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Use this resource to autoscale an LLM inference cluster on Kubernetes
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In a terminal, from the folder you want:
npx --yes palatekit@latest install llm-inference-autoscalingWith no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.
First time: connect the CLI with
npx --yes palatekit@latest loginThe agent installs the GPU operator, deploys vLLM with its GPU resources, then configures KEDA on Prometheus metrics or a Redis queue, with ScaledJob for batch work and a mix of on-demand and spot nodes. You get manifests to adapt and test.
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Updated November 2, 2026
You say
“Set up KEDA autoscaling for my vLLM service on my Redis queue length, with spot nodes.”

Skill published by sickn33 under the MIT license, delivered in its original version.
Listed unmodified
« llm-inference-scaling » (sickn33, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.
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