Configure the Arena client

Prerequisites

Ensure you have the following resources ready:

• An ACK cluster with GPU-accelerated nodes (managed or dedicated).

• Cluster nodes have internet access.

• Arena is installed via the cloud-native AI suite.

Step 1: Connect to the cluster

Connection method depends on your cluster type.

Run kubectl get nodes to verify your kubeconfig.

Step 2: Install the Arena client

Select the package for your OS and architecture.

# Download the Arena installation package.
wget https://aliacs-k8s-cn-hangzhou.oss-cn-hangzhou.aliyuncs.com/arena/arena-installer-0.12.0-linux-amd64.tar.gz

# Extract the package.
tar -zxvf arena-installer-0.12.0-linux-amd64.tar.gz

# Install Arena.
cd arena-installer-0.12.0-linux-amd64
bash install.sh --only-binary

# Download the Arena installation package.
wget https://aliacs-k8s-cn-hangzhou.oss-cn-hangzhou.aliyuncs.com/arena/arena-installer-0.12.0-linux-arm64.tar.gz

# Extract the package.
tar -zxvf arena-installer-0.12.0-linux-arm64.tar.gz

# Install Arena.
cd arena-installer-0.12.0-linux-arm64
bash install.sh --only-binary

# Download the Arena installation package.
wget https://aliacs-k8s-cn-hangzhou.oss-cn-hangzhou.aliyuncs.com/arena/arena-installer-0.12.0-darwin-amd64.tar.gz

# Extract the package.
tar -zxvf arena-installer-0.12.0-darwin-amd64.tar.gz

# Install Arena.
cd arena-installer-0.12.0-darwin-amd64
bash install.sh --only-binary

# Download the Arena installation package.
wget https://aliacs-k8s-cn-hangzhou.oss-cn-hangzhou.aliyuncs.com/arena/arena-installer-0.12.0-darwin-arm64.tar.gz

# Extract the package.
tar -zxvf arena-installer-0.12.0-darwin-arm64.tar.gz

# Install Arena.
cd arena-installer-0.12.0-darwin-arm64
bash install.sh --only-binary

Step 3: (Optional) Enable shell auto-completion

Press Tab to complete partially typed Arena commands.

sudo yum install bash-completion -y

sudo apt-get install bash-completion

brew install bash-completion@2

echo "source <(arena completion bash)" >> ~/.bashrc
chmod u+x ~/.bashrc

echo "source $(brew --prefix)/etc/profile.d/bash_completion.sh" >> ~/.bashrc

Step 4: Verify the installation

Confirm Arena is working.

1. Check available GPU resources in the cluster:

   arena top node

   Expected output:

   NAME                        IPADDRESS      ROLE    STATUS  GPU(Total)  GPU(Allocated)
   cn-huhehaote.192.168.X.XXX  192.168.0.117  <none>  ready   8           0
   cn-huhehaote.192.168.X.XXX  192.168.0.118  <none>  ready   8           0
   cn-huhehaote.192.168.X.XXX  192.168.0.119  <none>  ready   8           0
   cn-huhehaote.192.169.X.XXX  192.168.0.120  <none>  ready   8           0
   -----------------------------------------------------------------------------------------
   Allocated/Total GPUs In Cluster:
   0/32 (0%)

2. Submit a test training job:

   arena submit tf \
         --name=firstjob \
         --gpus=1 \
         --image=registry.cn-hangzhou.aliyuncs.com/tensorflow-samples/tf-mnist-standalone:gpu \
         "python /app/main.py"

   Expected output:

   configmap/firstjob-tfjob created
   configmap/firstjob-tfjob labeled
   tfjob.kubeflow.org/firstjob created
   INFO[0001] The Job firstjob has been submitted successfully
   INFO[0001] You can run `arena get firstjob --type tfjob` to check the job status

3. List all jobs:

   arena list

   Expected output:

   NAME      STATUS   TRAINER  AGE  NODE
   firstjob  RUNNING  TFJOB    5s   192.168.X.XXX

4. Check the job status:

   arena get firstjob

   Expected output:

   STATUS: SUCCEEDED
   NAMESPACE: default
   PRIORITY: N/A
   TRAINING DURATION: 52s
   NAME      STATUS     TRAINER  AGE  INSTANCE          NODE
   firstjob  SUCCEEDED  TFJOB    14m  firstjob-chief-0  192.168.X.XXX

5. View the job logs:

   arena logs --tail=10 firstjob

   Expected output:

   Accuracy at step 910: 0.9694
   Accuracy at step 920: 0.9687
   Accuracy at step 930: 0.9676
   Accuracy at step 940: 0.9678
   Accuracy at step 950: 0.9704
   Accuracy at step 960: 0.9692
   Accuracy at step 970: 0.9721
   Accuracy at step 980: 0.9696
   Accuracy at step 990: 0.9675
   Adding run metadata for 999

   The job completed successfully.

Related video

Watch how to install Arena and submit a Gang Scheduling job.

Next steps

• Submit a TensorFlow training job

• Submit a PyTorch training job