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 […]
Read more →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.
Read more →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 […]
Read more →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.
Read more →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. […]
Read more →Airflow on Kubernetes in Production: Architecture, Deployment, and Cost Optimization
Production-tested patterns for running Apache Airflow on Kubernetes with the KubernetesExecutor. Covers architecture, deployment, auto-scaling, cost optimization, and real-world case studies achieving 40-60% cost savings.
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