AZ-204 Develop Azure compute solutions Practice Question
You are building a solution that processes real-time telemetry from IoT devices. The telemetry data must be ingested, processed with minimal latency, and stored in Azure Blob Storage for long-term analytics. You need to choose the serverless compute service that is best suited for this scenario. What should you use?
⚠ Common exam trap
A common mix-up: candidates confuse Azure Logic Apps (which also has an Event Hubs connector) with Azure Functions, but Logic Apps are designed for orchestration and have higher latency, making them inappropriate for real-time, high-throughput telemetry processing.
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
✓
Azure Functions with Event Hubs trigger
Azure Functions with an Event Hubs trigger is the best choice because it provides a serverless, event-driven compute model that can process high-throughput telemetry data with minimal latency. The Event Hubs trigger scales automatically based on the number of partitions and events, ensuring real-time processing, and the output can directly write to Azure Blob Storage for long-term analytics.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Azure Functions with Event Hubs trigger
Why this is correct
This is the optimal choice for real-time telemetry processing due to its serverless nature and event-driven architecture. The Event Hubs trigger allows Azure Functions to automatically scale out to handle high-throughput, low-latency ingestion of millions of events per second, processing them efficiently on a consumption-based billing model without managing underlying infrastructure. This makes it highly cost-effective and responsive for dynamic workloads, perfectly aligning with real-time processing requirements.
- ✗
Azure Batch with Event Hubs input
Why it's wrong here
Azure Batch is designed for large-scale parallel batch processing of compute-intensive workloads, not for continuous, real-time stream processing. It excels at scheduling and managing a pool of virtual machines to execute discrete jobs on large datasets, typically after data has been collected and stored. Its architecture introduces inherent latency unsuitable for immediate telemetry analysis, as it's optimized for throughput over instantaneous response, making it inappropriate for real-time scenarios.
- ✗
Azure Logic Apps with Event Hubs connector
Why it's wrong here
While Logic Apps can connect to Event Hubs, they are primarily designed for workflow orchestration and integrating various services with a low-code approach. Their inherent design prioritizes stateful, multi-step business processes and integrations, which introduces higher latency and less granular control over compute resources compared to Azure Functions. This makes them less suitable for the high-volume, low-latency demands of real-time telemetry processing where immediate action on individual events is critical.
- ✗
Azure WebJobs with Event Hubs SDK
Why it's wrong here
Azure WebJobs run within an Azure App Service plan, meaning they are not serverless and consume dedicated resources from the underlying App Service instance. This requires manual scaling or pre-provisioning of capacity, which is less efficient and cost-effective for highly variable, real-time telemetry workloads compared to the automatic, consumption-based scaling offered by Azure Functions. WebJobs are better suited for background tasks within an existing App Service, not for dynamic, real-time event stream processing.
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
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.
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.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AZ-204 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AZ-204 exam.