Kubernetes has become one of the most popular container orchestration tools, and Azure Kubernetes Service (AKS) is a managed Kubernetes service provided by Microsoft Azure. With the increasing use of Kubernetes and AKS, there is a growing need to improve the security and management of access to cloud resources. AKS pod managed identity is a […]
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Advanced RAG Patterns: From Naive Retrieval to Production-Grade Systems (Part 1 of 2)
Introduction: Retrieval-Augmented Generation (RAG) has become the go-to architecture for building LLM applications that need access to private or current information. By retrieving relevant documents and including them in the prompt, RAG grounds LLM responses in factual content, reducing hallucinations and enabling knowledge that wasn’t in the training data. But naive RAG implementations often disappoint—the […]
Read more →HL7 v3: Understanding RIM and Why v3 Failed to Replace v2
Executive Summary HL7 v3 was designed in the 1990s as the successor to HL7 v2, promising a rigorous, model-driven approach based on the Reference Information Model (RIM). Despite 20+ years of development and standardization, v3 never achieved widespread adoption. Understanding why v3 failed—and where it still matters—is crucial for architects navigating healthcare interoperability standards. 🏥 […]
Read more →Enterprise Machine Learning in Production: Healthcare and Financial Services Case Studies
Real-world enterprise ML implementations in healthcare diagnostics and financial fraud detection. Explore RAG and LLM integration patterns, ML maturity frameworks, and strategic recommendations for building ML-enabled organizations.
Read more →How is AKS workload identity different from AKS pod managed identity?
AKS workload identity and AKS pod managed identity both provide a way to manage access to Azure resources from within a Kubernetes cluster. However, there are some key differences between the two features. Scope AKS pod managed identity provides a managed identity for each individual pod within a Kubernetes cluster. This allows you to grant […]
Read more →MLOps Best Practices: Building Production Machine Learning Pipelines That Scale
Master MLOps practices for production machine learning systems. Learn data versioning, experiment tracking with MLflow, CI/CD for ML, model registry governance, and monitoring strategies for AWS, Azure, and GCP.
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