Senior Devops

Name: Senior Devops
Author: aaaaqwq

aaaaqwq/agi-super-skills

7 installs
82 repo stars
Updated August 2, 2026
aaaaqwq/agi-super-skills

This is a copy of senior-devops by davila7 - installs and ranking accrue to the original listing.

senior-devops is a Claude Code skill that generates CI/CD pipelines, scaffolds Terraform, and automates deployments across AWS, GCP, and Azure.

About

senior-devops is a Claude Code skill for CI/CD, infrastructure automation, and cloud deployment. It exposes three Python scripts that generate pipelines, scaffold Terraform, and manage deployments, backed by reference guides for CI/CD, infrastructure-as-code, and deployment strategies. It targets AWS, GCP, and Azure with containerization via Docker and Kubernetes.

Generates CI/CD pipelines via pipeline_generator.py
Scaffolds Terraform infrastructure-as-code
Manages deployments across AWS, GCP, and Azure

Senior Devops by the numbers

7 all-time installs (skills.sh)
Data as of Aug 3, 2026 (Skillselion catalog sync)

At a glance

senior-devops capabilities & compatibility

Free; runs local Python scripts, though cloud deployments incur provider costs.

Capabilities: pipeline generation · terraform scaffolding · deployment automation · ci cd setup
Works with: terraform · docker · kubernetes · github · aws · gcp · azure · jenkins
Use cases: devops · ci cd
Pricing: Free

From the docs

What senior-devops says it does

Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure).

SKILL.md

**DevOps:** Docker, Kubernetes, Terraform, GitHub Actions, CircleCI

SKILL.md

npx skills add https://github.com/aaaaqwq/agi-super-skills --skill senior-devops

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Installs	7
repo stars	★ 82
Last updated	August 2, 2026
Repository	aaaaqwq/agi-super-skills ↗

What it does

Use when setting up CI/CD pipelines, scaffolding infrastructure-as-code, or automating deployments to a cloud platform.

Who is it for?

Setting up CI/CD pipelines, generating Terraform, and automating cloud deployments.

When should I use this skill?

When the user wants to set up a pipeline, provision infrastructure as code, or automate a deployment.

What you get

Scaffolded pipelines, Terraform infrastructure, and deployment automation following documented best practices.

CI/CD pipeline
Terraform scaffolding
deployment automation

By the numbers

3 core scripts: pipeline generator, terraform scaffolder, deployment manager
3 reference guides bundled

Files

SKILL.mdMarkdownGitHub ↗

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:

# 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:

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:

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:

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

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

# Configure environment
cp .env.example .env

2. Run Quality Checks

# 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

# 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

Cicd Pipeline Guide

Overview

This reference guide provides comprehensive information for senior devops.

Patterns and Practices

Pattern 1: Best Practice Implementation

Description: Detailed explanation of the pattern.

When to Use:

Scenario 1
Scenario 2
Scenario 3

Implementation:

// Example code implementation
export class Example {
  // Implementation details
}

Benefits:

Benefit 1
Benefit 2
Benefit 3

Trade-offs:

Consider 1
Consider 2
Consider 3

Pattern 2: Advanced Technique

Description: Another important pattern for senior devops.

Implementation:

// Advanced example
async function advancedExample() {
  // Code here
}

Guidelines

Code Organization

Clear structure
Logical separation
Consistent naming
Proper documentation

Performance Considerations

Optimization strategies
Bottleneck identification
Monitoring approaches
Scaling techniques

Security Best Practices

Input validation
Authentication
Authorization
Data protection

Common Patterns

Pattern A

Implementation details and examples.

Pattern B

Implementation details and examples.

Pattern C

Implementation details and examples.

Anti-Patterns to Avoid

Anti-Pattern 1

What not to do and why.

Anti-Pattern 2

What not to do and why.

Tools and Resources

Recommended Tools

Tool 1: Purpose
Tool 2: Purpose
Tool 3: Purpose

Conclusion

Key takeaways for using this reference guide effectively.

Deployment Strategies

Overview

This reference guide provides comprehensive information for senior devops.

Patterns and Practices

Pattern 1: Best Practice Implementation

Description: Detailed explanation of the pattern.

