Building production-grade infrastructure automation from scratch — Python, Linux, Docker, and CI — one modular, well-documented project at a time.

CSE 2nd year student in Bangladesh, self-teaching DevOps and Cloud Automation with the goal of landing a remote-friendly role in this field.

My approach: Build → Test → Break → Troubleshoot → Improve → Document

I don't chase tutorials — I build one system deeply, break it, fix it, and document why every decision was made.

A modular Server Health Monitoring, Alerting & Self-Healing System built to production standards, not toy-project standards:

• Monitoring — CPU/memory/disk/load/network metrics via psutil, host-aware in containers
• Alerting — Telegram, Slack, Email channels with cooldown-based anti-spam logic
• Self-Healing — retry-safe, dry-run-capable remediation via Bash + subprocess
• Scheduling — idempotent cron installer, systemd-safe wrapper scripts
• Containerization — multi-stage Docker build, non-root runtime, host /proc bind-mounts, log-freshness healthcheck
• CI — GitHub Actions: lint → test → security scan (bandit, pip-audit, Trivy) with severity gates
• Testing — 48+ tests, 80%+ coverage, singleton-pattern-aware fixtures
• Workflow — every feature built on its own branch, reviewed, and squash-merged into main

Full architecture, data flow, and design-decision rationale are documented in docs/ — not as an afterthought, but as a first-class part of the build.

Archive of 24+ Python automation scripts — my early practice ground for scripting, problem-solving, and documentation.

Seeking a remote DevOps/Cloud Automation role (part-time or full-time) where I can contribute to infrastructure, CI, monitoring, and automation — while continuing to learn AWS and production systems.

AWS core services to widen where I can apply:

• EC2 · S3 · Lambda · IAM & Security · VPC

Next stop for PhoenixAuto-Ops: real EC2 deployment with CloudWatch monitoring.

Open to remote DevOps/Cloud Automation opportunities — feel free to reach out via LinkedIn or GitHub.