Introduction: Real-time data streaming has become essential for modern data architectures, enabling immediate insights and actions on data as it arrives. This comprehensive guide explores production streaming patterns using Apache Kafka and Python, covering producer/consumer design, stream processing with Flink, exactly-once semantics, and operational best practices. After building streaming platforms processing billions of events daily,… Continue reading
Author: Nithin Mohan TK
Technology Enthusiast | .NET Specialist | Blogger | Gadget & Hardware Geek
Tips and Tricks – Use AWS Lambda Layers for Shared Dependencies
Share common code and dependencies across Lambda functions to reduce deployment size.
The Patterns That Actually Matter: What Building Microservices at Scale Taught Me About Distributed Systems
The first time I decomposed a monolith into microservices, I made every mistake in the book. We ended up with a distributed monolith—all the complexity of microservices with none of the benefits. That painful experience taught me that microservices architecture isn’t about the services themselves; it’s about the patterns that make them work together. Microservices… Continue reading
Tips and Tricks – Use Terraform Modules for Reusable Infrastructure
Create reusable infrastructure components with Terraform modules for consistency and DRY code.
BigQuery Unleashed: Building Enterprise Data Warehouses That Scale to Petabytes
Introduction: BigQuery stands as Google Cloud’s crown jewel—a serverless, petabyte-scale data warehouse that has fundamentally changed how enterprises approach analytics. This comprehensive guide explores BigQuery’s enterprise capabilities, from columnar storage and slot-based execution to advanced features like BigQuery ML, BI Engine, and real-time streaming. After architecting data platforms across all major cloud providers, I’ve found… Continue reading
ETL for Vector Embeddings: Preparing Data for RAG
Preparing data for RAG requires specialized ETL pipelines. After building pipelines for 50+ RAG systems, I’ve learned what works. Here’s the complete guide to ETL for vector embeddings.
Feature Engineering at Scale: Building Production Feature Stores and Real-Time Serving Pipelines
Introduction: Feature engineering remains the most impactful activity in machine learning, often determining model success more than algorithm selection. This comprehensive guide explores production feature engineering patterns, from feature stores and versioning to automated feature generation and real-time feature serving. After building feature platforms across multiple organizations, I’ve learned that success depends on treating features… Continue reading
The AI Hardware Price Surge: Why GPUs, SSDs, and RAM Are Getting Expensive (And When It’ll End)
Hardware prices are surging due to unprecedented AI demand. Comprehensive analysis of why GPU, SSD, and RAM prices are up 30-70% in 2025, when normalization will occur, and strategic buying recommendations.
The Cloud Bill Always Comes Due: Hard Lessons in FinOps from a Decade of Enterprise Cloud Migrations
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
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