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NEW QUESTION: 1
True or False? MPLS may use an existing data link layer header field to identify a label, instead of using a specific MPLS header
A. FALSE
B. TRUE
Answer: B

NEW QUESTION: 2
Click to expand each objective. To connect to the Azure portal, type https://portal.azure.com in the browser address bar.



When you are finished performing all the tasks, click the 'Next' button.
Note that you cannot return to the lab once you click the 'Next' button. Scoring occur in the background while you complete the rest of the exam.
Overview
The following section of the exam is a lab. In this section, you will perform a set of tasks in a live environment. While most functionality will be available to you as it would be in a live environment, some functionality (e.g., copy and paste, ability to navigate to external websites) will not be possible by design.
Scoring is based on the outcome of performing the tasks stated in the lab. In other words, it doesn't matter how you accomplish the task, if you successfully perform it, you will earn credit for that task.
Labs are not timed separately, and this exam may have more than one lab that you must complete. You can use as much time as you would like to complete each lab. But, you should manage your time appropriately to ensure that you are able to complete the lab(s) and all other sections of the exam in the time provided.
Please note that once you submit your work by clicking the Next button within a lab, you will NOT be able to return to the lab.
To start the lab
You may start the lab by clicking the Next button.
You plan to configure VM1 to be accessible from the Internet.
You need to add a public IP address to the network interface used by VM1.
What should you do from Azure portal?
Answer:
Explanation:
See solution below.
Explanation
You can add private and public IP addresses to an Azure network interface by completing the steps that follow.
Step 1: In Azure portal, click More services > type virtual machines in the filter box, and then click Virtual machines.
Step 2: In the Virtual machines pane, click the VM you want to add IP addresses to. Click Network interfaces in the virtual machine pane that appears, and then select the network interface you want to add the IP addresses to. In the example shown in the following picture, the NIC named myNIC from the VM named myVM is selected:

Step 3: In the pane that appears for the NIC you selected, click IP configurations.
Step 4: Click Create public IP address.

Step 5: In the Create public IP address pane that appears, enter a Name, select an IP address assignment type, a Subscription, a Resource group, and a Location, then click Create, as shown in the following picture:
References:
https://docs.microsoft.com/en-us/azure/virtual-network/virtual-network-multiple-ip-addresses-portal

NEW QUESTION: 3
Azureサービスを正しい定義に一致させます。
手順:回答するには、適切なAzureサービスを左側の列から右側の説明にドラッグします。 各サービスは、1回、複数回、またはまったく使用されません。
注:それぞれの正しい選択には1ポイントの価値があります。

Answer:
Explanation:

Explanation

Box 1:
Azure Functions provides the platform for serverless code.
Azure Functions is a serverless compute service that lets you run event-triggered code without having to explicitly provision or manage infrastructure.
Box 2:
Azure Databricks is a big analysis service for machine learning.
Azure Databricks is an Apache Spark-based analytics platform. The platform consists of several components including 'MLib'. Mlib is a Machine Learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as underlying optimization primitives.
Box 3:
Azure Application Insights detects and diagnoses anomalies in web apps.
Application Insights, a feature of Azure Monitor, is an extensible Application Performance Management (APM) service for developers and DevOps professionals. Use it to monitor your live applications. It will automatically detect performance anomalies, and includes powerful analytics tools to help you diagnose issues and to understand what users actually do with your app.
Box 4:
Azure App Service hosts web apps.
Azure App Service is an HTTP-based service for hosting web applications, REST APIs, and mobile back ends.
You can develop in your favorite language, be it .NET, .NET Core, Java, Ruby, Node.js, PHP, or Python.
Applications run and scale with ease on both Windows and Linux-based environments.
References:
https://docs.microsoft.com/en-us/azure/azure-functions/
https://docs.microsoft.com/en-us/azure/azure-databricks/what-is-azure-databricks#apache-spark-based-analytics-
https://docs.microsoft.com/en-us/azure/azure-monitor/app/app-insights-overview
https://docs.microsoft.com/en-us/azure/app-service/overview

NEW QUESTION: 4
You have an Azure Stream Analytics query. The query returns a result set that contains 10,000 distinct values for a column named clusterID.
You monitor the Stream Analytics job and discover high latency.
You need to reduce the latency.
Which two actions should you perform? Each correct answer presents a complete solution.
注:それぞれの正しい選択には1ポイントの価値があります。
A. Increase the number of streaming units.
B. Add a temporal analytic function.
C. Add a pass-through query.
D. Convert the query to a reference query.
E. Scale out the query by using PARTITION BY.
Answer: A,E
Explanation:
C: Scaling a Stream Analytics job takes advantage of partitions in the input or output. Partitioning lets you divide data into subsets based on a partition key. A process that consumes the data (such as a Streaming Analytics job) can consume and write different partitions in parallel, which increases throughput.
E: Streaming Units (SUs) represents the computing resources that are allocated to execute a Stream Analytics job. The higher the number of SUs, the more CPU and memory resources are allocated for your job. This capacity lets you focus on the query logic and abstracts the need to manage the hardware to run your Stream Analytics job in a timely manner.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-parallelization
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-streaming-unit-consumption