Free DP-420 Braindumps Download Updated on Oct 15, 2025 with 146 Questions
Microsoft DP-420 Exam Practice Test Questions
Microsoft DP-420 certification exam is designed for individuals who are interested in demonstrating their expertise in designing and implementing cloud-native applications using Microsoft Azure Cosmos DB. DP-420 exam validates the skills and knowledge required to design and implement scalable, globally distributed, and highly available applications using Azure Cosmos DB. DP-420 exam covers various topics such as data modeling, partitioning, indexing, querying, and scaling Azure Cosmos DB databases. Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB certification exam is suitable for developers, architects, and data professionals who work with Azure Cosmos DB and want to validate their skills and knowledge in this area.
To earn the Microsoft DP-420 certification, candidates must pass the certification exam. DP-420 exam consists of multiple-choice questions, and candidates will have two hours to complete it. DP-420 exam fee is $165, and it can be taken online or in-person at a Microsoft testing center. After passing the exam, candidates will receive a digital badge and a certificate that they can use to showcase their skills and expertise in developing cloud-native applications using Azure Cosmos DB.
NEW QUESTION # 25
You have an Azure subscription that contains an Azure Cosmos DB for NoSQL database named DB1. The shared throughput provisioned for DB1 is 10,000 DTU/s. DB1 contains the containers shown in the following table.
You need to modify the throughput for the containers. The solution must meet the following requirements:
* The maximum throughput for Container1 must be 4,000 DTU/s.
* The throughput for Contained must be shared across the containers.
* Administrative effort must be minimized.
What should you do? To answer, select the appropriate options in the answer are a. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 26
You plan to deploy two Azure Cosmos DB Core (SQL) API accounts that will each contain a single database.
The accounts will be configured as shown in the following table.
How should you provision the containers within each account to minimize costs? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Serverless capacity mode
Azure Cosmos DB serverless best fits scenarios where you expect intermittent and unpredictable traffic with long idle times. Because provisioning capacity in such situations isn't required and may be cost-prohibitive, Azure Cosmos DB serverless should be considered in the following use-cases:
Getting started with Azure Cosmos DB
Running applications with bursty, intermittent traffic that is hard to forecast, or low (<10%) average-to-peak traffic ratio Developing, testing, prototyping and running in production new applications where the traffic pattern is unknown Integrating with serverless compute services like Azure Functions Box 2: Provisioned throughput capacity mode and autoscale throughput The use cases of autoscale include:
Variable or unpredictable workloads: When your workloads have variable or unpredictable spikes in usage, autoscale helps by automatically scaling up and down based on usage. Examples include retail websites that have different traffic patterns depending on seasonality; IOT workloads that have spikes at various times during the day; line of business applications that see peak usage a few times a month or year, and more. With autoscale, you no longer need to manually provision for peak or average capacity.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/serverless
https://docs.microsoft.com/en-us/azure/cosmos-db/provision-throughput-autoscale#use-cases-of-autoscale
NEW QUESTION # 27
You have a database named db1 in an Azure Cosmos DB for NoSQL account named account1. The db1 database has a manual throughput of 4,000 request units per second (RU/s).
You need to move db1 from manual throughput to autoscale throughput by using the Azure CLI. The solution must provide a minimum of 4,000 RU/s and a maximum of 40,000 RU/s.
How should you complete the CLI statements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 28
You have a database named db1 in an Azure Cosmos DB f You have a third-party application that is exposed thro You need to migrate data from the application to a What should you use?
- A. Database Migration Assistant
- B. Azure Data Factory
- C. Azure Migrate
Answer: B
Explanation:
Explanation
you can migrate data from various data sources to Azure Cosmos DB using different tools and methods. The choice of the migration tool depends on factors such as the data source, the Azure Cosmos DB API, the size of data, and the expected migration duration1. Some of the common migration tools are:
Azure Cosmos DB Data Migration tool: This is an open source tool that can import data to Azure Cosmos DB from sources such as JSON files, MongoDB, SQL Server, CSV files, and Azure Cosmos DB collections. This tool supports the SQL API and the Table API of Azure Cosmos DB2.
Azure Data Factory: This is a cloud-based data integration service that can copy data from various sources to Azure Cosmos DB using connectors. This tool supports the SQL API, MongoDB API, Cassandra API, Gremlin API, and Table API of Azure Cosmos DB3.
Azure Cosmos DB live data migrator: This is a command-line tool that can migrate data from one Azure Cosmos DB container to another container within the same or different account. This tool supports live migration with minimal downtime and works with any Azure Cosmos DB API4.