When to Use:

Scenario 1
Scenario 2
Scenario 3

Implementation:

// Example code implementation
export class Example {
  // Implementation details
}

Benefits:

Benefit 1
Benefit 2
Benefit 3

Trade-offs:

Consider 1
Consider 2
Consider 3

Pattern 2: Advanced Technique

Description: Another important pattern for senior devops.

Implementation:

// Advanced example
async function advancedExample() {
  // Code here
}

Guidelines

Code Organization

Clear structure
Logical separation
Consistent naming
Proper documentation

Performance Considerations

Optimization strategies
Bottleneck identification
Monitoring approaches
Scaling techniques

Security Best Practices

Input validation
Authentication
Authorization
Data protection

Common Patterns

Pattern A

Implementation details and examples.

Pattern B

Implementation details and examples.

Pattern C

Implementation details and examples.

Anti-Patterns to Avoid

Anti-Pattern 1

What not to do and why.

Anti-Pattern 2

What not to do and why.

Tools and Resources

Recommended Tools

Tool 1: Purpose
Tool 2: Purpose
Tool 3: Purpose

Conclusion

Key takeaways for using this reference guide effectively.

Infrastructure As Code

Overview

This reference guide provides comprehensive information for senior devops.

Patterns and Practices

Pattern 1: Best Practice Implementation

Description: Detailed explanation of the pattern.

When to Use:

Scenario 1
Scenario 2
Scenario 3

Implementation:

// Example code implementation
export class Example {
  // Implementation details
}

Benefits:

Benefit 1
Benefit 2
Benefit 3

Trade-offs:

Consider 1
Consider 2
Consider 3

Pattern 2: Advanced Technique

Description: Another important pattern for senior devops.

Implementation:

// Advanced example
async function advancedExample() {
  // Code here
}

Guidelines

Code Organization

Clear structure
Logical separation
Consistent naming
Proper documentation

Performance Considerations

Optimization strategies
Bottleneck identification
Monitoring approaches
Scaling techniques

Security Best Practices

Input validation
Authentication
Authorization
Data protection

Common Patterns

Pattern A

Implementation details and examples.

Pattern B

Implementation details and examples.

Pattern C

Implementation details and examples.

Anti-Patterns to Avoid

Anti-Pattern 1

What not to do and why.

Anti-Pattern 2

What not to do and why.

Tools and Resources

Recommended Tools

Tool 1: Purpose
Tool 2: Purpose
Tool 3: Purpose

Conclusion

Key takeaways for using this reference guide effectively.

#!/usr/bin/env python3
"""
Deployment Manager
Automated tool for senior devops tasks
"""

import os
import sys
import json
import argparse
from pathlib import Path
from typing import Dict, List, Optional

class DeploymentManager:
    """Main class for deployment manager functionality"""
    
    def __init__(self, target_path: str, verbose: bool = False):
        self.target_path = Path(target_path)
        self.verbose = verbose
        self.results = {}
    
    def run(self) -> Dict:
        """Execute the main functionality"""
        print(f"🚀 Running {self.__class__.__name__}...")
        print(f"📁 Target: {self.target_path}")
        
        try:
            self.validate_target()
            self.analyze()
            self.generate_report()
            
            print("✅ Completed successfully!")
            return self.results
            
        except Exception as e:
            print(f"❌ Error: {e}")
            sys.exit(1)
    
    def validate_target(self):
        """Validate the target path exists and is accessible"""
        if not self.target_path.exists():
            raise ValueError(f"Target path does not exist: {self.target_path}")
        
        if self.verbose:
            print(f"✓ Target validated: {self.target_path}")
    
    def analyze(self):
        """Perform the main analysis or operation"""
        if self.verbose:
            print("📊 Analyzing...")
        
        # Main logic here
        self.results['status'] = 'success'
        self.results['target'] = str(self.target_path)
        self.results['findings'] = []
        
        # Add analysis results
        if self.verbose:
            print(f"✓ Analysis complete: {len(self.results.get('findings', []))} findings")
    
    def generate_report(self):
        """Generate and display the report"""
        print("\n" + "="*50)
        print("REPORT")
        print("="*50)
        print(f"Target: {self.results.get('target')}")
        print(f"Status: {self.results.get('status')}")
        print(f"Findings: {len(self.results.get('findings', []))}")
        print("="*50 + "\n")

def main():
    """Main entry point"""
    parser = argparse.ArgumentParser(
        description="Deployment Manager"
    )
    parser.add_argument(
        'target',
        help='Target path to analyze or process'
    )
    parser.add_argument(
        '--verbose', '-v',
        action='store_true',
        help='Enable verbose output'
    )
    parser.add_argument(
        '--json',
        action='store_true',
        help='Output results as JSON'
    )
    parser.add_argument(
        '--output', '-o',
        help='Output file path'
    )
    
    args = parser.parse_args()
    
    tool = DeploymentManager(
        args.target,
        verbose=args.verbose
    )
    
    results = tool.run()
    
    if args.json:
        output = json.dumps(results, indent=2)
        if args.output:
            with open(args.output, 'w') as f:
                f.write(output)
            print(f"Results written to {args.output}")
        else:
            print(output)

if __name__ == '__main__':
    main()

#!/usr/bin/env python3
"""
Pipeline Generator
Automated tool for senior devops tasks
"""

import os
import sys
import json
import argparse
from pathlib import Path
from typing import Dict, List, Optional

class PipelineGenerator:
    """Main class for pipeline generator functionality"""
    
    def __init__(self, target_path: str, verbose: bool = False):
        self.target_path = Path(target_path)
        self.verbose = verbose
        self.results = {}
    
    def run(self) -> Dict:
        """Execute the main functionality"""
        print(f"🚀 Running {self.__class__.__name__}...")
        print(f"📁 Target: {self.target_path}")
        
        try:
            self.validate_target()
            self.analyze()
            self.generate_report()
            
            print("✅ Completed successfully!")
            return self.results
            
        except Exception as e:
            print(f"❌ Error: {e}")
            sys.exit(1)
    
    def validate_target(self):
        """Validate the target path exists and is accessible"""
        if not self.target_path.exists():
            raise ValueError(f"Target path does not exist: {self.target_path}")
        
        if self.verbose:
            print(f"✓ Target validated: {self.target_path}")
    
    def analyze(self):
        """Perform the main analysis or operation"""
        if self.verbose:
            print("📊 Analyzing...")
        
        # Main logic here
        self.results['status'] = 'success'
        self.results['target'] = str(self.target_path)
        self.results['findings'] = []
        
        # Add analysis results
        if self.verbose:
            print(f"✓ Analysis complete: {len(self.results.get('findings', []))} findings")
    
    def generate_report(self):
        """Generate and display the report"""
        print("\n" + "="*50)
        print("REPORT")
        print("="*50)
        print(f"Target: {self.results.get('target')}")
        print(f"Status: {self.results.get('status')}")
        print(f"Findings: {len(self.results.get('findings', []))}")
        print("="*50 + "\n")

def main():
    """Main entry point"""
    parser = argparse.ArgumentParser(
        description="Pipeline Generator"
    )
    parser.add_argument(
        'target',
        help='Target path to analyze or process'
    )
    parser.add_argument(
        '--verbose', '-v',
        action='store_true',
        help='Enable verbose output'
    )
    parser.add_argument(
        '--json',
        action='store_true',
        help='Output results as JSON'
    )
    parser.add_argument(
        '--output', '-o',
        help='Output file path'
    )
    
    args = parser.parse_args()
    
    tool = PipelineGenerator(
        args.target,
        verbose=args.verbose
    )
    
    results = tool.run()
    
    if args.json:
        output = json.dumps(results, indent=2)
        if args.output:
            with open(args.output, 'w') as f:
                f.write(output)
            print(f"Results written to {args.output}")
        else:
            print(output)

if __name__ == '__main__':
    main()

