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Troubleshooting Vertex AI Workbench

This page describes troubleshooting steps that you might find helpful if you run into problems when you use Vertex AI Workbench.

See also Troubleshooting Vertex AI for help using other components of Vertex AI.

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Helpful procedures

This section describes procedures that you might find helpful.

Use SSH to connect to your user-managed notebooks instance

Use ssh to connect to your instance by typing the following command in either Cloud Shell or any environment where the Google Cloud CLI is installed.

gcloud compute ssh --project PROJECT_ID \
  --zone ZONE \
  INSTANCE_NAME -- -L 8080:localhost:8080

Replace the following:

PROJECT_ID: Your project ID
ZONE: The Google Cloud zone where your instance is located
INSTANCE_NAME: The name of your instance

Re-register with the Inverting Proxy server

To re-register the user-managed notebooks instance with the internal Inverting Proxy server, you can stop and start the VM from the User-managed notebooks page or you can use ssh to connect to your user-managed notebooks instance and enter:

cd /opt/deeplearning/bin
sudo ./attempt-register-vm-on-proxy.sh

Verify the Docker service status

To verify the Docker service status you can use ssh to connect to your user-managed notebooks instance and enter:

sudo service docker status

Verify that the Inverting Proxy agent is running

To verify if the notebook Inverting Proxy agent is running, use ssh to connect to your user-managed notebooks instance and enter:

# Confirm Inverting Proxy agent Docker container is running (proxy-agent)
sudo docker ps

# Verify State.Status is running and State.Running is true.
sudo docker inspect proxy-agent

# Grab logs
sudo docker logs proxy-agent

Verify the Jupyter service status and collect logs

To verify the Jupyter service status you can use ssh to connect to your user-managed notebooks instance and enter:

sudo service jupyter status

To collect Jupyter service logs:

sudo journalctl -u jupyter.service --no-pager

Verify that the Jupyter internal API is active

To verify that the Jupyter internal API is active you can use ssh to connect to your user-managed notebooks instance and enter:

curl http://127.0.0.1:8080/api/kernelspecs

Restart the Docker service

To restart the Docker service, you can stop and start the VM from the User-managed notebooks page or you can use ssh to connect to your user-managed notebooks instance and enter:

sudo service docker restart

Restart the Inverting Proxy agent

To restart the Inverting Proxy agent, you can stop and start the VM from the User-managed notebooks page or you can use ssh to connect to your user-managed notebooks instance and enter:

sudo docker restart proxy-agent

Restart the Jupyter service

To restart the Jupyter service, you can stop and start the VM from the User-managed notebooks page or you can use ssh to connect to your user-managed notebooks instance and enter:

sudo service jupyter restart

Make a copy of the user data on an instance

To store a copy of an instance's user data in Cloud Storage, complete the following steps.

Create a Cloud Storage bucket (optional)

In the same project where your instance is located, create a Cloud Storage bucket where you can store your user data. If you already have a Cloud Storage bucket, skip this step.

Create a Cloud Storage bucket:
```
gcloud storage buckets create gs://BUCKET_NAME
```
Replace BUCKET_NAME with a bucket name that meets the bucket naming requirements.

Copy your user data

In your instance's JupyterLab interface, select File > New > Terminal to open a terminal window. For user-managed notebooks instances, you can instead connect to your instance's terminal by using SSH.
Use the gsutil tool to copy your user data to a Cloud Storage bucket. The following example command copies all of the files from your instance's /home/jupyter/ directory to a directory in a Cloud Storage bucket.
```
gsutil cp -R /home/jupyter/* gs://BUCKET_NAMEPATH
```
Replace the following:
- BUCKET_NAME: the name of your Cloud Storage bucket
- PATH: the path to the directory where you want to copy your files, for example: /copy/jupyter/