For your scenario, if you want to migrate data from a third-party application that is exposed through an OData endpoint to a container in Azure Cosmos DB for NoSQL, you should use Azure Data Factory. Azure Data Factory has an OData connector that can read data from an OData source and write it to an Azure Cosmos DB sink using the SQL API5. You can create a copy activity in Azure Data Factory that specifies the OData source and the Azure Cosmos DB sink, and run it on demand or on a schedule.
NEW QUESTION # 29
You plan to create an operational system that will store data in an Azure Cosmos OB 'or NoSQL account. You need to configure the account to meet the following requirements:
* Support Spar* queries.
* Support the analysis of data from the last six months.
* Only pay for analytical compute when running queries.
Which three actions should you perform? Each correct answer presents part of the solution. NOTE Each correct selection is worth one point.
- A. Create a container and set the time to live to six months.
- B. Create an Azure Databanks notebook.
- C. Create an Azure Synapse pipeline.
- D. Create a container and set the analytical property to six months.
- E. Create an Azure Synapse linked service.
- F. Enable Azure Synapse Link for the account
Answer: B,D,F
NEW QUESTION # 30
You have an Azure Cosmos DB Core (SQL) API account named account1.
You have the Azure virtual networks and subnets shown in the following table.
The vnet1 and vnet2 networks are connected by using a virtual network peer.
The Firewall and virtual network settings for account1 are configured as shown in the exhibit.
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:
Box 1: Yes
VM1 is on vnet1.subnet1 which has the Endpoint Status enabled.
Box 2: No
Only virtual network and their subnets added to Azure Cosmos account have access. Their peered VNets cannot access the account until the subnets within peered virtual networks are added to the account.
Box 3: No
Only virtual network and their subnets added to Azure Cosmos account have access.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/how-to-configure-vnet-service-endpoint
NEW QUESTION # 31
You have a container in an Azure Cosmos DB for NoSQL account. The database that has a manual throughput of 30,000 request units per second (RU/s). The current consumption details are shewn in the following chart.
Normalized RU Consumption (%) By PartitionKeyRangeID
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:
Explanation:
NEW QUESTION # 32
You have an Azure Cosmos DB for NoSQL account.
The change feed is enabled on a container named invoice.
You create an Azure function that has a trigger on the change feed.
What is received by the Azure function?
- A. only the partition key and the changed properties of the updated items
- B. all the properties of the original items and the updated items
- C. all the properties of the updated items
- D. only the changed properties and the system-defined properties of the updated items
Answer: D
Explanation:
According to the Azure Cosmos DB documentation12, the change feed is a persistent record of changes to a container in the order they occur. The change feed outputs the sorted list of documents that were changed in the order in which they were modified.
The Azure function that has a trigger on the change feed receives all the properties of the updated items2. The change feed does not include the original items or only the changed properties. The change feed also includes some system-defined properties such as _ts (the last modified timestamp) and _lsn (the logical sequence number)3.
Therefore, the correct answer is:
A: all the properties of the updated items
NEW QUESTION # 33
You have a container named container! in an Azure Cosmos DB for NoSQL account.
You need to provide a user named User1 with the ability to insert items into container1 by using role-based access The solution must use the principle of least privilege.
Which roles should you assign to User1?
- A. DocumentDB Account Contribute only
- B. DocumentDB Account Contributor and Cosmos DB Built-in Data Contributor
- C. Cosmos DB Operator only
- D. Cosmos DB Built-in Data Contributor only
Answer: D
Explanation:
The Cosmos DB Built-in Data Contributor role provides the necessary permissions to insert items into a container in an Azure Cosmos DB for NoSQL account. This role grants the minimum required privileges for the described task, adhering to the principle of least privilege.
NEW QUESTION # 34
You need to configure an Apache Kafka instance to ingest data from an Azure Cosmos DB Core (SQL) API account. The data from a container named telemetry must be added to a Kafka topic named iot. The solution must store the data in a compact binary format.
Which three configuration items should you include in the solution? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. "connector.class": "com.azure.cosmos.kafka.connect.source.CosmosDBSinkConnector"
- B. "connect.cosmos.containers.topicmap": "iot"
- C. "connector.class": "com.azure.cosmos.kafka.connect.source.CosmosDBSourceConnector"
- D. "key.converter": "org.apache.kafka.connect.json.JsonConverter"
- E. "key.converter": "io.confluent.connect.avro.AvroConverter"
- F. "connect.cosmos.containers.topicmap": "iot#telemetry"
Answer: A,E,F
Explanation:
C: Avro is binary format, while JSON is text.
