Introduction
Power Platform solutions handle business logic, data, and user experience well. When a solution needs long-running work, scheduled processing, event-driven integration, or secret-free access to another service, Azure Functions provides a backend option.
Meet Contoso's equipment-provisioning challenge
Contoso, Ltd. runs a custom Dataverse solution that tracks equipment requests across four tables: employee, device, request, and allowance. An employee submits a request for replacement equipment, and the solution checks allowance and eligibility. An external device-availability service outside Dataverse then reports whether stock is available, but that check can take from a few seconds to several minutes. A coordinator tracks each request through approval and fulfillment.
This scenario exposes common integration limits. Dataverse should not wait on a slow external check while a Power Automate flow or Dataverse plug-in caller stays blocked. The solution also needs a way to process nightly reconciliation on a schedule and react when request data changes without relying on polling.
What this module focuses on
In this module, you examine patterns that help Azure Functions support the Contoso scenario. You look at ways to start long-running work without keeping the caller waiting, run backend processing on a timer, and respond to events from Dataverse-connected components.
You also examine how a function accesses Dataverse by using a managed identity together with a Dataverse application user, instead of storing a client secret. Although the examples center on equipment provisioning, the same patterns apply to many Power Platform solutions that combine Dataverse with external services.
By the end of this module, you're able to design Azure Functions that handle long-running work, scheduled and event-driven processing, and secure Dataverse access without stored secrets.