Building a Solution for Monitoring and Alarm Triggering with Azure Stream Analytics
Question
You operate an IoT solution for a plant manufacturing ceramic filter inserts for the automotive industry.
The critical part of the technology where the products are being baked in high-temperature ovens.
A large number of temperature data is collected from several ovens by sensors, most of them being not relevant.
However, when the average temperature exceeds a certain threshold, an alarm has to be triggered and the data related to the exception event must be forwarded to the IoT hub.
You start building a solution using Azure Stream Analytics running on edge devices, following these steps: Create a Stream Analytics job Create a storage account Set the input of the job to Edge Hub <.......1........> Define the transformation query <.......2........> Create a deployment manifest Which two steps are missing?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D. E.Correct Answers: A and C.
Option A is CORRECT because it is the Edge Hub module that orchestrates the message flow between the other modules.
Both the input and the output of the ASA job should be set to Edge Hub.
Option B is incorrect because it is the Edge Hub module that orchestrates the message flow between the other modules.
Event Hubs is an Azure service which plays no role in this scenario.
Option C is CORRECT because to prepare a Stream Analytics job for an IoT Edge device, you need to associate the job with a container in a storage account.
While deploying the job, the job definition is exported to the storage container.
Option D is incorrect because the job doesn't need to be linked to the IoT hub.
It needs to be linked to a container of a storage account so that it can be deployed to the edge device.
Option E is incorrect because defining the message routes is part of the “Create deployment manifest” task.
Diagram:
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Reference:
Based on the scenario described, the missing steps to complete the solution using Azure Stream Analytics running on edge devices are:
- Set the output of the job to Event Hub or IoT Hub
- Link the job with a container in a storage account
Explanation:
Set the output of the job to Event Hub or IoT Hub: After setting the input of the Stream Analytics job to Edge Hub, the next step is to define where to send the data that has been processed by the job. In this case, the requirement is to forward the data related to the exception event to the IoT Hub, so it can be further analyzed and acted upon. This can be achieved by setting the output of the job to either Event Hub or IoT Hub. The choice between these two options depends on the specific requirements of the solution, but both of them are capable of forwarding data to the IoT Hub. Therefore, options A and B are correct.
Link the job with a container in a storage account: Once the data has been processed and forwarded to the IoT Hub, it may be necessary to store it for further analysis or compliance purposes. To achieve this, a container in a storage account can be used to hold the data. Therefore, the job needs to be linked with the storage account and the specific container. This can be done by defining a connection string that points to the storage account and container in the Stream Analytics job's output configuration. This step is not explicitly mentioned in the given scenario, but it is a common practice to store the processed data in a container. Therefore, option C is also correct.
Regarding options D and E, they are not necessary for completing the solution, as they are not mentioned in the scenario. However, it is worth noting that linking the job with the IoT Hub (option D) may be required in other scenarios where bidirectional communication is needed, or when the job needs to receive commands or configurations from the IoT Hub. Defining the routes between the edge modules (option E) is also not mentioned in the scenario, but it is a step that may be required when multiple modules are involved in the solution and need to communicate with each other.