F: Kafka Connect for Azure Cosmos DB is a connector to read from and write data to Azure Cosmos DB. The Azure Cosmos DB sink connector allows you to export data from Apache Kafka topics to an Azure Cosmos DB database. The connector polls data from Kafka to write to containers in the database based on the topics subscription.
D: Create the Azure Cosmos DB sink connector in Kafka Connect. The following JSON body defines config for the sink connector.
Extract:
"connector.class": "com.azure.cosmos.kafka.connect.sink.CosmosDBSinkConnector",
"key.converter": "org.apache.kafka.connect.json.AvroConverter"
"connect.cosmos.containers.topicmap": "hotels#kafka"
Incorrect Answers:
B: JSON is plain text.
Note, full example:
{
"name": "cosmosdb-sink-connector",
"config": {
"connector.class": "com.azure.cosmos.kafka.connect.sink.CosmosDBSinkConnector",
"tasks.max": "1",
"topics": [
"hotels"
],
"value.converter": "org.apache.kafka.connect.json.AvroConverter",
"value.converter.schemas.enable": "false",
"key.converter": "org.apache.kafka.connect.json.AvroConverter",
"key.converter.schemas.enable": "false",
"connect.cosmos.connection.endpoint": "https://<cosmosinstance-name>.documents.azure.com:443/",
"connect.cosmos.master.key": "<cosmosdbprimarykey>",
"connect.cosmos.databasename": "kafkaconnect",
"connect.cosmos.containers.topicmap": "hotels#kafka"
}
}
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/sql/kafka-connector-sink
https://www.confluent.io/blog/kafka-connect-deep-dive-converters-serialization-explained/
NEW QUESTION # 35
You maintain a relational database for a book publisher. The database contains the following tables.
The most common query lists the books for a given authorId.
You need to develop a non-relational data model for Azure Cosmos DB Core (SQL) API that will replace the relational database. The solution must minimize latency and read operation costs.
What should you include in the solution?
- A. Create a container for Author and a container for Book. In each Author document and Book document embed the data from Bookauthorlnk.
- B. Create a container that contains a document for each Author and a document for each Book. In each Book document, embed authorId.
- C. Create Author, Book, and Bookauthorlnk documents in the same container.
- D. Create a container for Author and a container for Book. In each Author document, embed booked for each book by the author. In each Book document embed author of each author.
Answer: D
Explanation:
Store multiple entity types in the same container.
NEW QUESTION # 36
You are implementing an Azure Data Factory data flow that will use an Azure Cosmos DB (SQL API) sink to write a dataset. The data flow will use 2,000 Apache Spark partitions.
You need to ensure that the ingestion from each Spark partition is balanced to optimize throughput.
Which sink setting should you configure?
- A. Write throughput budget
- B. Batch size
- C. Throughput
- D. Collection action
Answer: B
Explanation:
Batch size: An integer that represents how many objects are being written to Cosmos DB collection in each batch. Usually, starting with the default batch size is sufficient. To further tune this value, note:
Cosmos DB limits single request's size to 2MB. The formula is "Request Size = Single Document Size * Batch Size". If you hit error saying "Request size is too large", reduce the batch size value.
The larger the batch size, the better throughput the service can achieve, while make sure you allocate enough RUs to empower your workload.
Reference: https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-cosmos-db
NEW QUESTION # 37
You have an Azure Cosmos DB Core (SQL) API account named storage1 that uses provisioned throughput capacity mode.
The storage1 account contains the databases shown in the following table.
The databases contain the containers shown in the following table.
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:
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/plan-manage-costs
https://azure.microsoft.com/en-us/pricing/details/cosmos-db/
NEW QUESTION # 38
The following is a sample of a document in orders.
The orders container uses customer as the partition key.
You need to provide a report of the total items ordered per month by item type. The solution must meet the following requirements:
Ensure that the report can run as quickly as possible.
Minimize the consumption of request units (RUs).
What should you do?
- A. Configure the report to query orders by using a SQL query through a dedicated gateway.
- B. Configure the report to query orders by using a SQL query.
- C. Configure the report to query a new aggregate container. Populate the aggregates by using SQL queries that run daily.
- D. Configure the report to query a new aggregate container. Populate the aggregates by using the change feed.
Answer: C
Explanation:
You can facilitate aggregate data by using Change Feed and Azure Functions, and then use it for reporting.
NEW QUESTION # 39
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 Synapse 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:
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/sql/changefeed-ecommerce-solution
NEW QUESTION # 40
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