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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GraphQL for AI Services: Flexible Querying for LLM Applications
GraphQL provides flexible querying for LLM applications. After implementing GraphQL for 15+ AI services, I’ve learned what works. Here’s the complete guide to using GraphQL for AI services. Figure 1: GraphQL Architecture for AI Services Why GraphQL for AI Services GraphQL offers significant advantages for AI services: Flexible queries: Clients request exactly what they need […]
Read more →Fine-Tuning vs RAG: A Comprehensive Decision Framework
Last year, I faced a critical decision: fine-tune our LLM or implement RAG? We chose fine-tuning. It was expensive, time-consuming, and didn’t solve our core problem. After building 20+ LLM applications, I’ve learned when to use each approach. Here’s the comprehensive decision framework that will save you months of work. Figure 1: Fine-Tuning vs RAG […]
Read more →Edge AI with ONNX Runtime: Running Models On-Device
Last year, I deployed an AI model to a mobile device. The first attempt failed—the model was too large, inference was too slow, and battery drain was unacceptable. After optimizing 15+ models for edge deployment using ONNX Runtime, I’ve learned what works. Here’s the complete guide to running AI models on-device with ONNX Runtime. Figure […]
Read more →Serverless AI Architecture: Building Scalable LLM Applications
Three years ago, I built my first serverless LLM application. It failed spectacularly. Cold starts made responses take 15 seconds. Timeouts killed long-running requests. Costs spiraled out of control. After architecting 30+ serverless AI systems, I’ve learned what works. Here’s the complete guide to building scalable serverless LLM applications. Figure 1: Serverless AI Architecture Overview […]
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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