Graduated with a Diploma in Shipbuilding Technology and worked as a project engineer at FMC Dockyard, Chittagong. Spent three years in an environment where precision isn't a preference — it's a structural requirement. Drawings had to match what production could actually build, and every handoff between engineering and the shop floor had to be unambiguous.

While still working in engineering, I taught myself Python and Shell scripting and took on a part-time remote IT support role at NEON Publication, Dhaka — then moved into it full-time. Managing real Linux systems taught me what keeps infrastructure alive: monitoring, backups, and scripts that remove manual work. That confirmed automation was what I wanted to do full-time.

At Seatrium in Singapore, I build automation with Python, Shell, and Power Platform that processes 10,000+ daily submissions — cutting the failure rate from 35.65% to 1.47% and processing time to about 5–30 seconds. In parallel, I completed an 18-month DevOps apprenticeship through the DevOps Career Track by Poridhi (Dec 2023 – May 2025). Every project on this GitHub reflects hands-on implementation — not copy-pasted YAML.

Pursuing a Bachelor's in Computer Science (Cloud Computing) at INTI International University. Earned the OCI Architect Associate and Foundations Associate certifications in Oct 2026, and now preparing for AWS Solutions Architect Associate. My learning style is hands-on first: I build the thing, break it, rebuild it better, then write about it.

Production-style Kubernetes infrastructure on AWS EKS, designed for multi-environment deployments. Implements a complete IaC stack covering cluster provisioning, node group management, IAM role binding, and network policies — built to be cost-effective without sacrificing scalability or reliability.

Lightweight K3s Kubernetes cluster on AWS, fully automated through Terraform. A complete infrastructure-as-code blueprint covering EC2 provisioning, VPC networking, and K3s cluster bootstrapping — demonstrating that lightweight doesn't mean cutting corners on production readiness.

Hands-on implementation of Kubernetes Horizontal Pod Autoscaler — the mechanism that separates truly elastic systems from ones that just claim to be. Builds a real workload, fires synthetic traffic at it, and watches the cluster respond: pods scale out under load, scale back when it clears. Includes metrics-server setup and threshold tuning.

Implementation of zero-downtime deployment strategies using Kubernetes rolling updates and rollbacks. Covers maxSurge/maxUnavailable tuning, readiness probe configuration, and rollback execution — the real ops work that keeps services alive through deployments. Includes failure simulation and controlled recovery.

Comprehensive Jenkins CI/CD implementation from bare infrastructure to a fully operational distributed build environment. Covers automated server provisioning on AWS, controller-agent architecture configuration, job management, and pipeline automation — the full pipeline lifecycle, not just a hello-world pipeline.

A multi-container system where NGINX doesn't just run — it's watched. A dedicated watcher container continuously polls the server's health; on failure, a mailer container fires an automated alert instantly. A clean, composable implementation of the sidecar monitoring pattern that reflects how production observability actually works at the container level.

Storage in Kubernetes is where stateless container thinking collides with stateful reality. This article breaks down PV/PVC architecture, storage classes, and access modes — with production-ready patterns for engineers managing data-bearing workloads.

Kubernetes Secrets are powerful and frequently misunderstood. This guide covers Secret types, creation strategies, RBAC scoping, and encryption at rest — everything you need to handle credentials, tokens, and keys safely in a production cluster.