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Foundation · architecture

Why Kubernetes for generative AI

You will be able to defend the choice of Kubernetes for an LLM workload — and explain what changes when the workload is a 30 GB model.

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0 / 3 lessons
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  1. 01
    Why Kubernetes for generative AI
    What changes when the workload is a 30 GB model behind an API
  2. 02
    The generative AI workload lifecycle
    From a model on Hugging Face to a paying customer's request
  3. 03
    Containers, pods, nodes for AI workloads
    What standard Kubernetes already gets right — and where it breaks
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Bursty LLM inference endpoint

Serve a 13B chat model behind a public API. Traffic doubles in 30s twice a day. Cold start is 4 minutes.

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