A comprehensive collection of DevOps tools, infrastructure-as-code templates, and automation scripts for multi-cloud environments. This repository serves as both a production-ready toolkit and a portfolio demonstrating modern DevOps practices.
- Overview
- AI DevOps Suite
- Infrastructure as Code
- Automation Scripts
- CI/CD Workflows
- Getting Started
- License
This repository contains production-ready tools and templates for:
- Multi-cloud infrastructure (AWS, GCP)
- GitLab CI/CD pipeline templates
- AI-powered DevOps automation
- Container orchestration (Docker, Kubernetes)
- Infrastructure provisioning (Terraform, CloudFormation)
- Security scanning and secrets management
Reusable GitLab CI/CD templates located in /ai_devops/:
Modern continuous deployment for GCP Cloud Deploy integration with Kubernetes.
- Automated review app deployment for feature branches
- Multi-environment support (review/staging/production)
- Doppler secrets management integration
- Automatic cleanup of stale review apps
- Template:
ai_devops/cloud-deploy/.gitlab-ci-template.yml
AI-powered Terraform infrastructure change analysis using Google Gemini.
- Automatic sensitive data redaction (16+ patterns)
- Context-aware AI analysis of infrastructure changes
- GitLab MR comment integration
- Support for 10+ Terraform providers
- Script:
ai_devops/terraform-plan-analyzer/terraform_plan_analyzer.py
Automated code review using Google Gemini Pro via Vertex AI.
- Line-by-line code review with severity ratings
- GitLab webhook integration
- Cloud Tasks for asynchronous processing
- Customizable review prompts per project
- Deployment: Google Cloud Run
Centralized secrets management from Doppler to GitLab CI/CD.
- Hierarchical secret resolution
- Branch-to-environment mapping
- Automatic feature branch config creation
- Migration tool for GitLab β Doppler secrets
- Template:
ai_devops/doppler/.gitlab-ci.template.yml
Automated dependency management and update tracking.
- Multi-package-manager support (Terraform, npm, Python, Docker)
- Automated MR creation with release notes
- Issue tracking for available upgrades
- Template:
ai_devops/renovate/.gitlab-ci-template.yml
Container vulnerability and secret detection.
- CVE scanning for CRITICAL/HIGH vulnerabilities
- Secret detection in container images
- GitLab Security Dashboard integration
- Template:
ai_devops/trivy/.gitlab-ci-template.yml
Terraform (/Terraform/)
- GCP Infrastructure: GKE clusters, Cloud Storage, networking
- AWS Infrastructure: EC2, VPC, RDS, security groups
- Reusable Modules: 11+ modules for common infrastructure patterns
- Reference Architectures: Three-tier applications, complete infrastructure examples
- GitLab Agent: Kubernetes agent deployment for GKE
CloudFormation (/cloudformation/)
- VPC and networking configurations
- DynamoDB, EC2, and IAM setups
- Instance scheduling automation
- Multi-version template evolution
Kubernetes (/kubernetes/)
- Multi-tier application stacks (Apache, PostgreSQL, Redis)
- Production-ready manifests
Docker (/docker/)
- Development and production Dockerfiles
- Docker Compose configurations for multi-environment setups
- Docker Swarm stack definitions
Python Scripts (/python-scripts/)
AWS Automation:
- EC2 management (backup, idle detection, cleanup)
- EBS volume management
- AMI lifecycle management
- VPC flow log analysis
- SNS/SQS/DynamoDB integration
GitLab Monitoring:
pipeline-performance-multiple-projects-test.py: Multi-project performance analysisgitlab_pipeline_performance_with_retry.py: Flakiness analysis and retry tracking
Infrastructure Deployment:
- Three-tier high-availability deployment orchestration
- VPC creation automation
Bash Scripts (/bash-scripts/)
- Server provisioning and setup
- Database backup automation (MySQL)
- User management
- File organization and batch operations
- Log cleanup and rotation
- Git automation
Lambda Functions (/lambda-functions/)
Serverless functions for AWS automation:
- EC2 cost optimization
- Storage lifecycle management
- Event-driven data pipelines
- Network monitoring
AWS CLI (/aws-cli/)
Ready-to-use AWS CLI commands for:
- DynamoDB table operations
- EC2 instance management
- IAM policy configuration
GitHub Actions (.github/workflows/)
Pipeline Performance Audit (pipeline-audit.yml):
- Schedule: First Friday of each month at 6:00 UTC
- Purpose: GitLab pipeline performance monitoring and flakiness analysis
- Features:
- Multi-project performance testing
- Retry logic analysis
- Email notifications (success/failure)
- Artifact collection and archiving
- Timezone-aware execution (America/Chicago)
Include templates in your .gitlab-ci.yml:
include:
- remote: 'https://raw.githubusercontent.com/hogtai/public-repo/main/ai_devops/cloud-deploy/.gitlab-ci-template.yml'
- remote: 'https://raw.githubusercontent.com/hogtai/public-repo/main/ai_devops/trivy/.gitlab-ci-template.yml'Reference modules in your Terraform configuration:
module "vpc" {
source = "git::https://github.com/hogtai/public-repo.git//Terraform/modules/vpc"
# ... configuration
}# Example: GitLab pipeline performance analysis
export GITLAB_PROJECT_IDS="123456,789012"
export GITLAB_ACCESS_TOKEN="your-token"
python python-scripts/gitlab/pipeline-performance-multiple-projects-test.pyThis repository includes multiple security features:
- Automatic secret redaction in Terraform plans
- Container vulnerability scanning (Trivy)
- Secret detection in CI/CD pipelines
- Centralized secrets management (Doppler)
- Token-based authentication for webhooks
Cloud Platforms: AWS, Google Cloud Platform Infrastructure: Terraform, CloudFormation, Kubernetes, Docker CI/CD: GitLab CI/CD, GitHub Actions Languages: Python, Bash, HCL, YAML AI/ML: Google Gemini Pro, Vertex AI Security: Trivy, Doppler Automation: Renovate Bot, Cloud Deploy
- 72+ production-ready scripts and templates
- 6 AI-powered DevOps tools
- Multi-cloud support (AWS + GCP)
- 11+ reusable Terraform modules
- Automated security scanning and dependency management
This repository is licensed under the MIT License. Feel free to use, modify, and distribute the contents as needed.
Made with β€οΈ by Tait Hoglund
Cloud Engineer | DevOps Specialist | Infrastructure Automation