> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tensormesh.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Install on SUSE Rancher / RKE2

> Run the Tensormesh Operator on SUSE Rancher + RKE2 (SLES) for SUSE AI — supported versions and platform notes.

The Tensormesh Operator runs on the SUSE platform — SUSE Rancher managing RKE2 on SUSE
Linux Enterprise Server — the same way it does on vanilla Kubernetes. Unlike OpenShift,
RKE2 permits the `hostIPC` the cache engine needs out of the box, so **no security overlay
is required**.

<Note>
  Read this **after** [Install with Helm](/operator/installation/helm). This page adds the
  SUSE-specific platform notes; it does not replace the Helm install steps.
</Note>

## Supported SUSE platform

Tensormesh supports **SUSE AI** on SUSE Rancher–managed RKE2. Validated on:

| Component                    | Supported version                       |
| ---------------------------- | --------------------------------------- |
| SUSE Linux Enterprise Server | 15 SP6                                  |
| SUSE Rancher                 | 2.14.3                                  |
| RKE2                         | `v1.35.6+rke2r1`                        |
| Storage                      | Longhorn (SUSE Storage) — ReadWriteMany |
| GPU                          | NVIDIA (validated on L4)                |

Tensormesh tracks the latest supported RKE2 and SUSE Rancher versions per the
[SUSE Rancher support matrix](https://www.suse.com/suse-rancher/support-matrix/all-supported-versions/latest/).
The operator, cache engine, and Helm chart are supported as a matched set — deploy a single
row from the [compatibility matrix](/operator/installation/compatibility) together.

## Why SUSE needs no extra config

Engine pods request `hostIPC` so the LMCache cache server can share memory with the vLLM
worker processes outside the pod. RKE2's default [Pod Security Admission](https://kubernetes.io/docs/concepts/security/pod-security-admission/)
profile is `privileged`, which permits `hostIPC` — so the engine pod starts with no
OpenShift-style SecurityContextConstraint and no `openshift.enabled` flag.

<Note>
  You only need to act if you have **hardened the target namespace to the `baseline` or
  `restricted` PSA level**. In that case either label the namespace
  `pod-security.kubernetes.io/enforce=privileged`, or run the cache in colocated (sidecar)
  mode, which needs no `hostIPC`.
</Note>

## Prerequisites

* An **RKE2 cluster managed by SUSE Rancher** (the supported versions above).
* **GPU-enabled node(s).** Set up the NVIDIA GPU stack on the cluster first — the driver,
  the containerd runtime integration, and the device plugin — following NVIDIA's guidance for
  RKE2 (for example, the NVIDIA GPU Operator). This is a platform prerequisite, independent of
  Tensormesh; on SLES, match the driver to the running kernel. The cache engine schedules only
  on nodes labeled `nvidia.com/gpu.present=true`.
* A **ReadWriteMany StorageClass** for the shared model hub — **Longhorn (SUSE Storage)** works
  out of the box (install `open-iscsi` on every node first).

## Install

Install with Helm exactly as on vanilla Kubernetes — pin **explicit image tags** (never `latest`):

```bash theme={null}
helm install tensormesh-operator \
  oci://ghcr.io/tensormesh-production/charts/tensormesh-operator \
  --version 0.5.2 \
  --namespace tensormesh-operator --create-namespace \
  --wait
```

<Note>
  The chart is distributed through a private registry. Request an access token from the
  Tensormesh team, then authenticate before installing — see
  [Install with Helm → Install](/operator/installation/helm#install).
</Note>

## Verify

```bash theme={null}
# Nodes are SUSE Linux Enterprise + RKE2
kubectl get nodes -o custom-columns=\
'NODE:.metadata.name,OS:.status.nodeInfo.osImage,KUBERNETES:.status.nodeInfo.kubeletVersion'

# The cache engine pod is Running (hostIPC is allowed by default on RKE2)
kubectl get pods -n tensormesh-operator \
  -l app.kubernetes.io/component=cache-engine
```

## Commercial support

Tensormesh provides commercial support for the operator on the SUSE Rancher and RKE2
versions listed above. Contact the Tensormesh team for support terms.

## Next steps

<CardGroup cols={2}>
  <Card title="Helm install reference" icon="ship-wheel" href="/operator/installation/helm">
    Full install, upgrade, and uninstall flow.
  </Card>

  <Card title="Compatibility matrix" icon="table-cells-large" href="/operator/installation/compatibility">
    The matched operator / cache engine / chart version set.
  </Card>

  <Card title="Troubleshooting" icon="stethoscope" href="/operator/installation/troubleshooting">
    Engine scheduling, GPU, and permission diagnostics.
  </Card>

  <Card title="Cache sizing" icon="gauge-high" href="/operator/configuration/cache-sizing">
    Simulate the hit rate and right-size the L1/L2 cache for your workload — including memory-constrained GPUs.
  </Card>
</CardGroup>