Which action can address the application updates issue without affecting the functionality of the application?

Topic 1, Litware, inc

Case Study

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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.

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?
A . Enable time to live for the con-product container.
B. Set the default consistency level of account1 to strong.
C. Set the default consistency level of account1 to bounded staleness.
D. Add a custom indexing policy to the con-product container.

View Answer

Answer: C

Explanation:

Bounded staleness is frequently chosen by globally distributed applications that expect low write latencies but require total global order guarantee. Bounded staleness is great for applications featuring group collaboration and sharing, stock ticker, publish-subscribe/queueing etc.

Scenario: 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.

Explanation:

Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels