Security as Code: Why the Best DevSecOps Teams Treat Vulnerabilities Like Bugs, Not Afterthoughts

The first time I watched a security vulnerability slip through our CI/CD pipeline and make it to production, I felt the same sinking feeling every engineer knows: that moment when you realize the system you trusted has a blind spot. It was 2019, and we had what we thought was a mature DevOps practice. Automated […]

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Building Your First AI Agent with Microsoft Agent Framework (Python) – Part 3

Build a production-ready Research Assistant AI agent using Python. Complete tutorial covering async patterns, @ai_function decorators, multi-turn conversations, and best practices.

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Observability Practices in AI Engineering: A Complete Guide to LLM Monitoring

Master AI observability with this comprehensive guide. Compare Langfuse, Helicone, LangSmith, and other tools. Learn which metrics matter, how to build evaluation pipelines, and implement production-grade monitoring for LLM applications.

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The Modern Data Engineer’s Toolkit: Why Python Became the Lingua Franca of Data Pipelines

After 20 years building data pipelines across multiple languages—Java, Scala, Go, Python—I’ve watched Python evolve from a scripting language to the undisputed standard for data engineering. This article explores why Python became the lingua franca of data pipelines and shares production patterns for building enterprise-grade systems. 1. The Evolution: From Java to Python In 2005, […]

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Disaster Recovery for AI Systems: Multi-Region Deployment Strategies

Disaster Recovery for AI Systems: Multi-Region Deployment Strategies Expert Guide to Building Resilient AI Systems Across Multiple Regions I’ve designed disaster recovery strategies for AI systems that handle millions of requests per day. When a region goes down, your AI application shouldn’t. Multi-region deployment isn’t just about redundancy—it’s about maintaining service availability, data consistency, and […]

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