DP-420 Practice Test

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 conproduct
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.