Create Datasets

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1.0 Introduction

A dataset contains information on how to securely retrieve remote data.

This includes the following:

  • A location, such as a URL to an external storage service.

  • Credentials such as username, password, auth-token, and so on, which are stored securely in a KMS (currently this is Fortanix-Data-Security-Managers).

NOTE

  • A Credential is a fully user-provided object, for example: this can be a JSON string that contains the query parameter of the S3 pre-signed URL and the decryption key.

  • Credentials can be rotated through updates to datasets; all approved enclaves are allowed to refresh and get the latest credentials.

You can leverage these objects to provide data to enclaves securely.

Fortanix CCM’s EDP and EnclaveOS products can retrieve datasets and their credentials when run in an approved workflow. For more information about workflows, refer to Workflows.

2.0 Create a Dataset

User's Guide: Create Datasets

Perform the following steps to create a dataset:

  1. In the CCM left navigation panel, click the Dataverse Datasets menu item, and then click + ADD DATASET to create a new dataset.

    Figure 1: Add dataset

  2. In the DATASET form, do the following:

    1. Name – the dataset name. For example: Dataset1.

    2. Description (optional) – the dataset description.

    3. Labels (optional)– attach one or more key-value labels to the dataset.

    4. Group – Select the required group name from the drop down menu to associate this dataset with that group.

    5. Location – the URL where the data can be accessed.

    6. Long Description (optional)– enter the content in GitHub-flavoured Markdown file format. You can also use the Fetch Long Description button to get the Markdown file content from an external URL. Ensure that Cross-origin resource sharing (CORS) is enabled on the external URL so that Fortanix CCM can access it. For more information, refer to the steps for AWS and Azure.

    7. Name: Enter a name for the dataset. For example, Demo Dataset.

    8. Description (Optional): Enter a short description of the dataset. 

    9. Labels (Optional): Add one or more key–value labels to the dataset.  

    10. Group: Select the required group name from the drop down menu to associate this dataset with that group.

    11. Location: Enter the URL where the data can be accessed.

    12. Long Description (Optional): Enter the dataset details in GitHub-flavored Markdown format.

      The following is the sample long description in Markdown format:

      - Strikethrough Text
      ~~It is Strikethrough test..~~
      
      - Blockquote Text
      > Test Blockquote.
      
      - Bold
      **A sample Description.**
      
      - Italic
      *It is Italics*
      
      - Bold and Italic
      ***Bold and Italics text***
      
      - Link
      This is [Website](https://www.fortanix.com/)?

      Or you can click FETCH LONG DESCRIPTION to import the Markdown file content from an external URL.

      Figure 2: Fetch long description

      Your title goes here

      Ensure that Cross-origin resource sharing (CORS) is enabled on the external URL so that Fortanix CCM can access it. For more information, refer to the steps for AWS and Azure.

    13. Credentials: Enter the credentials required to access the data.

    Figure 3: Create new dataset

  3. Click SAVE to create the dataset.  

The dataset is created successfully.

Figure 4: Dataset created

3.0 Update a Dataset

Perform the following steps to edit a dataset:

  1. From the dataset table, select the dataset that you want to update.

  2. In the dataset details view, click EDIT to modify the dataset configuration.

    Figure 5: Edit dataset

  3. Update the required fields, such as Name, Description, Location, Labels, and Credentials.

  4. Click SAVE after you edit the dataset. 

    NOTE

    You can also update a dataset by clicking the overflow menu for the dataset entry in the table and selecting EDIT DATASET from the drop down menu.

    Figure 6: Edit dataset

4.0 Delete a Dataset

Perform the following steps to delete a dataset:

  1. From the dataset table, select the dataset that you want to delete.

  2. In the dataset details view, click DELETE.

    Figure 7: Delete dataset

  3. In the confirmation dialog box, click DELETE to confirm the action.

    NOTE

    You can also delete a dataset by clicking the overflow menu for the dataset entry in the table and selecting DELETE DATASET from the drop down menu.

    Figure 8: Delete dataset

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As of August 2025