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

# Azure AKS

> Deploy a tracebloc workspace on Azure Kubernetes Service.

**When to pick it** — You're on Azure and want managed Kubernetes with autoscaling and GPU node pools.

## Prerequisites

* An AKS cluster, and `kubectl` pointed at it (`az aks get-credentials …`).
* **Helm 3.x**.
* Your **Client ID** and password from the [clients page](https://ai.tracebloc.io/clients).

## Install

```bash theme={null}
helm repo add tracebloc https://tracebloc.github.io/client
helm repo update
helm show values tracebloc/client > values.yaml   # edit per below
helm upgrade --install tracebloc tracebloc/client \
  -n tracebloc --create-namespace -f values.yaml
```

Set your credentials in `values.yaml` (see [Configuration → Authentication](/environment-setup/configuration#authentication)).

## Verify

```bash theme={null}
kubectl get pods -n tracebloc
```

Pods `Running`, your workspace **Online** on the clients page.

## Environment-specific config

Use Azure Files for shared storage:

```yaml theme={null}
storageClass:
  create: true
  provisioner: file.csi.azure.com
  parameters:
    skuName: Standard_LRS
  mountOptions: [dir_mode=0750, file_mode=0640, uid=999, gid=999, mfsymlinks, cache=strict, actimeo=30]
clusterScope: true
```

* **NetworkPolicy:** create the AKS cluster with `--network-policy azure` (Azure NPM) or Calico — otherwise the training-pod egress lockdown won't enforce.
* `metrics-server` is bundled on AKS.

## Production notes

* Use GPU node pools for training workloads; size requests/limits per job.
* Day-2 upgrades and rollbacks: see [Operations](/environment-setup/operations).