AI-100試験無料問題集「Microsoft Designing and Implementing an Azure AI Solution 認定」

You have several AI applications that use an Azure Kubernetes Service (AKS) cluster. The cluster supports a maximum of 32 nodes.
You discover that occasionally and unpredictably, the application requires more than 32 nodes.
You need to recommend a solution to handle the unpredictable application load.
Which scaling method should you recommend?

You plan to build an application that will perform predictive analytics. Users will be able to consume the application data by using Microsoft Power Bl or a custom website.
You need to ensure that you can audit application usage.
Which auditing solution should you use?

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have an app named App1 that uses the Face API.
App1 contains several PersonGroup objects.
You discover that a PersonGroup object for an individual named Ben Smith cannot accept additional entries.
The PersonGroup object for Ben Smith contains 10,000 entries.
You need to ensure that additional entries can be added to the PersonGroup object for Ben Smith. The solution must ensure that Ben Smith can be identified by all the entries.
Solution: You create a second PersonGroup object for Ben Smith.
Does this meet the goal?

You plan to implement a bot that will require user authentication.
You need to recommend a secure solution that provides encryption for the authentication of the bot.
Which two security solutions should you include in the recommendation? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

You have an Azure SQL database, an Azure Data Lake Storage Gen 2 account, and an API developed by using Azure Machine Learning Studio.
You need to ingest data once daily from the database. score each row by using the API, and write the data to the storage account.
Solution: You create an Azure Data Factory pipeline that contains a Jupyter notebook activity.
Does this meet the goal?

You need to design an application that will analyze real-time data from financial feeds. The data will be ingested into Azure loT Hub. The data must be processed as quickly as possible in the order in which it is ingested.
Which service should you include in the design?

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You need to create an IoT solution that performs the following tasks:
* Identifies hazards
* Provides a real-time online dashboard
* Takes images of an area every minute
* Counts the number of people in an area every minute
Solution: You configure the IoT devices to send the images to an Azure IoT hub, and then you configure an Azure Automation call to Azure Cognitive Services that sends the results to an Azure event hub. You configure Microsoft Power BI to connect to the event hub by using Azure Stream Analytics.
Does this meet the goal?

Your company has an on-premises datacenter.
You plan to publish an app that will recognize a set of individuals by using the Face API. The model is trained.
You need to ensure that all images are processsed in the on-premises datacenter.
What should you deploy to host the Face API?

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have Azure IoT Edge devices that generate streaming data.
On the devices, you need to detect anomalies in the data by using Azure Machine Learning models. Once an anomaly is detected, the devices must add information about the anomaly to the Azure IoT Hub stream.
Solution: You expose a Machine Learning model as an Azure web service.
Does this meet the goal?