A collection of tools, code samples, labs, tutorials, and resources for exploring AIOps in enterprise network environments. Ideal for prototyping, learning, and validating real-world use cases.

My personal collection of AIOps and DevOps labs covering Kubernetes, CI/CD, Terraform, Ansible, and observability tools with practical hands-on projects.

MLOps-Project-Library is a curated collection of real-world, production-ready MLOps projects built on Kubernetes, Kubeflow, AWS, GitHub Actions, and AIOps concepts. Designed for DevOps engineers aspiring to master MLOps, this repository showcases practical, end-to-end ML system implementations with automation, observability, and CI/CD.

This repo is built for AIOps aspirants who want to start from scratch and grow step by step. It includes beginner-friendly tutorials, hands-on labs, and industry-standard projects across DevOps, MLOps, SysOps, Cloud, and Security. Ideal for learners aiming to build practical, job-ready skills in automation,cloud-native tools,and AI-driven operation

AIOps Practical Training Project

Unified AIOps on AWS — Practical Build Log

XOps explained. A practical guide to DevOps, MLOps, DataOps, SecOps, CloudOps, GitOps, and AIOps with real-world examples.

Practical Bash and Python scripts for day-to-day operations: AWS/cloud tasks, network diagnostics, system health checks, security audits, backups, and reliability workflows. Built from production experience and evolving toward Platform Engineering, FinOps, and AIOps.