Non-Employee : NELM source vs Azure AD filtered source

Hi Experts,

We have an Azure AD source that contains employee and vendor (B2B data).

The client also wants to use IDN for non-employee lifecycle management in future releases.

What should be the preferred approach in this scenario - creating an AAD source which filters the vendor’s records and using it for identity profile, UAR and provisioning activities or using a NELM source.

From my understanding, using AAD with a filter would be a simpler approach and should be able to solve the UAR and provisioning requirements; manually creating the NELM source feed and maintaining it don’t seem to be ideal, along with the limitation on 10 additional schema attributes and 20k users per source. I went through NELM documentation but the recommendation is not clear in which scenarios it can be used and what additional benefits it can provide over a filtered direct connector. Please advise here.

@colin_mckibben

Regards,
Aditya

Before you post in our general IdentityNow (IDN) category, please review other subcategories for a better fit. If you’re posting here regarding UI configuration or Out of the Box Connectors, please visit our Compass Community for assistance. The SailPoint Developer Forum focuses on helping the developer community extend the capabilities of IDN beyond what is provided in the user interface.

Hi Aditya

The developer forum focuses on helping the developer community extend the capabilities of IDN beyond what is provided out of the box in the user interface. This typically involves the use of APIs, event triggers, and rules. The Compass community focuses on assisting admins with the configuration of their tenants within the IDN UI as well as with out-of-the-box connectors. To help us keep our conversations focused and to provide community members like you with the best possible experience, can you please ask your question in Compass? I think you will find knowledgeable experts in Compass that can assist you with your question. Thank you for your understanding.

1 Like