#!/usr/bin/env python3
"""
Terraform Scaffolder
Automated tool for senior devops tasks
"""

import os
import sys
import json
import argparse
from pathlib import Path
from typing import Dict, List, Optional

class TerraformScaffolder:
    """Main class for terraform scaffolder functionality"""
    
    def __init__(self, target_path: str, verbose: bool = False):
        self.target_path = Path(target_path)
        self.verbose = verbose
        self.results = {}
    
    def run(self) -> Dict:
        """Execute the main functionality"""
        print(f"🚀 Running {self.__class__.__name__}...")
        print(f"📁 Target: {self.target_path}")
        
        try:
            self.validate_target()
            self.analyze()
            self.generate_report()
            
            print("✅ Completed successfully!")
            return self.results
            
        except Exception as e:
            print(f"❌ Error: {e}")
            sys.exit(1)
    
    def validate_target(self):
        """Validate the target path exists and is accessible"""
        if not self.target_path.exists():
            raise ValueError(f"Target path does not exist: {self.target_path}")
        
        if self.verbose:
            print(f"✓ Target validated: {self.target_path}")
    
    def analyze(self):
        """Perform the main analysis or operation"""
        if self.verbose:
            print("📊 Analyzing...")
        
        # Main logic here
        self.results['status'] = 'success'
        self.results['target'] = str(self.target_path)
        self.results['findings'] = []
        
        # Add analysis results
        if self.verbose:
            print(f"✓ Analysis complete: {len(self.results.get('findings', []))} findings")
    
    def generate_report(self):
        """Generate and display the report"""
        print("\n" + "="*50)
        print("REPORT")
        print("="*50)
        print(f"Target: {self.results.get('target')}")
        print(f"Status: {self.results.get('status')}")
        print(f"Findings: {len(self.results.get('findings', []))}")
        print("="*50 + "\n")

def main():
    """Main entry point"""
    parser = argparse.ArgumentParser(
        description="Terraform Scaffolder"
    )
    parser.add_argument(
        'target',
        help='Target path to analyze or process'
    )
    parser.add_argument(
        '--verbose', '-v',
        action='store_true',
        help='Enable verbose output'
    )
    parser.add_argument(
        '--json',
        action='store_true',
        help='Output results as JSON'
    )
    parser.add_argument(
        '--output', '-o',
        help='Output file path'
    )
    
    args = parser.parse_args()
    
    tool = TerraformScaffolder(
        args.target,
        verbose=args.verbose
    )
    
    results = tool.run()
    
    if args.json:
        output = json.dumps(results, indent=2)
        if args.output:
            with open(args.output, 'w') as f:
                f.write(output)
            print(f"Results written to {args.output}")
        else:
            print(output)

if __name__ == '__main__':
    main()

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FAQ

Which cloud platforms does senior-devops target?

It covers AWS, GCP, and Azure, with Docker, Kubernetes, Terraform, GitHub Actions, and CircleCI in its stack.

How does the skill run its capabilities?

Through three Python scripts: pipeline_generator.py, terraform_scaffolder.py, and deployment_manager.py.

DevOps & CI/CDdeployinframonitoring

About

Senior Devops by the numbers

senior-devops capabilities & compatibility

What senior-devops says it does

Add your badge

What it does

Who is it for?

When should I use this skill?

What you get

By the numbers

Files

Senior Devops

Quick Start

Main Capabilities

Core Capabilities

1. Pipeline Generator

2. Terraform Scaffolder

3. Deployment Manager

Reference Documentation

Cicd Pipeline Guide

Infrastructure As Code

Deployment Strategies

Tech Stack

Development Workflow

1. Setup and Configuration

2. Run Quality Checks

3. Implement Best Practices

Best Practices Summary

Code Quality

Performance

Security

Maintainability

Common Commands

Troubleshooting

Common Issues

Getting Help

Resources

Cicd Pipeline Guide

Overview

Patterns and Practices

Pattern 1: Best Practice Implementation

Pattern 2: Advanced Technique

Guidelines

Code Organization

Performance Considerations

Security Best Practices

Common Patterns

Pattern A

Pattern B

Pattern C

Anti-Patterns to Avoid

Anti-Pattern 1

Anti-Pattern 2

Tools and Resources

Recommended Tools

Further Reading

Conclusion

Deployment Strategies

Overview

Patterns and Practices

Pattern 1: Best Practice Implementation

Pattern 2: Advanced Technique

Guidelines

Code Organization

Performance Considerations

Security Best Practices

Common Patterns

Pattern A

Pattern B

Pattern C

Anti-Patterns to Avoid

Anti-Pattern 1

Anti-Pattern 2

Tools and Resources

Recommended Tools

Further Reading

Conclusion

Infrastructure As Code

Overview

Patterns and Practices