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

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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.

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Install

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).

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Verify

kubectl get pods -n tracebloc
Pods Running, your workspace Online on the clients page.

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Environment-specific config

Use Azure Files for shared storage: 
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.

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Production notes

  • Use GPU node pools for training workloads; size requests/limits per job.
  • Day-2 upgrades and rollbacks: see Operations.