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Professional Latest DP-420 Exam Experience - Win Your Microsoft Certificate with Top Score

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The Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420) certification is a valuable credential that every Microsoft professional should earn it. The Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420) certification exam offers a great opportunity for beginners and experienced professionals to demonstrate their expertise. With the Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420) certification exam everyone can upgrade their skills and knowledge. There are other several benefits that the Microsoft DP-420 exam holders can achieve after the success of the Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420) certification exam.

Microsoft DP-420 Exam is an industry-recognized certification designed for professionals who want to prove their expertise in designing and implementing cloud-native applications using Microsoft Azure Cosmos DB. This is an advanced-level exam that tests the candidate's knowledge and skills in cloud-native application development, Azure Cosmos DB, and other related technologies.

Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q49-Q54):

NEW QUESTION # 49
You need to create a database in an Azure Cosmos DB for NoSQL account. The database will contain three containers named coll1, coll2 and coll3. The coll1 container will have unpredictable read and write volumes. The col!2 and coll3 containers will have predictable read and write volumes. The expected maximum throughput for coll1 and coll2 is 50,000 request units per second (RU/s) each.
How should you provision the collection while minimizing costs?

A. Create a provisioned throughput account. Set the throughput for call1 to Autoscale. Set the throughput for call2 and coll3 to Manual.
B. Create a serverless account.
C. Create a provisioned throughput account. Set the throughput for coll1 to Manual. Set the throughput for coll2 and coll3 to Autoscale.

Answer: A

Explanation:
Azure Cosmos DB offers two different capacity modes: provisioned throughput and serverless1. Provisioned throughput mode allows you to configure a certain amount of throughput (expressed in Request Units per second or RU/s) that is provisioned on your databases and containers. You get billed for the amount of throughput you've provisioned, regardless of how many RUs were consumed1. Serverless mode allows you to run your database operations without having to configure any previously provisioned capacity. You get billed for the number of RUs that were consumed by your database operations and the storage consumed by your data1.
To create a database that minimizes costs, you should consider the following factors:
The read and write volumes of your containers
The predictability and variability of your traffic
The latency and throughput requirements of your application
The geo-distribution and availability needs of your data
Based on these factors, one possible option that you could choose is B. Create a provisioned throughput account. Set the throughput for coll1 to Autoscale. Set the throughput for coll2 and coll3 to Manual.
This option has the following advantages:
It allows you to handle unpredictable read and write volumes for coll1 by using Autoscale, which automatically adjusts the provisioned throughput based on the current load1.
It allows you to handle predictable read and write volumes for coll2 and coll3 by using Manual, which lets you specify a fixed amount of provisioned throughput that meets your performance needs1.
It allows you to optimize your costs by paying only for the throughput you need for each container1.
It allows you to enable geo-distribution for your account if you need to replicate your data across multiple regions1.
This option also has some limitations, such as:
It may not be suitable for scenarios where all containers have intermittent or bursty traffic that is hard to forecast or has a low average-to-peak ratio1.
It may not be optimal for scenarios where all containers have low or sporadic traffic that does not justify provisioned capacity1.
It may not support availability zones or multi-master replication for your account1.
Depending on your specific use case and requirements, you may need to choose a different option. For example, you could use a serverless account if all containers have low or sporadic traffic that does not require predictable performance or geo-distribution1. Alternatively, you could use a provisioned throughput account with Manual for all containers if all containers have stable and consistent traffic that requires predictable performance or geo-distribution1.

NEW QUESTION # 50
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 container1 in an Azure Cosmos DB Core (SQL) API account.
You need to make the contents of container1 available as reference data for an Azure Stream Analytics job.
Solution: You create an Azure Data Factory pipeline that uses Azure Cosmos DB Core (SQL) API as the input and Azure Blob Storage as the output.
Does this meet the goal?

A. Yes
B. No

Answer: B

Explanation:
Instead create an Azure function that uses Azure Cosmos DB Core (SQL) API change feed as a trigger and Azure event hub as the output.
The Azure Cosmos DB change feed is a mechanism to get a continuous and incremental feed of records from an Azure Cosmos container as those records are being created or modified. Change feed support works by listening to container for any changes. It then outputs the sorted list of documents that were changed in the order in which they were modified.
The following diagram represents the data flow and components involved in the solution:

NEW QUESTION # 51
You have an on-premises computer named Computer1 that runs Windows 11.
On Computer1, you install the Azure Cosmos DB Emulator by using the default settings. You need to connect to the API for NoSQL clients hosted by the emulator. What should you use?

A. localhost :443 and the built-in Administrator user account credentials
B. Computer1 and a randomly-generated key
C. localhost: 8681 and a well-known key
D. Computer1 and the credentials used when installing the emulator

Answer: C

NEW QUESTION # 52
You have the indexing policy shown in the following exhibit.

Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Box 1: ORDER BY c.name DESC, c.age DESC
Queries that have an ORDER BY clause with two or more properties require a composite index.
The following considerations are used when using composite indexes for queries with an ORDER BY clause with two or more properties:
If the composite index paths do not match the sequence of the properties in the ORDER BY clause, then the composite index can't support the query.
The order of composite index paths (ascending or descending) should also match the order in the ORDER BY clause.
The composite index also supports an ORDER BY clause with the opposite order on all paths.
Box 2: At the same time as the item creation
Azure Cosmos DB supports two indexing modes:
Consistent: The index is updated synchronously as you create, update or delete items. This means that the consistency of your read queries will be the consistency configured for the account.
None: Indexing is disabled on the container.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/index-policy

NEW QUESTION # 53
You have an Apache Spark pool in Azure Synapse Analytics that runs the following Python code in a notebook.

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
New and updated orders will be added to contoso-erp.orders: Yes
The code performs bulk data ingestion from contoso-app: No
Both contoso-app and contoso-erp have Analytics store enabled: Yes
The code uses the spark.readStream method to read data from a container named orders in a database named contoso-app. The data is then filtered by a condition and written to another container named orders in a database named contoso-erp using the spark.writeStream method. The write mode is set to "append", which means that new and updated orders will be added to the destination container1.
The code does not perform bulk data ingestion from contoso-app, but rather stream processing. Bulk data ingestion is a process of loading large amounts of data into a data store in batches. Stream processing is a process of continuously processing data as it arrives in real-time2.
Both contoso-app and contoso-erp have Analytics store enabled, because they are both accessed by Spark pools using the spark.cosmos.oltp method. This method requires that the containers have Analytics store enabled, which is a feature that allows Spark pools to query data stored in Azure Cosmos DB containers using SQL APIs3.

NEW QUESTION # 54
......

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