Introduction: As LLM applications grow in complexity, managing prompts becomes a significant engineering challenge. Hard-coded prompts scattered across your codebase make iteration difficult, A/B testing impossible, and debugging a nightmare. Prompt template management solves this by treating prompts as first-class configuration—versioned, validated, and dynamically rendered. A good template system separates prompt logic from application code, […]
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Azure Traffic Manager: A Solutions Architect’s Guide to Global DNS-Based Load Balancing
In the world of globally distributed applications, ensuring users connect to the optimal endpoint is crucial for performance and reliability. Azure Traffic Manager stands as Microsoft’s DNS-based traffic load balancer, enabling you to distribute traffic across global Azure regions and external endpoints. After architecting numerous multi-region deployments, I’ve come to appreciate Traffic Manager as an […]
Read more →Orchestrating Enterprise Data Pipelines with Google Cloud Composer and Apache Airflow
Production-tested patterns for orchestrating enterprise data pipelines with Google Cloud Composer and Apache Airflow. Includes architecture, code examples, security, and cost optimization strategies.
Read more →EU EEHRxF: The Future of European Health Record Exchange
What is EEHRxF? EEHRxF vs IPS vs eHDSI EEHRxF Architecture EEHRxF Clinical Dataset Ireland’s EEHRxF Readiness FHIR Implementation Example Standards and References Series Conclusion Related Articles in This Series Conclusion
Read more →Production Deployment on Google Cloud – Part 4 of 5
Deploy ADK agents to production on Google Cloud. Complete guide covering Cloud Run, Vertex AI Agent Engine, and GKE deployments with observability, security, and CI/CD pipelines.
Read more →Knowledge Graph Integration: Structured Reasoning for LLM Applications
Introduction: Vector search finds semantically similar content, but it misses the structured relationships that make knowledge truly useful. Knowledge graphs capture entities and their relationships explicitly—who works where, what depends on what, how concepts connect. Combining knowledge graphs with LLMs creates systems that can reason over structured relationships while generating natural language responses. This guide […]
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