The correct architecture uses an Azure Storage queue as an asynchronous buffer between the HTTP ingestion path and the computationally expensive image-processing workload. The HTTP-triggered function should accept the upload, enqueue a work message, and return promptly rather than waiting for image processing to finish. Microsoft specifically recommends asynchronous patterns for long-running HTTP operations because an HTTP-triggered Azure Function can encounter the Azure Load Balancer response timeout even though the underlying function continues executing.
A queue-triggered function then performs image processing independently. Azure Functions applies target- based scaling to Azure Queue Storage triggers based on queued workload, allowing worker capacity to expand as the backlog increases rather than being directly tied to HTTP arrival processing.
For reliability, Azure Queue-triggered Functions provide retry behavior. The visibilityTimeout setting controls the delay before a failed message becomes available for another attempt, while maxDequeueCount controls how many processing attempts occur before the message is transferred to the < queue-name > - poison queue. The default maximum is five attempts.
C defeats the asynchronous requirement. D can be useful for tracking upload state, but it does not itself provide workload decoupling, retry handling, or queue-driven scaling.
Study Guide references: Azure Functions # Queue Storage triggers and bindings; event-driven scaling; retry
/poison queue behavior; asynchronous HTTP processing.