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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 →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 →Production-Ready Agents: Observability, Security & Deployment – Part 8
Deploy AI agents to production with enterprise-grade observability, security, and resilience. Complete guide to OpenTelemetry, content safety, and Azure deployment.
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 →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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