A healthcare technology company is designing a secure cloud-native application on Azure to process patient data. The application requires two primary workloads:
* A front-end REST API that handles user requests, runs continuously, and scales dynamically based on incoming HTTP request volume.
* A background processing component that executes complex medical image analysis tasks. Each analysis task takes between 15 to 45 minutes to complete, must run in its own isolated container environment, and must scale down to zero when no tasks are in the queue.
You need to recommend a compute solution for the application. The design must minimize administrative and operational overhead.
Which two compute options should you recommend?
- Azure Container Apps to host the front-end REST APICevap
- Azure Container Apps jobs to host the background medical image analysis tasksCevap
- CAzure Kubernetes Service (AKS) to host both the front-end REST API and background tasks
- DAzure Functions on a Consumption plan to host the background medical image analysis tasks
Cevap
Azure Container Apps to host the front-end REST API, and Azure Container Apps jobs to host the background medical image analysis tasks
The correct recommendation uses Azure Container Apps for the front-end REST API and Azure Container Apps jobs for the background medical image analysis. Azure Container Apps handles continuous HTTP-triggered workloads with automatic scaling and zero cluster management. Azure Container Apps jobs are designed for run-to-completion, event-triggered execution (such as processing from a queue) and support long-running processes up to multiple hours, which easily accommodates the 15 to 45-minute medical image analysis tasks while scaling down to zero when idle and minimizing management overhead.
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Azure Container Apps and Jobs vs. AKS and Serverless Functions