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AxiLayer AI · Integrations · Clouds and AI platforms

Kubernetes integration

Shows security teams the self-hosted AI running on Kubernetes clusters, from GPU nodes to AI-serving containers.

LiveClouds and AI platforms
What it does

What this integration does

The Kubernetes integration shows the AI running on your clusters: inference workloads, GPU nodes, model volumes and AI-serving containers. Cluster information reaches AxiReady and AxiSentinel by import or by a host node, giving security teams a clear picture of self-hosted AI that can sit outside cloud AI inventories.

Benefits

Benefits

Expose self-hosted inferenceBrings inference workloads into view when teams run models on clusters instead of a managed AI service.
Map GPU capacity to AIShows which GPU nodes support AI work, helping teams connect costly hardware to known systems and owners.
Locate model volumesHelps reviewers see where model volumes sit in a cluster, so stored models get a named owner.
Include isolated clustersGives security teams a route to review clusters on restricted networks through import or a host node.
Use cases

Use cases

GPU census for a colocation operator

A colocation operator wants to know which GPU nodes carry AI work across its clusters. Its security team sees inference workloads beside the hardware and gains a clearer view of AI inside its halls.

Review of an isolated cluster

A defense program runs AI on a cluster inside a classified network. By import, its security team sees AI-serving containers and model volumes there, which keeps a sensitive enclave inside the wider AI review.

Model volumes on the line

A robotics maker hosts inspection models on a plant cluster. Its security team sees the model volumes and inference workloads behind the line, so each one can be tied to an accountable engineering owner.

Coverage is confirmed for your environment during onboarding. Product names belong to their owners and are used only to describe a technical connection.

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