AZ-204 Develop Azure compute solutions Practice Question
You are building a serverless image-processing solution using Azure Functions. The function must automatically run whenever a new image is uploaded to a blob container and must scale out to handle high upload volumes. Which trigger and hosting plan should you use?
⚠ Common exam trap
Many candidates confuse the Blob trigger with other triggers (like Timer or Queue) that can indirectly process blobs, but only the Blob trigger directly and automatically responds to blob creation events without additional infrastructure.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Blob trigger with Consumption plan
The Blob trigger is designed to automatically execute a function when a blob is created or updated in Azure Blob Storage, making it the correct choice for an image-processing solution that must run on new uploads. The Consumption plan provides automatic scaling to handle high upload volumes by allocating resources on demand, which aligns with the serverless, event-driven requirement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Timer trigger with Consumption plan
Why it's wrong here
A Timer trigger is designed to execute a function on a recurring, predefined schedule, such as every hour or once a day. It operates independently of external events like new blob uploads. Therefore, it cannot react immediately or automatically when an image is added to storage, making it unsuitable for an event-driven image processing solution that requires real-time or near real-time responses to new data.
- ✓
Blob trigger with Consumption plan
Why this is correct
The Blob trigger is specifically designed to activate an Azure Function whenever a new or updated blob is detected in a specified Azure Storage container. This directly addresses the requirement for processing images upon upload. Coupled with the Consumption plan, the function automatically scales out to handle fluctuating volumes of image uploads, executing only when triggered and incurring costs solely based on execution time and memory usage, making it highly efficient and cost-effective for serverless workloads.
- ✗
HTTP trigger with Premium plan
Why it's wrong here
An HTTP trigger requires an explicit incoming HTTP request to invoke the function, meaning it would not automatically fire when a blob is uploaded without an intermediary service making that request. While the Premium plan offers enhanced performance and features like pre-warmed instances, it is primarily chosen for scenarios requiring minimal cold start times or VNet integration, not as a direct solution for automatically reacting to storage events or for scaling in this specific event-driven context.
- ✗
Queue trigger with App Service plan
Why it's wrong here
A Queue trigger processes messages from an Azure Storage Queue, not directly from blob creation events. While a queue could be used in an architecture where another service enqueues messages upon blob upload, the trigger itself does not react to the blob directly. Furthermore, hosting an Azure Function on an App Service plan typically involves pre-provisioned resources, requiring manual scaling configuration or "Always On" settings, which contradicts the serverless, auto-scaling, and pay-per-execution benefits ideal for an event-driven image processing solution.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
Go deeper
Related to this question
Learn chapter
Azure Functions Development
Key term
Durable Functions
Durable Functions is an extension of Azure Functions that lets you write stateful workflows in code, managing complex sequences of tasks, retries, and delays automatically.
Key term
Azure Functions Bindings
Azure Functions Bindings are declarative connections that link your serverless function code to Azure services or external resources, handling input and output data automatically without writing extra networking or authentication code.
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