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 […]
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LLM Monitoring and Alerting: Building Observability for Production AI Systems
Introduction: LLM monitoring is essential for maintaining reliable, cost-effective AI applications in production. Unlike traditional software where errors are obvious, LLM failures can be subtle—degraded output quality, increased hallucinations, or slowly rising costs that go unnoticed until the monthly bill arrives. Effective monitoring tracks latency, token usage, error rates, output quality, and cost metrics in […]
Read more →Event-Driven Architecture: When and How to Implement
What is Event-Driven Architecture? Event-Driven Architecture Overview When to Use Event-Driven Architecture Event Types & Patterns Implementation: Real-World Example Scenario: E-Commerce Order Processing Producer: Publishing Events Consumer: Processing Events Critical Design Decisions Technology Choices Common Pitfalls & Solutions ⚠️ Top 7 EDA Mistakes 1. Event Coupling: Events that know too much about consumers → Keep […]
Read more →Anthropic Claude SDK: Building AI Applications with Advanced Reasoning and 200K Context
Introduction: Anthropic’s Claude SDK provides developers with access to one of the most capable and safety-focused AI model families available. Claude models are known for their exceptional reasoning abilities, 200K token context windows, and strong performance on complex tasks. The SDK offers a clean, intuitive API for building applications with tool use, vision capabilities, and […]
Read more →The Complete Guide to RAG Architecture: From Fundamentals to Production
Master Retrieval-Augmented Generation (RAG) with this expert-level guide. Learn about RAG types (Naive, Advanced, Modular, Agentic), chunking strategies, embedding models, vector databases, hybrid retrieval, and production best practices with high-quality architecture diagrams.
Read more →Deploying LLM Applications on Cloud Run: A Complete Guide
Last year, I deployed our first LLM application to Cloud Run. What should have taken hours took three days. Cold starts killed our latency. Memory limits caused crashes. Timeouts broke long-running requests. After deploying 20+ LLM applications to Cloud Run, I’ve learned what works and what doesn’t. Here’s the complete guide. Figure 1: Cloud Run […]
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