The first time I saw a cloud bill exceed a million dollars in a single month, I knew something had fundamentally changed about how we needed to think about infrastructure. This wasn’t a massive enterprise with unlimited budgets—it was a mid-sized company that had enthusiastically embraced “cloud-first” without understanding what that commitment actually meant financially.… Continue reading
Category: Emerging Technologies
Emerging technologies include a variety of technologies such as educational technology, information technology, nanotechnology, biotechnology, cognitive science, psychotechnology, robotics, and artificial intelligence.
Microsoft Azure AI Foundry: The Complete Guide to Enterprise AI Development
Introduction: Microsoft Azure AI Foundry (formerly Azure AI Studio) represents Microsoft’s unified platform for building, evaluating, and deploying generative AI applications. Announced at Microsoft Ignite 2024, AI Foundry consolidates Azure’s AI capabilities into a single, cohesive experience that spans model selection, prompt engineering, evaluation, fine-tuning, and production deployment. With access to Azure OpenAI models, Meta… Continue reading
Tips and Tricks – Use Multi-Stage Docker Builds for Smaller Images
Reduce container image size by separating build and runtime stages.
MLOps Excellence with MLflow: From Experiment Tracking to Production Model Deployment
Introduction: MLflow has emerged as the leading open-source platform for managing the complete machine learning lifecycle, from experimentation through deployment. This comprehensive guide explores production MLOps patterns using MLflow, covering experiment tracking, model registry, automated deployment pipelines, and monitoring strategies. After implementing MLflow across multiple enterprise ML platforms, I’ve found that success depends on establishing… Continue reading
Tips and Tricks – Use Web Workers for Heavy Computations
Move CPU-intensive tasks off the main thread to keep the UI responsive.
Spark Isn’t Magic: What Twenty Years of Data Engineering Taught Me About Distributed Processing
Every few years, a technology emerges that fundamentally changes how we think about data processing. MapReduce did it in 2004. Apache Spark did it in 2014. And after spending two decades building data pipelines across enterprises of every size, I’ve learned that the difference between a successful Spark implementation and a failed one rarely comes… Continue reading
Data Pipelines for LLM Training: Building Production ETL Systems
Building production ETL pipelines for LLM training is complex. After building pipelines processing 100TB+ of data, I’ve learned what works. Here’s the complete guide to building production data pipelines for LLM training. Figure 1: LLM Training Data Pipeline Architecture Why Production ETL Matters for LLM Training LLM training requires massive amounts of clean, processed data:… Continue reading
Tips and Tricks – Use Intersection Observer for Lazy Loading
Load images and content only when they enter the viewport for faster initial page loads.
Your Copilot Is Watching: The Real Story Behind AI Coding Assistants in 2025
Something shifted in how we write code over the past two years. It wasn’t a single announcement or product launch—it was the gradual realization that the cursor blinking in your IDE now has a silent partner. GitHub Copilot crossed 1.8 million paid subscribers in 2024. Cursor raised $60 million at a $400 million valuation. Amazon… Continue reading
Tips and Tricks – Use functools.cache for Automatic Memoization
Cache expensive function results automatically with the built-in cache decorator.