AI agents that can write and execute code introduce significant security risks—from data exfiltration to resource abuse. Azure Container Apps Dynamic Sessions provides a solution: ephemeral, sandboxed execution environments that isolate agent-generated code from your production infrastructure. This comprehensive guide explores how to implement secure code execution for AI code interpreters, automated testing agents, and […]
Read more →Data Quality for AI: Ensuring High-Quality Training Data
Data quality determines AI model performance. After managing data quality for 100+ AI projects, I’ve learned what matters. Here’s the complete guide to ensuring high-quality training data. Figure 1: Data Quality Framework Why Data Quality Matters Data quality directly impacts model performance: Accuracy: Poor data leads to poor predictions Bias: Biased data creates biased models […]
Read more →Production Model Deployment Patterns: From REST APIs to Kubernetes Orchestration in Python
After deploying hundreds of ML models to production across startups and enterprises, I’ve learned that model deployment is where most AI projects fail. Not because the models don’t work—but because teams underestimate the engineering complexity of serving predictions reliably at scale. This article shares production-tested deployment patterns from REST APIs to Kubernetes orchestration. 1. The […]
Read more →Migration Guide: From Semantic Kernel & AutoGen to Microsoft Agent Framework – Part 10
Complete migration guide from Semantic Kernel and AutoGen to Microsoft Agent Framework. Before/after code examples and step-by-step instructions.
Read more →The Server-First Revolution: How React Server Components Changed Everything I Thought I Knew About Frontend Architecture
For eight years, I built React applications the same way everyone else did: render everything on the client, fetch data with useEffect, and watch the bundle size grow with every new feature. Then React Server Components arrived, and I had to unlearn almost everything I thought I knew about frontend architecture. Server Components vs Client […]
Read more →Real-Time Data Streaming with Apache Kafka: Building Production Event Pipelines in Python
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, […]
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