AZ-305 Design infrastructure solutions Practice Question
Your organization is designing a solution to capture and analyze IoT data from millions of devices. The solution must ingest data at high velocity, store the data for long-term analytics, and provide real-time dashboards. Which combination of Azure services should you recommend?
⚠ Common exam trap
Test-takers frequently confuse Azure IoT Hub with Azure Event Hubs, as both can ingest device data, but IoT Hub is designed for device management and bidirectional communication, not for the massive-scale, high-velocity event streaming required for millions of devices.
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 Event Hubs, Azure Data Lake Storage, and Azure Stream Analytics
Azure Event Hubs is designed for high-velocity data ingestion from millions of devices, Azure Data Lake Storage provides scalable and cost-effective long-term storage for analytics, and Azure Stream Analytics enables real-time processing and dashboarding. This combination directly addresses the requirements of high-throughput ingestion, durable storage, and real-time analytics without unnecessary complexity.
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 Event Hubs, Azure Data Lake Storage, and Azure Stream Analytics
Why this is correct
Azure Event Hubs is a massively scalable event streaming platform that ingests millions of events per second with low latency, making it the correct high-velocity ingestion layer. Azure Data Lake Storage Gen2 stores both structured and unstructured data in a hierarchical namespace with POSIX access control and ACID transactions, ideally suited for long-term analytics. Azure Stream Analytics runs serverless, SQL-like queries on live and historical streams, providing the low-latency, stateful processing needed to deliver real-time dashboards.
- ✗
Azure Service Bus, Azure SQL Database, and Power BI
Why it's wrong here
Azure Service Bus is an enterprise message broker built for reliable communication between decoupled applications, not for high-velocity telemetry ingestion; its queue and topic throughput is far below Event Hubs' partitioned stream capacity. Azure SQL Database is an OLTP-oriented relational store that, while supporting analytic workloads in small scale, is cost-prohibitive and architecturally unsuited for petabyte-scale long-term analytics. Power BI can render dashboards, but only when fed from a proper analytical stream or warehouse, and it cannot fix the fundamental mismatches in the ingestion and storage layers.
- ✗
Azure Cosmos DB, Azure Data Explorer, and Azure Logic Apps
Why it's wrong here
Azure Cosmos DB is a multi-model NoSQL database engineered for single-digit-millisecond operational reads and writes, not for long-term analytical storage; its request-unit-based charging becomes excessively expensive for massive historical datasets. Azure Data Explorer specializes in near-real-time time-series and log analytics with powerful aggregation, but it is a query-and-exploration service rather than a dashboard engine and does not natively present live visualizations to end users. Azure Logic Apps handles workflow automation and integration, but it is not a data-processing service capable of continuous, high-velocity event analytics.
- ✗
Azure IoT Hub, Azure Blob Storage, and Azure Functions
Why it's wrong here
Azure IoT Hub is tailored to secure device connectivity, including device identity, twin state, and command-and-control, but it is not a general-purpose high-velocity ingestion pipeline—it is fine for specific device messages yet lacks Event Hubs' open, multi-publisher event streaming semantics. Azure Blob Storage is an inexpensive object store, but it lacks the hierarchical namespace, distributed filesystem scheme, and analytics-oriented access patterns that Data Lake Storage Gen2 provides, limiting its efficiency for long-running analytical queries. Azure Functions is a serverless compute trigger that runs on demand, not a real-time dashboard or analytics service; it does not execute continuous, low-latency queries over streaming data.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AZ-305 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-305 exam.