> ## 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 with Helm
> Install the Tensormesh Operator from the official Helm chart.
Helm is the primary install path for the Tensormesh Operator. A single `helm install`
command deploys the operator, registers its CRDs (`LMCacheEngine`, `LMCacheCoordinator`,
`CacheBlendEngine`), and by default creates an lmcache engine CR that the operator reconciles into
a DaemonSet on your GPU nodes, plus a fleet coordinator the engines register with.
## Prerequisites
* Helm `3.8` or newer (`helm version`)
* Cluster access with permission to create cluster-scoped resources
* A reachable Kubernetes 1.28+ cluster — see [Getting Started](/installation/getting-started)
* [cert-manager](https://cert-manager.io/docs/installation/) — the chart enables the
mutating webhook by default and cert-manager issues its serving certificate:
```bash theme={null}
kubectl apply -f https://github.com/cert-manager/cert-manager/releases/latest/download/cert-manager.yaml
kubectl -n cert-manager wait --for=condition=Available deploy --all --timeout=180s
```
* **Access token from the Tensormesh team**
The chart is distributed through a private registry. To install it, request an access
token from [https://www.tensormesh.ai/contact](https://www.tensormesh.ai/contact). You'll use it to authenticate before installing.
## Quick Install
Authenticate to the registry with the token Tensormesh provided, write your
configuration into `my-values.yaml`, and install:
```yaml my-values.yaml theme={null}
engine:
enabled: true
spec:
privileged: true # required for GPU visibility in some cluster
l1:
sizeGB: 200 # per-node L1 cache size
image:
repository: lmcache/vllm-openai
tag: v0.5.3 # pin the tag the Compatibility Matrix pairs with your chart
pullPolicy: IfNotPresent
coordinator:
spec:
image:
repository: lmcache/vllm-openai
tag: v0.5.3 # Same image as engine
pullPolicy: IfNotPresent
```
```bash theme={null}
# One-time: log in with the token Tensormesh gave you. When authenticating with a token,
# the username is not validated — any non-empty value works (we use "tensormesh" here).
echo '' | helm registry login ghcr.io -u tensormesh --password-stdin
helm install tensormesh-operator \
oci://ghcr.io/tensormesh-production/charts/tensormesh-operator \
--version 0.5.3 \
--namespace tensormesh-operator \
--create-namespace \
-f my-values.yaml \
--wait
```
**If install fails, jump to [Troubleshooting](/installation/troubleshooting).**
## Verify
```bash theme={null}
helm list -n tensormesh-operator
```
Example:
```text theme={null}
NAME NAMESPACE REVISION UPDATED STATUS CHART APP VERSION
tensormesh-operator tensormesh-operator 1 2026-08-12 02:05:00 UTC deployed tensormesh-operator-0.5.2 v0.5.2
```
`STATUS` should be `deployed`.
```bash theme={null}
kubectl get pods -n tensormesh-operator
```
Example:
```text theme={null}
NAME READY STATUS RESTARTS AGE
tensormesh-operator-5f47f76bd6-bzmqf 1/1 Running 0 2m
tensormesh-operator-coordinator-7c6446f7c8-zc7g7 1/1 Running 0 2m
```
```bash theme={null}
kubectl get crd | grep lmcache.ai
```
Example:
```text theme={null}
cacheblendengines.lmcache.lmcache.ai 2026-08-12T02:04:10Z
lmcachecoordinators.lmcache.lmcache.ai 2026-08-12T02:04:10Z
lmcacheengines.lmcache.lmcache.ai 2026-08-12T02:04:10Z
```
The chart ships all three CRDs (`crds.enabled=true`).
