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 consistent […]
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Multi-Agent Orchestration Patterns in Microsoft Agent Framework – Part 7
Master the five orchestration patterns: Sequential, Concurrent, Handoff, Group Chat, and Magentic. Learn when to use each pattern.
Read more →The Dawn of .NET 10 and C# 14: A New Era of Performance and Language Innovation Arrives
November 2025 marks a watershed moment in the history of the .NET ecosystem. With the release of .NET 10, Microsoft has not only cemented the platform’s dominance in cloud-native performance but has also delivered the most requested language features in a decade with C# 14. This release focuses on “Zero-Cost Abstractions 2.0″—pushing the boundaries of […]
Read more →Case Study: Enterprise Healthcare Integration – Building a HIPAA-Compliant Patient-Provider Platform
The Challenge: Healthcare Integration at Scale Solution Architecture: High-Level Design (HLD) ⚖️ COMPLIANCE HIPAA Requirements Met: All PHI encrypted using AES-256 (at rest) and TLS 1.3 (in transit). Comprehensive audit logging captures all data access events with immutable records stored in Azure Monitor. Access controls implement principle of least privilege using Azure AD RBAC with […]
Read more →Spark Isn’t Magic: What Twenty Years of Data Engineering Taught Me About Distributed Processing
🎓 AUTHORITY NOTE Drawing from 20+ years of data engineering experience across Fortune 500 enterprises, having architected and optimized Spark deployments processing petabytes of data daily. This represents production-tested knowledge, not theoretical understanding. Executive Summary Every few years, a technology emerges that fundamentally changes how we think about data processing. MapReduce did it in 2004. […]
Read more →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: […]
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