You have an Azure Cosmos DB for NoSQL container. The container contains items that have the following properties.

You need to protect the data stored in the container by using Always Encrypted. For each property, you must use the strongest type of encryption and ensure that queries execute properly.
What is the strongest type of encryption that you can apply to each property? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

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You have a container named container1 in an Azure Cosmos DB for NoSQL account named account1.
You configure container1 to use Always Encrypted by using an encryption policy as shown in the C# and the Java exhibits. (Click the C# tab to view the encryption policy in C#. Click the Java tab to see the encryption policy in Java.)


For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation
According to the Azure Cosmos DB documentation1, Always Encrypted is a feature designed to protect sensitive data, such as credit card numbers or national identification numbers, stored in Azure Cosmos DB.
Always Encrypted allows clients to encrypt sensitive data inside client applications and never reveal the encryption keys to the database.
To use Always Encrypted, you need to define an encryption policy for each container that specifies which properties should be encrypted and which data encryption keys (DEK) should be used. The DEKs are stored in Azure Cosmos DB and are wrapped by customer-managed keys (CMK) that are stored in Azure Key Vault.
Based on the encryption policy shown in the exhibits, the creditcard property is encrypted with a DEK named dek1, and the SSN property is encrypted with a DEK named dek2. Both DEKs are wrapped by a CMK named cmk1.
To answer your statements:
You can perform a query that filters on the creditcard property = No. This is because the creditcard property is encrypted and cannot be used for filtering or sorting operations1.
You can perform a query that filters on the SSN property = No. This is also because the SSN property is encrypted and cannot be used for filtering or sorting operations1.
An application can be allowed to read the creditcard property while being restricted from reading the SSN property = Yes. This is possible by using different CMKs to wrap different DEKs and applying access policies on the CMKs in Azure Key Vault. For example, if you use cmk2 to wrap dek2 instead of cmk1, you can grant an application access to cmk1 but not cmk2, which means it can read the creditcard property but not the SSN property2.

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You plan to deploy two Azure Cosmos DB Core (SQL) API accounts that will each contain a single database.
The accounts will be configured as shown in the following table.

How should you provision the containers within each account to minimize costs? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

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Explanation

Box 1: Serverless capacity mode
Azure Cosmos DB serverless best fits scenarios where you expect intermittent and unpredictable traffic with long idle times. Because provisioning capacity in such situations isn't required and may be cost-prohibitive, Azure Cosmos DB serverless should be considered in the following use-cases:
Getting started with Azure Cosmos DB
Running applications with bursty, intermittent traffic that is hard to forecast, or low (<10%) average-to-peak traffic ratio Developing, testing, prototyping and running in production new applications where the traffic pattern is unknown Integrating with serverless compute services like Azure Functions Box 2: Provisioned throughput capacity mode and autoscale throughput The use cases of autoscale include:
Variable or unpredictable workloads: When your workloads have variable or unpredictable spikes in usage, autoscale helps by automatically scaling up and down based on usage. Examples include retail websites that have different traffic patterns depending on seasonality; IOT workloads that have spikes at various times during the day; line of business applications that see peak usage a few times a month or year, and more. With autoscale, you no longer need to manually provision for peak or average capacity.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/serverless
https://docs.microsoft.com/en-us/azure/cosmos-db/provision-throughput-autoscale#use-cases-of-autoscale

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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 in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a container named container! in an Azure Cosmos DB for NoSQL account.
You need to make the contents of container1 available as reference data for an Azure Stream Analytics job.
Solution: You create an Azure function that uses the Azure Cosmos 08 for NoSQL change feed as a trigger and an Azure event hub as the output.
Does this meet the goal?

• A.Yes
• B.No

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You have an Azure Cosmos DB for NoSQL account1 that is configured for automatic failover. The account1 account has a single read-write region in West US and a and a read region in East US.
You run the following PowerShell command.

What is the effect of running the command?

• A.A manual failover will occur.
• B.The account will be unavailable to writes during the change.
• C.The provisioned throughput for account1 will increase.
• D.The account will be configured for multi-region writes.

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