```bash theme={null}
kubectl get lmcacheengines -n tensormesh-operator
```
Example:
```text theme={null}
NAME PHASE READY DESIRED AGE
tensormesh-operator-default-engine Running 1 1 2m
```
```bash theme={null}
# select by the engine CR's name (instance label) — the component label
# (cache-engine) also matches CacheBlend engine pods when those are enabled
kubectl get pods -n tensormesh-operator -o wide \
-l app.kubernetes.io/instance=tensormesh-operator-default-engine
```
Example:
```text theme={null}
NAME READY STATUS RESTARTS AGE IP NODE
tensormesh-operator-default-engine-gfj2k 1/1 Running 0 2m 10.129.6.79 worker-gpu-a100-1
```
Expect one pod per GPU node. On a cluster with no GPU nodes this list is empty — which
is correct, not a failure.
```bash theme={null}
helm test tensormesh-operator -n tensormesh-operator
```
Example:
```text theme={null}
NAME: tensormesh-operator
LAST DEPLOYED: Sat May 24 02:05:00 2026
NAMESPACE: tensormesh-operator
STATUS: deployed
TEST SUITE: tensormesh-operator-test-basic
Last Started: 2026-05-24 02:08:00 +0000 UTC
Last Completed: 2026-05-24 02:08:20 +0000 UTC
Phase: Succeeded
```
## Upgrade
```bash theme={null}
helm upgrade tensormesh-operator \
oci://ghcr.io/tensormesh-production/charts/tensormesh-operator \
--version 0.5.3 -n tensormesh-operator \
-f my-values.yaml
```
Roll back if needed:
```bash theme={null}
helm history tensormesh-operator -n tensormesh-operator
helm rollback tensormesh-operator -n tensormesh-operator
```
## Uninstall
```bash theme={null}
helm uninstall tensormesh-operator -n tensormesh-operator
```
A pre-delete hook removes the chart-managed CRs (`LMCacheEngine`, `LMCacheCoordinator`,
and `CacheBlendEngine` if enabled) first, so their finalizers run cleanly before the
operator Deployment is torn down.
**The CRDs survive `helm uninstall`** — same convention cert-manager and
kube-prometheus-stack use. To remove them (and cascade-delete any remaining CRs):
```bash theme={null}
kubectl delete crd lmcacheengines.lmcache.lmcache.ai \
lmcachecoordinators.lmcache.lmcache.ai \
cacheblendengines.lmcache.lmcache.ai
```
## Helm Values
| Key | Default | What it creates |
| ----------------------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `crds.enabled` | `true` | The three CRD schemas |
| `operator.enabled` | `true` | The controller-manager Deployment |
| `engine.enabled` | `true` | An `LMCacheEngine` CR, which the operator reconciles into a DaemonSet (one cache server per GPU node) |
| `coordinator.enabled` | `true` | An `LMCacheCoordinator` CR — one fleet-wide Deployment the engines register with |
| `webhook.enabled` | `true` | The **CacheBlend** pod-mutating webhook. **Requires cert-manager**; rendering fails fast without it. The chart does not register the LMCache connection webhook — wire those pods [manually](/installation/existing-deployment) |
| `cacheBlend.enabled` | `false` | A `CacheBlendEngine` CR — see [CacheBlend](/configuration/cacheblend). Requires `webhook.enabled=true` |
| `observability.enabled` | `false` | An OpenTelemetry Collector CR. Requires the OpenTelemetry Operator already installed |
| `openshift.enabled` | `false` | The privileged SCC binding the engine's `hostIPC` needs |
| `tests.enabled` | `true` | The `helm test` smoke-test pods |
### See every value
The table above is the common subset. For the full list with defaults:
```bash theme={null}
helm show values \
oci://ghcr.io/tensormesh-production/charts/tensormesh-operator --version 0.5.3
```
See the [Configuration reference](/reference/configuration) for per-section detail
and example overlays.
## Next steps
Install, deploy vLLM against the engine, see the cache hit, run the benchmark.
Patch the workload you already run to consume the engine connection ConfigMap.
Engine `Pending`, `ImagePullBackOff`, hung uninstalls, and more.