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Introductory Info
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 解析 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 frst 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 ofce 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 confgured 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 identifes 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.
Confgure account1 to support multiple read-write regions.
Implement referential integrity for the con-product container.
Use Azure Functions to send notifcations 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 identifes 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 frewall changes in the retail stores.
Requirements. Product Catalog Requirements
Litware identifes the following requirements for the product catalog:
Implement a custom confict resolution policy for the product catalog data.
Minimize the frequency of errors during updates of the con-product container.
Once multi-region writes are confgured, 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.
Question
You are troubleshooting the current issues caused by the application updates.
Which action can address the application updates issue without affecting the functionality of the application?