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1 post about AKS. Every summary links to the original.
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A model deployed on AKS is open by default. See how MaaS policies insert Authorino authentication and Limitador rate limits in front of vLLM, so bad keys and over-quota requests stop at the gate.
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Red Hat AI Inference 3.5 extends its Model-as-a-Service (MaaS) governance layer to non-OpenShift Kubernetes distributions, including Azure Kubernetes Service (AKS). MaaS adds multi-tenant API governance on top of the inference platform, controlling authentication, rate limiting, and model access via Authorino and Limitador from Red Hat Connectivity Link (Kuadrant). A model is first deployed with a single LLMInferenceService YAML, creating a vLLM server and router-scheduler, but the endpoint is open. Applying a MaaSSubscription and MaaSAuthPolicy activates governance: Authorino validates API keys or JWTs, and Limitador enforces token rate limits. The post demonstrates three enforcement scenarios on an AKS cluster with a T4 GPU running Qwen3-0.6B: 401 for missing or invalid keys, 200 for authenticated requests, and 429 when rate limits are exceeded, blocking requests before they reach vLLM.
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