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AZ-204 Practice Question: Connect to and consume Azure services and third-party services

You are building a solution that processes events from multiple Azure Event Hubs. Events must be dispatched to different downstream services based on the event type. You need a serverless solution that can handle high throughput and uses managed identity to authenticate to Event Hubs. Which Azure service should you use?

⚠ Common exam trap

Test-takers frequently confuse Azure Stream Analytics as a general-purpose event dispatcher, but it is specifically a stream analytics engine, not a serverless event router; Azure Functions is the correct choice for event-driven dispatching with managed identity support.

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 (Event Hubs trigger) with managed identity

Azure Functions with an Event Hubs trigger supports managed identity authentication, enabling secure, passwordless connections to Event Hubs. It is a serverless, event-driven compute service that can scale to handle high throughput by processing events in parallel across multiple partitions. This makes it the ideal choice for dispatching events to downstream services based on event type.

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 (Event Hubs trigger) with managed identity

    Why this is correct

    Azure Functions with an Event Hubs trigger is an excellent choice for processing events from multiple Event Hubs at scale. It automatically handles consumer group management and checkpointing, allowing for highly concurrent and reliable event processing. Utilizing a managed identity provides a secure, credential-free way for the Function App to authenticate with Event Hubs and other Azure services, adhering to the principle of least privilege and enhancing security posture.

  • Azure Stream Analytics

    Why it's wrong here

    Azure Stream Analytics is primarily designed for real-time data analytics, performing aggregations, transformations, and pattern matching on streaming data. While it can ingest from Event Hubs, its strength lies in SQL-like queries for analytical insights and routing to predefined sinks, not in executing arbitrary custom code or complex business logic for individual event processing and routing, which is better suited for a compute service.

  • Azure Logic Apps (Event Hubs connector)

    Why it's wrong here

    Azure Logic Apps excel at orchestrating workflows and integrating various services through its extensive connector library, including Event Hubs. However, for high-throughput event processing scenarios, Logic Apps typically incur higher costs and have inherent throughput limitations compared to compute services like Azure Functions. Its consumption model and design are optimized for business process automation and integration, not for raw, high-volume event ingestion and processing at scale.

  • Azure Data Factory

    Why it's wrong here

    Azure Data Factory is a cloud-based ETL and data integration service designed for orchestrating and automating data movement and transformation across various data stores. It is primarily built for batch processing and scheduled data pipelines, not for real-time, event-driven processing of individual messages from a streaming source like Event Hubs. Its operational model is fundamentally different from a real-time event consumer.

Quick reference

Cloud Service Model Comparison

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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