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Chapter 4. Managing storage classes
OpenShift cluster administrators use storage classes to describe the different types of storage that is available in their cluster. These storage types can represent different quality-of-service levels, backup policies, or other custom policies set by cluster administrators.
4.1. Configuring storage class settings
As an OpenShift AI administrator, you can manage OpenShift cluster storage class settings for usage within OpenShift AI, including the display name, description, and whether users can use the storage class when creating or editing cluster storage. These settings do not impact the storage class within OpenShift.
Prerequisites
- You have logged in to OpenShift AI as a user with OpenShift AI administrator privileges.
Procedure
From the OpenShift AI dashboard, click Settings
Storage classes. The Storage classes page appears, displaying the storage classes for your cluster as defined in OpenShift.
- To enable or disable a storage class for users, on the row containing the storage class, click the toggle in the Enable column.
To edit a storage class, on the row containing the storage class, click the action menu (⋮) and then select Edit.
The Edit storage class details dialog opens.
- Optional: In the Display Name field, update the name for the storage class. This name is used only in OpenShift AI and does not impact the storage class within OpenShift.
- Optional: In the Description field, update the description for the storage class. This description is used only in OpenShift AI and does not impact the storage class within OpenShift.
- Click Save.
Verification
- If you enabled a storage class, the storage class is available for selection when a user adds cluster storage to a data science project or workbench.
- If you disabled a storage class, the storage class is not available for selection when a user adds cluster storage to a data science project or workbench.
- If you edited a storage class name, the updated storage class name is displayed when a user adds cluster storage to a data science project or workbench.
Additional resources
4.2. Configuring the default storage class for your cluster
As an OpenShift AI administrator, you can configure the default storage class for OpenShift AI to be different from the default storage class in OpenShift.
Prerequisites
- You have logged in to OpenShift AI as a user with OpenShift AI administrator privileges.
Procedure
From the OpenShift AI dashboard, click Settings
Storage classes. The Storage classes page appears, displaying the storage classes for your cluster as defined in OpenShift.
- If the storage class that you want to set as the default is not enabled, on the row containing the storage class, click the toggle in the Enable column.
- To set a storage class as the default for OpenShift AI, on the row containing the storage class, select Set as default.
Verification
- When a user adds cluster storage to a data science project or workbench, the default storage class that you configured is automatically selected.
Additional resources
4.3. Overview of object storage endpoints
To ensure correct configuration of object storage in OpenShift AI, you must format endpoints correctly for the different types of object storage supported. These instructions are for formatting endpoints for Amazon S3, MinIO, or other S3-compatible storage solutions, minimizing configuration errors and ensuring compatibility.
Properly formatted endpoints enable connectivity and reduce the risk of misconfigurations. Use the appropriate endpoint format for your object storage type. Improper formatting might cause connection errors or restrict access to storage resources.
4.3.1. MinIO (On-Cluster)
For on-cluster MinIO instances, use a local endpoint URL format. Ensure the following when configuring MinIO endpoints:
-
Prefix the endpoint with
http://orhttps://depending on your MinIO security setup. - Include the cluster IP or hostname, followed by the port number if specified.
-
Use a port number if your MinIO instance requires one (default is typically
9000).
Example:
http://minio-cluster.local:9000
Verify that the MinIO instance is accessible within the cluster by checking your cluster DNS settings and network configurations.
4.3.2. Amazon S3
When configuring endpoints for Amazon S3, use region-specific URLs. Amazon S3 endpoints generally follow this format:
-
Prefix the endpoint with
https://. -
Format as
<bucket-name>.s3.<region>.amazonaws.com, where<bucket-name>is the name of your S3 bucket, and<region>is the AWS region code (for example,us-west-1,eu-central-1).
Example:
https://my-bucket.s3.us-west-2.amazonaws.com
For improved security and compliance, ensure that your Amazon S3 bucket is in the correct region.
4.3.3. Other S3-Compatible Object Stores
For S3-compatible storage solutions other than Amazon S3, follow the specific endpoint format required by your provider. Generally, these endpoints include the following items:
-
The provider base URL, prefixed with
https://. - The bucket name and region parameters as specified by the provider.
- Review the documentation from your S3-compatible provider to confirm required endpoint formats.
-
Replace placeholder values like
<bucket-name>and<region>with your specific configuration details.
Incorrectly formatted endpoints for S3-compatible providers might lead to access denial. Always verify the format in your storage provider documentation to ensure compatibility.
4.3.4. Verification and Troubleshooting
After configuring endpoints, verify connectivity by performing a test upload or accessing the object storage directly through the OpenShift AI dashboard. For troubleshooting, check the following items:
- Network Accessibility: Confirm that the endpoint is reachable from your OpenShift AI cluster.
- Authentication: Ensure correct access credentials for each storage type.
- Endpoint Accuracy: Double-check the endpoint URL format for any typos or missing components.
Additional resources
- Amazon S3 Region and Endpoint Documentation: AWS S3 Documentation
