Running LLM Inference on Kubernetes: What It Actually Takes (opens in new tab)

Teams run their own LLM inference for a range of reasons: data privacy, cost control at volume, latency, the ability to fine-tune, or just the need to operate independently of third-party rate limits and pricing changes. When they say they want to run inference on Kubernetes, they usually mean they want to host a model themselves rather than routing prompts to an API like OpenAI or Anthropic.