> For the complete documentation index, see [llms.txt](https://run-ai-docs.nvidia.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://run-ai-docs.nvidia.com/self-hosted/2.24/infrastructure-setup/advanced-setup/service-mesh.md).

# Service Mesh

NVIDIA Run:ai supports service mesh implementations. When a service mesh is deployed with sidecar injection, specific configurations must be applied to ensure compatibility with NVIDIA Run:ai. This document outlines the required changes for the NVIDIA Run:ai control plane and cluster.

## Control Plane Configuration

{% hint style="info" %}
**Note**

This section applies to **self-hosted only**.
{% endhint %}

By default, NVIDIA Run:ai prevents Istio from injecting sidecar containers into system jobs in the control plane. For other service mesh solutions, users must manually add annotations during installation.

To disable sidecar injection in the NVIDIA Run:ai control plane, modify the Helm values file by adding the required pod labels to the following components. See [Advanced control plane configurations](/self-hosted/2.24/infrastructure-setup/advanced-setup/control-plane-config.md) for more details.

Example for [Open Service Mesh](https://release-v0-11.docs.openservicemesh.io/docs/guides/app_onboarding/sidecar_injection/#explicitly-disabling-automatic-sidecar-injection-on-pods):

```yaml
authorizationMigrator:
  podLabels:
    openservicemesh.io/sidecar-injection: disabled
clusterMigrator:
  podLabels:
    openservicemesh.io/sidecar-injection: disabled
identityProviderReconciler:
  podLabels:
    openservicemesh.io/sidecar-injection: disabled
keepPVC:
  podLabels:
    openservicemesh.io/sidecar-injection: disabled
orgUnitsMigrator:
  podLabels:
    openservicemesh.io/sidecar-injection: disabled
```

## Cluster Configuration

### Installation Phase

Sidecar containers injected by some service mesh solutions can prevent NVIDIA Run:ai installation hooks from completing. To avoid this, modify the Helm installation command to include the required labels or annotations:

```bash
helm upgrade -i ... 
--set global.additionalJobLabels.A=B --set global.additionalJobAnnotations.A=B
```

Example for [Istio Service Mesh](https://istio.io/latest/docs/setup/additional-setup/sidecar-injection/#controlling-the-injection-policy):

```bash
helm upgrade -i ... 
--set-json global.additionalJobLabels='{"sidecar.istio.io/inject":false}'
```

### Workloads

To prevent sidecar injection in workloads created at runtime (such as training workloads), update the `runaiconfig` resource. See [Advanced cluster configurations](/self-hosted/2.24/infrastructure-setup/advanced-setup/cluster-config.md) for more details:

```yaml
spec:
  workload-controller:
    additionalPodLabels:
      sidecar.istio.io/inject: false
```


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://run-ai-docs.nvidia.com/self-hosted/2.24/infrastructure-setup/advanced-setup/service-mesh.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.