Hotspot Question You have a production line that is monitored by using IoT devices. You are building a project that will process data streams from the IoT devices. You need to recommend a pipeline…

This question tests your knowledge of Azure services for building an end-to-end IoT data pipeline that ingests streams, performs analysis/defect detection, and triggers automated actions.

Submitted by ngozi_ng· Mar 6, 2026Design data storage solutions

Question

Hotspot Question You have a production line that is monitored by using IoT devices. You are building a project that will process data streams from the IoT devices. You need to recommend a pipeline solution that will perform the following activities: - Ingest the data streams from the IoT devices. - Analyze the data and identify manufacturing defects among items on the production line. - When a manufacturing defect is identified, flag the item for removal from the production line. What should you include in the recommendation for each activity? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point. Answer:

Exhibit

Answer Area

Ingest the data streams:
Azure Cosmos DBAzure Event HubsAzure FunctionsAzure IoT CentralAzure Stream Analytics
Identify defects:
Azure Cosmos DBAzure Event HubsAzure FunctionsAzure IoT CentralAzure Stream Analytics
Flag the items:
Azure Cosmos DBAzure Event HubsAzure FunctionsAzure IoT CentralAzure Stream Analytics

Explanation

This question tests your knowledge of Azure services for building an end-to-end IoT data pipeline that ingests streams, performs analysis/defect detection, and triggers automated actions.

Approach. For ingesting data streams from IoT devices, Azure IoT Hub is the correct choice as it is purpose-built for bidirectional communication between IoT devices and the cloud, handling massive device connectivity and telemetry ingestion. For analyzing the data streams and identifying manufacturing defects, Azure Stream Analytics is the correct choice as it provides real-time stream processing with built-in ML model integration and can query live data to detect anomalies or defects. For flagging items for removal when a defect is identified, Azure Service Bus or Azure Logic Apps (or an Azure Function triggered by Stream Analytics output) is appropriate - Stream Analytics outputs an alert/event to a downstream service such as Azure Service Bus or an Azure Function, which then triggers the physical or logical action of flagging the item for removal from the production line.

Concept tested. Azure IoT and real-time data pipeline architecture: understanding the roles of Azure IoT Hub (device ingestion), Azure Stream Analytics (real-time processing and anomaly/defect detection), and downstream action services like Azure Service Bus or Azure Functions (event-driven automated responses) in an end-to-end IoT manufacturing scenario.

Reference. https://learn.microsoft.com/en-us/azure/stream-analytics/stream-analytics-solution-patterns

Topics

#IoT data processing#Azure Event Hubs#Azure Stream Analytics#Real-time analytics#Azure Functions

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