> ## 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.

# Installation

> Install the Operator UI into your cluster, next to the operator.

The UI installs the same way as the operator, from the same private registry — the access token you
already have works for both. If you don't have one, request it from the Tensormesh team.

Install the operator and at least one `LMCacheEngine` first: the UI is a read-only
dashboard over your engines, so it installs fine on an empty cluster but shows "No LMCacheEngines
found" until engines exist.

***

## Prerequisites

* Helm `3.8` or newer (`helm version`)
* A Kubernetes 1.28+ cluster with [Tensormesh Platform](/v1.0.1/installation/helm) installed,
  plus at least one `LMCacheEngine`
* **Prometheus running in the cluster** (with the Prometheus Operator), and the **engine's
  metrics scraped into it**. This powers every trend chart and takes two small steps, covered
  in [Configuration](/v1.0.1/ui/configuration#trend-charts-connect-your-prometheus).
* **The NVIDIA DCGM exporter, if you run GPUs**: standard on GPU clusters (it ships with the
  NVIDIA GPU Operator, and isn't part of Tensormesh). It drives the per-GPU utilization, memory,
  and hardware-fault cards.
* **An access token from the Tensormesh team** — the operator's token works

***

## Versions

Pin an explicit chart version — don't use `latest`. Like the
[platform compatibility matrix](/v1.0.1/installation/compatibility), each row is a
matched set: run the UI chart against the platform versions listed with it.

| UI version | Platform Helm chart | Status | As of |
| - | - | :-: | - |
| `1.0.1` | `1.0.1` | ✅ Supported | 2026-10-20 |

***

## Install

**1. Log in to the Registry (One Time)**

```bash theme={null}
# username isn't validated for token auth — any non-empty value works
echo '<TOKEN_FROM_TENSORMESH>' | helm registry login artifacts.tensormesh.ai -u tensormesh --password-stdin
```

If you already logged in to install the operator, skip this step.

**2. Write a Values File**

```yaml ui-values.yaml theme={null}
engineNamespace: tensormesh-platform      # where your engines run
prometheus:
  url: http://kube-prom-stack-kube-prome-prometheus.monitoring.svc:9090   # yours: kubectl get svc -A | grep -i prometheus
dcgmService: dcgm-exporter.cw-exporters:9400   # GPU cards — yours: kubectl get svc -A | grep -i dcgm
imagePullSecrets:
  - name: tensormesh-registry              # the operator's pull secret works here too
```

The UI picks up cluster access automatically once it's running inside the cluster. You never
set a kube API URL or token. See [Configuration](/v1.0.1/ui/configuration) for how each value
maps to what you see, plus multiple clusters.

**3. Install**

```bash theme={null}
helm upgrade --install tmo-ui \
  oci://artifacts.tensormesh.ai/tensormesh-production/charts/tensormesh-operator-ui \
  --version 1.0.1 -n tensormesh-platform --create-namespace \
  -f ui-values.yaml
```

The [table above](#versions) lists the current chart version and the operator versions it works
with. Pin an explicit version — don't use `latest`.

***

## Verify

```bash theme={null}
helm test tmo-ui -n tensormesh-platform
```

The bundled test confirms the UI is up and serving. If anything looks off once you open the
dashboard, see [Troubleshooting & FAQ](/v1.0.1/ui/troubleshooting).

***

## Open the Dashboard

The install doesn't expose the UI outside the cluster. To open it, port-forward the service:

```bash theme={null}
kubectl -n tensormesh-platform port-forward svc/tmo-ui-tensormesh-operator-ui 8080:80
# open http://localhost:8080
```

For shared team access, enable the ingress (`ingress.enabled=true` with your own hosts and
TLS). The UI has no built-in login, so if you expose it beyond port-forward, put SSO in front at
the ingress (see [Access & Security](/v1.0.1/ui/access-and-security)).

***

## What Gets Installed

A single dashboard pod and a service, nothing on your GPU nodes. Its cluster access is
**strictly read-only**: it can look at engines, pods, and metrics, and cannot modify
anything.

***

## Upgrade

Re-run the install with a new `--version` (same values file):

```bash theme={null}
helm upgrade --install tmo-ui \
  oci://artifacts.tensormesh.ai/tensormesh-production/charts/tensormesh-operator-ui \
  --version 1.0.1 -n tensormesh-platform -f ui-values.yaml
```

Roll back if needed:

```bash theme={null}
helm history tmo-ui -n tensormesh-platform
helm rollback tmo-ui <revision> -n tensormesh-platform
```

***

## Uninstall

```bash theme={null}
helm uninstall tmo-ui -n tensormesh-platform
```

The UI keeps no cluster state, so nothing is left behind.

***

## Next Steps

> **[Configuration](/v1.0.1/ui/configuration)**
>
> Connect metric history, GPU telemetry, and multiple clusters.

> **[Monitoring Your Fleet](/v1.0.1/ui/monitoring-your-fleet)**
>
> Triage what needs attention, drill into nodes and GPUs, and track cache and
> performance trends.


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.