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# Enterprise Infrastructure Portfolio
# Infrastructure Engineering Portfolio
This mono-repository showcases enterprise-level Linux infrastructure engineering capabilities through three comprehensive projects demonstrating DevOps and Platform Engineering best practices.
This repository contains independent infrastructure projects focused on automation, migration assurance, and observability. The projects are intentionally small enough to run locally, but structured around the operating patterns used in enterprise platform teams: repeatable workflows, clear evidence artifacts, and operational documentation.
## Projects Overview
## Projects
### 1. Enterprise Infrastructure Simulator
A container-based simulation of enterprise Linux infrastructure with Ansible automation for provisioning, patching, hardening, and decommissioning operations. Includes failure simulation and scaling scenarios.
- [Enterprise Infrastructure Simulator](enterprise-infra-simulator/) - Ansible-driven lifecycle operations for provisioning, patching, hardening, decommissioning, and failure simulation across Linux nodes.
- [Migration Validation Framework](migration-validation-framework/) - Python CLI for collecting before/after system snapshots and producing structured migration comparison results.
- [Observability Stack](observability-stack/) - Docker Compose based logging and dashboard stack with alert rules, sample logs, and incident simulation.
**Key Features:**
- Multi-node Linux simulation using Docker containers
- Ansible playbooks for infrastructure lifecycle management
- Automated scaling and failure injection scripts
- Enterprise-grade inventory and scenario management
## Skills Demonstrated
### 2. Migration Validation Framework
A Python CLI tool for validating system migrations by collecting, comparing, and reporting on system state changes. Generates comprehensive before/after snapshots and HTML reports.
- Infrastructure automation with Ansible
- Operational scenario design and incident simulation
- Migration validation, drift detection, and JSON reporting
- Docker Compose service validation
- Repository hygiene, CI checks, and professional project documentation
**Key Features:**
- Automated system data collection (mounts, services, disk usage)
- JSON snapshot generation and comparison
- HTML report generation with change visualization
- CLI interface for enterprise migration workflows
### 3. Observability Stack
A complete monitoring and logging stack using ELK (Elasticsearch, Logstash, Kibana) and Grafana for comprehensive infrastructure observability.
**Key Features:**
- Docker Compose deployment of full observability stack
- Sample log ingestion and processing pipelines
- Alerting rules and incident simulation scenarios
- Real-time dashboards and monitoring capabilities
## Architecture
See [docs/architecture.md](docs/architecture.md) for detailed architecture overview.
## Runbooks
Operational procedures and troubleshooting guides available in [docs/runbooks.md](docs/runbooks.md).
## Getting Started
Each project contains its own README.md with setup and usage instructions.
## CI/CD
Automated testing and linting via Gitea workflows in [.gitea/workflows/](.gitea/workflows/).
## Prerequisites
- Docker and Docker Compose
- Ansible
- Python 3.8+
- Make
## License
Enterprise Internal Use Only
Each project remains independent and includes its own README, architecture notes, examples, and runnable scenarios.