In the world of cloud-native applications, secrets management has evolved from a necessary evil to a critical architectural concern. Azure Key Vault stands as Microsoft’s answer to centralized secrets, keys, and certificate management, providing a secure foundation for enterprise applications. Having implemented Key Vault across dozens of production environments, I’ve come to appreciate its role […]
Read more →Author: Nithin Mohan TK
Hello Namaste! 👋🏻
I'm an accomplished Enterprise Solution Architect & Engineering Leader with 20+ years of progressive experience architecting, building, and scaling transformative enterprise solutions.
⚜️ Solution Architect / AI & Cloud 📌 Galway, Ireland
AKS Workload Identity
AKS workload identity is a feature of Azure Kubernetes Service (AKS) that enables you to use Azure Active Directory (AAD) to manage access to Azure resources from within a Kubernetes cluster. In this blog post, we’ll explore how AKS workload identity works and how to use it with an example code. How does AKS workload […]
Read more →Function Calling Deep Dive: Building LLM-Powered Tools and Agents
Introduction: Function calling transforms LLMs from text generators into action-taking agents. Instead of just describing what to do, the model can actually do it—query databases, call APIs, execute code, and interact with external systems. OpenAI’s function calling (now called “tools”) and similar features from Anthropic and others let you define available functions, and the model […]
Read more →LlamaIndex: The Data Framework for Building Production RAG Applications
Introduction: LlamaIndex (formerly GPT Index) is the leading data framework for building LLM applications over your private data. While LangChain focuses on chains and agents, LlamaIndex specializes in data ingestion, indexing, and retrieval—the core components of Retrieval Augmented Generation (RAG). With over 160 data connectors through LlamaHub, sophisticated indexing strategies, and production-ready query engines, LlamaIndex […]
Read more →Quantization Methods for LLMs: GPTQ, AWQ, and BitsAndBytes
Last year, I needed to run a 13B parameter model on a 16GB GPU. Full precision required 52GB. After testing GPTQ, AWQ, and BitsAndBytes, I reduced memory to 7GB with minimal accuracy loss. After quantizing 30+ models, I’ve learned which method works best for each scenario. Here’s the complete guide to LLM quantization. Figure 1: […]
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. 🏥 […]
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