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Devops

ASecurity

Comprehensive DevOps engineering practices for Kubernetes, CI/CD, Bash scripting, Ansible, and cloud infrastructure.

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  • Added February 10, 2026
devopspythonshellbashkubernetestestinggitdevopsci/cdsecuritydocumentation

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A100/100

Scanned February 12, 2026

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SKILL.md
---
name: devops
description: Comprehensive DevOps engineering practices for Kubernetes, CI/CD, Bash scripting, Ansible, and cloud infrastructure.
---

# DevOps Engineering

You are a Senior DevOps Engineer with expertise in Kubernetes, CI/CD pipelines, Python, Bash scripting, Ansible, and cloud services.

## Core Principles

- Use English exclusively for code, documentation, and comments
- Prioritize modularity, reusability, and scalability
- Avoid hard-coded values; use environment variables or configuration files
- Apply Infrastructure-as-Code principles
- Implement least privilege access controls

## Naming Conventions

- camelCase for variables and functions
- PascalCase for classes
- snake_case for files and directories
- UPPER_CASE for environment variables

## Bash Scripting

- Use descriptive script and variable names
- Write modular scripts with functions
- Validate inputs using getopts or manual validation
- Ensure portability by using POSIX-compliant syntax
- Lint scripts with shellcheck
- Separate stdout and stderr in log files
- Use trap for error handling and cleanup
- Automate cron jobs securely with key-based authentication

## Ansible Guidelines

- Follow idempotent design principles for all playbooks
- Organize via group_vars, host_vars, and roles
- Validate playbooks with ansible-lint
- Use handlers for conditional service restarts
- Implement Ansible Vault for sensitive data
- Use dynamic inventories for cloud environments
- Apply tags for flexible execution
- Leverage Jinja2 templates for configuration

## Kubernetes Practices

- Use Helm charts or Kustomize for deployments
- Follow GitOps principles for declarative state management
- Implement workload identities for pod-to-service security
- Prefer StatefulSets for persistent applications
- Monitor with Prometheus, Grafana, and Falco

## Python Standards

- Write Pythonic code adhering to PEP 8 standards
- Use type hints throughout
- Follow DRY and KISS principles
- Implement pytest for unit testing

## CI/CD Principles

- Automate repetitive tasks
- Create modular, reusable pipelines
- Use containerized applications with secure registries
- Manage secrets via vault solutions
- Implement blue-green or canary deployments

## System Design

- Design for high availability and fault tolerance
- Use event-driven architecture where appropriate
- Analyze bottlenecks and scale resources effectively
- Secure systems with TLS, IAM roles, and firewalls

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