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Read more →Tips and Tricks – Use AWS Lambda Layers for Shared Dependencies
Share common code and dependencies across Lambda functions to reduce deployment size.
Read more →The Patterns That Actually Matter: What Building Microservices at Scale Taught Me About Distributed Systems
🎓 AUTHORITY NOTE This content reflects 20+ years of hands-on enterprise software engineering and architecture experience. Recommendations are production-tested and enterprise-validated. Executive Summary The transition from monolithic architectures to microservices is often painted as a silver bullet for scalability. However, without the right distributed system patterns, it often results in a “distributed monolith”—a system that […]
Read more →Tips and Tricks – Use Terraform Modules for Reusable Infrastructure
Create reusable infrastructure components with Terraform modules for consistency and DRY code.
Read more →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 […]
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.
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