Azure Content Understanding and Azure OpenAI Service are regional services. A production document-processing workflow often cannot treat a regional endpoint, its model deployments, or its analyzer definitions as a single point of failure. In this post, we discuss a highly available solution built across multiple regions to handle regional failures. Architecture Figure 1. Implemented regional stacks and cross-region flows. The diagram shows two distinct planes: solid lines represent synchronous request traffic, while dashed lines represent asynchronous analyzer reconciliation. This separation addresses two related resilience challenges: routing requests to a healthy Content Understanding backend and keeping analyzer configurations consistent across regions. API Management selects a local-first backend synchronously within each available gateway, while two queue-driven Azure Functions synchronize analyzers asynchronously. Read more

Many organisations store their data in a centralised data lake on Azure Storage accounts. In this post we will look at a solution to scale the secure network access between the centralised data lake storage account and Azure Databricks workspaces VNets. The recommended approach to achieve a scalable and secure network access to the data lake storage is to use Private Endpoints for the storage accounts. Read more