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| Google Cloud Platform |
:::important This documentation page applies to deploying your own open source ClearML Server. It does not apply to ClearML Hosted Service users. :::
Deploy ClearML Server on the Google Cloud Platform (GCP) using one of the pre-built GCP Custom Images. ClearML provides custom images for each released version of ClearML Server. For a list of the pre-built custom images, see ClearML Server GCP Custom Image.
After deploying ClearML Server, configure the ClearML Python Package for it, see Configuring ClearML for ClearML Server.
For information about updgrading **ClearML server on GCP, see here.
:::important If ClearML Server is being reinstalled, we recommend clearing browser cookies for ClearML Server. For example, for Firefox, go to Developer Tools > Storage > Cookies, and for Chrome, go to Developer Tools > Application > Cookies, and delete all cookies under the ClearML Server URL. :::
Default ClearML Server service ports
After deploying ClearML Server, the services expose the following node ports:
- Web server on
8080 - API server on
8008 - File Server on
8081
Default ClearML Server storage paths
The persistent storage configuration:
- MongoDB:
/opt/clearml/data/mongo/ - Elasticsearch:
/opt/clearml/data/elastic_7/ - File Server:
/mnt/fileserver/
Importing the Custom Image to your GCP account
Before launching an instance using a ClearML Server GCP Custom Image, import the image to the custom images list.
:::note No upload of the image file is required. We provide links to image files stored in Google Storage. :::
To import the image to your custom images list:
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In the Cloud Console, go to the Images page.
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At the top of the page, click Create image.
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In Name, specify a unique name for the image.
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Optionally, specify an image family for the new image, or configure specific encryption settings for the image.
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In the Source menu, select Cloud Storage file.
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Enter the ClearML Server image bucket path (see ClearML Server GCP Custom Image), for example:
allegro-files/clearml-server/clearml-server.tar.gz. -
Click Create to import the image. The process can take several minutes depending on the size of the boot disk image.
For more information see Import the image to your custom images list in the Compute Engine Documentation.
Launching
:::warning By default, ClearML Server launches with unrestricted access. To restrict ClearML Server access, follow the instructions in the Security page. :::
To launch ClearML Server using a GCP Custom Image, see the Manually importing virtual disks in the "Google Cloud Storage" documentation, Compute Engine documentation. For more information on Custom Images, see Custom Images in the "Compute Engine documentation".
The minimum requirements for ClearML Server are:
- 2 vCPUs
- 7.5GB RAM
Restarting
To restart ClearML Server Docker deployment:
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Stop and then restart the Docker containers by executing the following commands:
docker-compose -f /opt/clearml/docker-compose.yml down docker-compose -f /opt/clearml/docker-compose.yml up -d
Backing up and restoring data and configuration
The commands in this section are an example of how to back up and restore data and configuration .
If data and configuration folders are in /opt/clearml, then archive all data into ~/clearml_backup_data.tgz, and
configuration into ~/clearml_backup_config.tgz:
sudo tar czvf ~/clearml_backup_data.tgz -C /opt/clearml/data .
sudo tar czvf ~/clearml_backup_config.tgz -C /opt/clearml/config .
If the data and the configuration need to be restored:
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Verify you have the backup files.
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Replace any existing data with the backup data:
sudo rm -fR /opt/clearml/data/* /opt/clearml/config/* sudo tar -xzf ~/clearml_backup_data.tgz -C /opt/clearml/data sudo tar -xzf ~/clearml_backup_config.tgz -C /opt/clearml/config -
Grant access to the data:
sudo chown -R 1000:1000 /opt/clearml
ClearML Server GCP Custom Image
The following section contains a list of Custom Image URLs (exported in different formats) for each released ClearML Server version.