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To prepare for the DP-420 certification exam, candidates should have a solid understanding of Azure Cosmos DB fundamentals, including its architecture, data model, and various APIs. They should also have experience in designing and implementing cloud-native solutions using Azure services, such as Azure Functions, Azure App Service, and Azure Event Grid. In addition, candidates should be familiar with programming languages such as C#, Java, Python, and JavaScript, as well as web development frameworks such as ASP.NET and Node.js. By passing the DP-420 Exam, professionals can demonstrate their expertise in using Azure Cosmos DB to design and build cloud-native applications that are scalable, performant, and highly available.
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NEW QUESTION # 36
You need to identify which connectivity mode to use when implementing App2. The solution must support the planned changes and meet the business requirements.
Which connectivity mode should you identify?
Answer: C
Explanation:
Scenario: Develop an app named App2 that will run from the retail stores and query the data in account2.
App2 must be limited to a single DNS endpoint when accessing account2.
By using Azure Private Link, you can connect to an Azure Cosmos account via a private endpoint. The private endpoint is a set of private IP addresses in a subnet within your virtual network.
When you're using Private Link with an Azure Cosmos account through a direct mode connection, you can use only the TCP protocol. The HTTP protocol is not currently supported.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/how-to-configure-private-endpoints
Topic 1, Litware, inc
Case Study
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.
At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.
To start the case study
To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.
Overview
Litware, Inc. is a United States-based grocery retailer. Litware has a main office and a primary datacenter in Seattle. The company has 50 retail stores across the United States and an emerging online presence. Each store connects directly to the internet.
Existing environment. Cloud and Data Service Environments.
Litware has an Azure subscription that contains the resources shown in the following table.
Each container in productdb is configured for manual throughput.
The con-product container stores the company's product catalog data. Each document in con-product includes a con-productvendor value. Most queries targeting the data in con-product are in the following format.
SELECT * FROM con-product p WHERE p.con-productVendor - 'name'
Most queries targeting the data in the con-productVendor container are in the following format SELECT * FROM con-productVendor pv ORDER BY pv.creditRating, pv.yearFounded Existing environment. Current Problems.
Litware identifies the following issues:
Updates to product categories in the con-productVendor container do not propagate automatically to documents in the con-product container.
Application updates in con-product frequently cause HTTP status code 429 "Too many requests". You discover that the 429 status code relates to excessive request unit (RU) consumption during the updates.
Requirements. Planned Changes
Litware plans to implement a new Azure Cosmos DB Core (SQL) API account named account2 that will contain a database named iotdb. The iotdb database will contain two containers named con-iot1 and con-iot2.
Litware plans to make the following changes:
Store the telemetry data in account2.
Configure account1 to support multiple read-write regions.
Implement referential integrity for the con-product container.
Use Azure Functions to send notifications about product updates to different recipients.
Develop an app named App1 that will run from all locations and query the data in account1.
Develop an app named App2 that will run from the retail stores and query the data in account2. App2 must be limited to a single DNS endpoint when accessing account2.
Requirements. Business Requirements
Litware identifies the following business requirements:
Whenever there are multiple solutions for a requirement, select the solution that provides the best performance, as long as there are no additional costs associated.
Ensure that Azure Cosmos DB costs for IoT-related processing are predictable.
Minimize the number of firewall changes in the retail stores.
Requirements. Product Catalog Requirements
Litware identifies the following requirements for the product catalog:
Implement a custom conflict resolution policy for the product catalog data.
Minimize the frequency of errors during updates of the con-product container.
Once multi-region writes are configured, maximize the performance of App1 queries against the data in account1.
Trigger the execution of two Azure functions following every update to any document in the con-product container.
NEW QUESTION # 37
You have an Azure Cosmos DB for NoSQL account.
You plan 10 create a container named container1. The container1 container will store items that include two properties named nm and age The most commonly executed queries will query container1 for a specific name. The following is a sample of the query.
You need to define an opt-in Indexing policy for container1. The solution must meet the following requirements:
* Minimize the number of request units consumed by the queries.
* Ensure that the _etag property is excluded from indexing.
How should you define the indexing poky? To answer, select the appropriate options in the answer are a. NOTE: Each correct selection Is worth one point.
Answer:
Explanation:
NEW QUESTION # 38
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.
Answer:
Explanation:
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.
NEW QUESTION # 39
You have a database named db1in an Azure Cosmos DB for NoSQL account named account 1.
You need to write JSON data to db1 by using Azure Stream Analytics. The solution must minimize costs.
Which should you do before you can use db1 as an output of Stream Analytics?
Answer: C
NEW QUESTION # 40
You need to create a data store for a directory of small and medium-sized businesses (SMBs). The data store must meet the following requirements:
* Store companies and the users employed by them. Each company will have less than 1,000 users.
* Some users have data that is greater than 2 KB.
* Associate each user to only one company.
* Provide the ability to browse by company.
* Provide the ability to browse the users by company.
* Whenever a company or user profile is selected, show a details page for the company and all the related users.
* Be optimized for reading data.
Which design should you implement to optimize the data store for reading data?
Answer: D
Explanation:
Explanation
Azure Cosmos DB is a multi-model database that supports various data models, such as documents, key-value, graph, and column-family3. The core content-model of Cosmos DB's database engine is based on atom-record-sequence (ARS), which allows it to store and query different types of data in a flexible and efficient way3.
To optimize the data store for reading data, you should consider the following factors:
* The size and shape of your data
* The frequency and complexity of your queries
* The latency and throughput requirements of your application
* The trade-offs between storage efficiency and query performance
Based on these factors, one possible design that you could implement is B. In a company container, create a document for each company. Embed the users into company documents. Use the company ID as the partition key.
This design has the following advantages:
* It stores companies and users as self-contained documents that can be easily retrieved by company ID1.
* It avoids storing redundant data or creating additional containers for users1.
* It allows you to browse by company and browse the users by company with simple queries1.
* It shows a details page for the company and all the related users by fetching a single document1.
* It leverages the benefits of embedding data, such as reducing the number of requests, improving query performance, and simplifying data consistency2.
This design also has some limitations, such as:
* It may not be suitable for some users who have data that is greater than 2 KB, as it could exceed the
* maximum document size limit of 2 MB2.
* It may not be optimal for scenarios where users need to be associated with more than one company or queried independently from companies2.
* It may not be scalable for companies that have more than 1,000 users, as it could result in hot partitions or throttling2.
Depending on your specific use case and requirements, you may need to adjust this design or choose a different one. For example, you could use a hybrid data model that combines embedding and referencing data2
, or you could use a graph data model that expresses entities and relationships as vertices and edges.
NEW QUESTION # 41
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