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- Claude Code
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Use this resource to autoscale LLM inference on Kubernetes automatically
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In a terminal, from the folder you want:
npx --yes palatekit@latest install llm-inference-autoscaling-kedaWith 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 NVIDIA GPU Operator, deploys vLLM pods with GPU resources, then configures KEDA on Prometheus metrics or a Redis queue, with a mix of on-demand and spot GPUs. You get autoscaling manifests and a cost strategy.
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Updated November 2, 2026
You say
“Set up KEDA autoscaling for our vLLM service based on the request queue length.”

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