Dataset Connections

AnalyticOps provides support for the self-service definition of dataset connections. In dataset connections, you can include your own credentials, thus making it easier for you to define project-level connections and credentials that can be used in model training and evaluation processes.

You can define dataset connections on a project level. These dataset connections are selected while defining dataset templates and are editable while performing model training, evaluation and deployment. AnalyticOps allows you to define Vantage, S3, Hadoop and a custom type of connections, and provides support of conventional username/password, Kerberos, AWS Secrets and Kubernetes as credentials.

The Connections Setting module organizes and facilitates creation and management of dataset connections for the selected project. This chapter covers the following details:

• Add a Connection

• View List of Connections

• View Connection Details

• Archive a Connection

Add a Connection

To add a connection in a selected project:

1. Click the Settings from the Navigation bar of a selected project.
   The list of connections for the project displays in the Work area and the Settings option highlights in the Navigation bar.

   

2. Click the Add Connection button.
   The Add Connection dialog displays.

   

3. In the Connection Details step, set the connection properties:

   Property	Description
   Type	Lets you select the type of connection as Vantage, S3, Hadoop or Custom.
   Name	Specifies the name of the connection.
   Description	Specifies the description of the connection.

   (i) For Vantage type, set the properties:

   

   Property	Description
   Host Name	Specifies the host name you want to connect.
   Login Mechanism	Specifies the authentication mechanism from the given options: TDNEGO, TD2, LDAP, KRBS

   (ii) For Hadoop type, set the properties:

   

   Property	Description
   Connection Custom Properties	Lets you define the custom properties as key/value pair.

   (iii) For Custom type, set the properties:

   

   Property	Description
   Connection Custom Properties	Lets you define the custom properties as key/value pair.

   Note: For S3 connection type, no detailed connection properties are required to specify.

4. In the Credential Template step, set the credentials template:

   Property	Description
   Type	Lets you select the credentials type as Default, Kerberos, Kubernetes.

   (i) For Default type, set the properties:

   

   Property	Description
   Username/Password	Specifies the username and password to connect to the host.

   (ii) For Kerberos type, set the properties:

   

   Property	Description
   Principal	Specifies the Kerberos service principal name for user authentication.
   Keytab Path	Specifies the Kerberos keytab file name for user authentication.

   (iii) For Kubernetes type, set the properties:

   

   Property	Description
   SecretsRef	Specifies the SecretsRef for user authentication.

5. Click Create.
   The connection adds to the list of connections.

   

View List of Connections

To view connections added in a project:

1. Click the Settings from the Navigation bar of a selected project.
   The list of connections for the project displays in the Work area.

   

   The list of Connections displays the following properties.

   Property	Description
   Name	Specifies the connection name.
   Description	Specifies the connection description.
   Type	Shows the connection type as Vantage, S3, Hadoop, or Custom.
   Host	Specifies the host name.
   Credentials Template	Displays the defined credentials template as Default, Kerberos, or Kubernetes.
   Creation Date	Displays the creation date of the connection.
   View Details	Allows you to view the details of the connection. For details, see View Connection Details.

View Connection Details

You can view the details of a connection including the defined parameters as environment variables and their sample usage in Python/R.

To view details of a connection:

1. In the Connections list, click the View Details icon for a connection.
   

   

   The Connection Details dialog displays.

   

   The Environment Variables section displays the defined parameters as Key/Value pair. The usage of these environment variables is shown in the Sample Usage in the Python/R section.

Archive a Connection

The archiving feature allows you to hide a connection from the list to better organize your connections list. You can view the archived connections and unarchive them if required.

Note: The Archiving feature is provided with multiple modules including projects, models, model versions, dataset templates, datasets, and connections.

To archive a connection:

1. Select a connection in the list.
   The Actions button enables.

   Comments: Images will be updated after implementation of the feature.

2. Click the Actions button.
   The Actions menu displays.

   Comments: Images will be updated after implementation of the feature.

3. Click Archive Connection.
   The connection archives and hides from the current list of connections. A confirmation message displays on the top.

   Comments: Images will be updated after implementation of the feature.

4. To view an Archived connection, click the Show Archived option on the top.
   The archived connection displays in the list along with an Archived label.

   Comments: Images will be updated after implementation of the feature.

To Un-archive a connection:

1. Select an archived connection in the list.
   The Actions button enables.

   Comments: Images will be updated after implementation of the feature.

2. Click the Actions button.
   The Actions menu displays.

   Comments: Images will be updated after implementation of the feature.

3. Click Un-Archive Connection.
   The connection un-archives and the label Archived removes. A confirmation message displays on the top.

   Comments: Images will be updated after implementation of the feature.