Deployment
docker build -t app:latest .
docker-compose up -d
kubectl apply -f k8s/
```

## Troubleshooting

### Common Issues

Check the comprehensive troubleshooting section in `references/deployment_strategies.md`.

### Getting Help

- Review reference documentation
- Check script output messages
- Consult tech stack documentation
- Review error logs

## Resources

- Pattern Reference: `references/cicd_pipeline_guide.md`
- Workflow Guide: `references/infrastructure_as_code.md`
- Technical Guide: `references/deployment_strategies.md`
- Tool Scripts: `scripts/` directory

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