Senior Devops
- 48 installs
- 51 repo stars
- Updated November 25, 2025
- ovachiever/droid-tings
This is a copy of senior-devops by davila7 - installs and ranking accrue to the original listing.
Helps with devops & ci/cd tasks during AI-assisted development.
About
senior-devops is a Claude Code skill for devops & ci/cd. It helps solo builders move faster with AI-assisted coding.
- senior-devops
- DevOps & CI/CD
- AI-coding skill
Senior Devops by the numbers
- 48 all-time installs (skills.sh)
- Data as of Jul 27, 2026 (Skillselion catalog sync)
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| Installs | 48 |
|---|---|
| repo stars | ★ 51 |
| Last updated | November 25, 2025 |
| Repository | ovachiever/droid-tings ↗ |
What it does
Helps with devops & ci/cd tasks during AI-assisted development.
Files
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 .env2. Run Quality Checks
# Use the analyzer script
python scripts/terraform_scaffolder.py .
# Review recommendations
# Apply fixes3. Implement Best Practices
Follow the patterns and practices documented in:
references/cicd_pipeline_guide.mdreferences/infrastructure_as_code.mdreferences/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
Further Reading
- Resource 1
- Resource 2
- Resource 3
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
Further Reading
- Resource 1
- Resource 2
- Resource 3
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
Further Reading
- Resource 1
- Resource 2
- Resource 3
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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