Which approach best improves performance in an OmniStudio solution?

Which approach best improves performance in an OmniStudio solution?

• A. Increase the number of API calls to fetch data more often.
• B. Reuse DataRaptor and Integration Procedure results to reduce repeated calls.
• C. Disable caching completely to ensure fresh data.
• D. Run all processing on the client side with no server involvement.

Answer: (B)

Optimizing performance comes from cutting unnecessary work and the number of round trips you make. Reusing the outputs from DataRaptor and Integration Procedures means you don’t have to redo expensive data fetches, transformations, or orchestrations for every request. By reusing those results, you reduce API calls, lower latency, and decrease load on your back-end systems, which translates to faster, more scalable solutions. This leverages the server-side processing path that OmniStudio relies on, keeping data consistent and fresh handling dependent on how you manage the reuse window and invalidation. In contrast, increasing API calls increases network latency and can hit limits; disabling caching eliminates a powerful performance buffer and forces repeated work; running all processing on the client side removes server-side orchestration, which not only can be slower due to client resources but also raises security and data-freshness concerns.

Optimizing performance comes from cutting unnecessary work and the number of round trips you make. Reusing the outputs from DataRaptor and Integration Procedures means you don’t have to redo expensive data fetches, transformations, or orchestrations for every request. By reusing those results, you reduce API calls, lower latency, and decrease load on your back-end systems, which translates to faster, more scalable solutions. This leverages the server-side processing path that OmniStudio relies on, keeping data consistent and fresh handling dependent on how you manage the reuse window and invalidation.

In contrast, increasing API calls increases network latency and can hit limits; disabling caching eliminates a powerful performance buffer and forces repeated work; running all processing on the client side removes server-side orchestration, which not only can be slower due to client resources but also raises security and data-freshness concerns.