You have an Azure virtual machine based on a custom image named VM1.VM1 hosts an instance of Microsoft SQL Server 2019 Standard.You need to automate the maintenance of VM1 to meet the following requirements:Automate the patching of SQL Server and Windows Server.Automate full database backups and transaction log backups of the databases on VM1.Minimize administrative effort.What should you do first?
Answer(s): D
Automated Patching depends on the SQL Server infrastructure as a service (IaaS) Agent Extension. The SQL Server IaaS Agent Extension (SqlIaasExtension) runs on Azure virtual machines to automate administration tasks. The SQL Server IaaS extension is installed when you register your SQL Server VM with the SQL Server VM resource provider.To utilize the SQL IaaS Agent extension, you must first register your subscription with the Microsoft.SqlVirtualMachine provider, which gives the SQL IaaS extension the ability to create resources within that specific subscription.
https://docs.microsoft.com/en-us/azure/azure-sql/virtual-machines/windows/sql-server-iaas-agent-extension- automate-management https://docs.microsoft.com/en-us/azure/azure-sql/virtual-machines/windows/sql-agent-extension-manually- register-single-vm?tabs=bash%2Cazure-cli
HOTSPOT (Drag and Drop is not supported)You are building an Azure Stream Analytics job to retrieve game data.You need to ensure that the job returns the highest scoring record for each five-minute time interval of each game.How should you complete the Stream Analytics query? To answer, select the appropriate options in the answer area.Note: Each correct selection is worth one point.Hot Area:
Answer(s): A
Box 1: TopOne() OVER(PARTITION BY Game ORDER BY Score Desc) TopOne returns the top-rank record, where rank defines the ranking position of the event in the window according to the specified ordering. Ordering/ranking is based on event columns and can be specified in ORDER BY clause.Analytic Function Syntax:TopOne() OVER ([<PARTITION BY clause>] ORDER BY (<column name> [ASC |DESC])+ <LIMIT DURATION clause> [<WHEN clause>])Box 2: Tumbling(minute 5)Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.
https://docs.microsoft.com/en-us/stream-analytics-query/topone-azure-stream-analytics https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/stream-analytics/stream-analytics-window- functions.md
A company plans to use Apache Spark analytics to analyze intrusion detection data.You need to recommend a solution to analyze network and system activity data for malicious activities and policy violations. The solution must minimize administrative efforts.What should you recommend?
Answer(s): B
Azure DataBricks does have integration with Azure Monitor. Application logs and metrics from Azure Databricks can be send to a Log Analytics workspace.
https://docs.microsoft.com/en-us/azure/architecture/databricks-monitoring/application-logs
DRAG DROP (Drag and Drop is not supported)Your company analyzes images from security cameras and sends alerts to security teams that respond to unusual activity. The solution uses Azure Databricks.You need to send Apache Spark level events, Spark Structured Streaming metrics, and application metrics to Azure Monitor.Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions in the answer area and arrange them in the correct order.Select and Place:
Send application metrics using Dropwizard.Spark uses a configurable metrics system based on the Dropwizard Metrics Library.To send application metrics from Azure Databricks application code to Azure Monitor, follow these steps:Step 1: Configure your Azure Databricks cluster to use the Databricksmonitoring library. Prerequisite: Configure your Azure Databricks cluster to use the monitoring library.Step 2: Build the spark-listeners-loganalytics-1.0-SNAPSHOT.jar JAR fileStep 3: Create Dropwizard counters in your application code Create Dropwizard gauges or counters in your application code
You have an Azure data solution that contains an enterprise data warehouse in Azure Synapse Analytics named DW1.Several users execute adhoc queries to DW1 concurrently.You regularly perform automated data loads to DW1.You need to ensure that the automated data loads have enough memory available to complete quickly and successfully when the adhoc queries run.What should you do?
Answer(s): C
The performance capacity of a query is determined by the user's resource class.Smaller resource classes reduce the maximum memory per query, but increase concurrency.Larger resource classes increase the maximum memory per query, but reduce concurrency.
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/resource-classes-for-workload- management
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