Articles

This article presents a phased blueprint for migrating from Google Workspace to Microsoft 365 with zero data loss and minimal downtime. It covers tenant hardeni

Why Most Production Models Fail Because Their Features Are Old, Not Because Their Models Are Bad Continue reading on Medium »

Today’s task was to build a complete DVC ML Pipeline with Remote Storage and Experiments. Continue reading on Medium »

How experience in critical infrastructure, conversations with HPC professionals, and AI-assisted engineering inspired the design of an… Continue reading on Medi

MLOps is not DevOps with a machine learning flavour. It solves a different class of problems — and the organisations that treat it like… Continue reading on Med

Running ML and LLM workloads on Kubernetes often starts with a surprisingly expensive step: getting the model onto the node. Continue reading on Medium »

Architect a robust MLOps pipeline from scratch using Python, Prefect, MLflow, and Flask to power real-time e-commerce tech. Continue reading on Analytics Vidhya

Five battle-tested patterns for building scalable, governed autonomous AI systems at enterprise scale Continue reading on Medium »

Five battle-tested patterns for building scalable, governed autonomous AI systems at enterprise scale Continue reading on Medium »

Compare DevOps, DataOps, MLOps, and ModelOps. Master enterprise AI governance, CI/CT, and scalable platform engineering strategies. Continue reading on Medium »

Why strong data workflows, reusable features, and traceable lineage are the foundation of scalable ML systems Continue reading on Medium »

Most ML tutorials stop the second the model says “87% accuracy.” This one keeps going -through tracking, evaluation, testing, logging, and… Continue reading on

Let’s be brutally honest for a second. Continue reading on Medium »

How to slash your vector database billing, eliminate memory map crashes, and master scalar quantization. Continue reading on Medium »

Project Architecture (AWS Infrastructure Overview) Continue reading on Medium »

MLOps (Machine Learning Operations) is a set of practices that combines Machine Learning (ML), DevOps, and Data Engineering to develop… Continue reading on Medi

Most teams focus on building models. Elite teams focus on keeping them alive in production. Here is the operational framework you are… Continue reading on Mediu

I ran Airflow at home to pull live stock data. Here’s how I did it and what I learned. Continue reading on Analytics Vidhya »

Yesterday, we built a pristine, isolated Python environment. It was clean. It was standard. Continue reading on Medium »

Yesterday, we built a pristine, isolated Python environment. It was clean. It was standard. Continue reading on Medium »

Slack modernized its data platform by replacing SSH based execution in Amazon EMR pipelines with a REST driven orchestration layer called Quarry. The migration

A comprehensive, battle-tested guide to implementing CI/CD pipelines for Machine Learning projects — and why they’re fundamentally… Continue reading on Medium »

A comprehensive, battle-tested guide to implementing CI/CD pipelines for Machine Learning projects — and why they’re fundamentally… Continue reading on Medium »

Every week I see the same pattern: someone posts a 10-minute tutorial installing Ollama, runs a model, asks it a question, and says “done… Continue reading on M