AI Engineering
LLM Serving Infrastructure at Scale
How to serve LLMs in production with vLLM, TGI, and TensorRT-LLM — covering batching, KV cache, quantization, and GPU memory management.
Akhil Sharma
February 4, 2026
12 min read
LLMInfrastructureGPUvLLM
More in AI Engineering
Building Reliable LLM Evaluation Pipelines
How to evaluate LLM outputs systematically with automated metrics, LLM-as-judge, human review, and CI/CD integration for prompt regression testing.
Prompt Caching Strategies That Cut Your LLM Costs in Half
Practical caching strategies for LLM applications — from exact match to semantic similarity caching to provider-level prefix caching — with real cost/latency numbers.
