Introduction: Google Kubernetes Engine represents the gold standard for managed Kubernetes, built on the same infrastructure that runs Google’s own containerized workloads at massive scale. This deep dive explores GKE’s enterprise capabilities—from Autopilot mode that eliminates node management to advanced features like workload identity, binary authorization, and multi-cluster service mesh. After deploying production Kubernetes clusters […]
Read more →Month: February 2025
Running LLMs on Kubernetes: Production Deployment Guide
Deploying LLMs on Kubernetes requires careful planning. After deploying 25+ LLM models on Kubernetes, I’ve learned what works. Here’s the complete guide to running LLMs on Kubernetes in production. Figure 1: Kubernetes LLM Architecture Why Kubernetes for LLMs Kubernetes offers significant advantages for LLM deployment: Scalability: Auto-scale based on demand Resource management: Efficient GPU and […]
Read more →Streaming LLM Responses: Building Real-Time AI Applications (Part 2 of 2)
Introduction: Waiting 10-30 seconds for an LLM response feels like an eternity. Streaming changes everything—users see tokens appear in real-time, creating the illusion of instant response even when generation takes just as long. Beyond UX, streaming enables early termination (stop generating when you have enough), progressive processing (start working with partial responses), and better error […]
Read more →Inside Ireland’s Healthcare IT: HSE’s Digital Transformation Journey
Executive Summary Ireland’s Health Service Executive (HSE) is undertaking one of Europe’s most ambitious healthcare IT transformation programs. From rolling out the Individual Health Identifier (IHI) to deploying a national Electronic Health Record system, the HSE’s eHealth Ireland strategy is modernizing how 5 million Irish citizens access healthcare services. 🏥 HEALTHCARE INTEROPERABILITY SERIES This article […]
Read more →Types of Machine Learning Explained: Supervised, Unsupervised, and Reinforcement Learning
Deep dive into the three fundamental paradigms of machine learning. Explore supervised learning for predictions, unsupervised learning for pattern discovery, and reinforcement learning for decision optimization with practical Python examples.
Read more →The Rise of GitOps: Automating Deployment and Improving Reliability
GitOps is a relatively new approach to software delivery that has been gaining popularity in recent years. It is a set of practices for managing and deploying infrastructure and applications using Git as the single source of truth. In this blog post, we will explore the concept of GitOps, its key benefits, and some examples […]
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