Microsoft DP-420 Dumps for Azure Cosmos DB Developer Specialty Exam Success in 2026

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.

Incorrect Answers:

A: Throughput: Set an optional value for the number of RUs you'd like to apply to your CosmosDB collection for each execution of this data flow. Minimum is 400.

B: Write throughput budget: An integer that represents the RUs you want to allocate for this Data Flow write operation, out of the total throughput allocated to the collection.

D: Collection action: Determines whether to recreate the destination collection prior to writing.

None: No action will be done to the collection.

Recreate: The collection will get dropped and recreated

App1 queries the con-product and con-productVendor containers.

Note: Request unit is a performance currency abstracting the system resources such as CPU, IOPS, and memory that are required to perform the database operations supported by Azure Cosmos DB.

Scenario:

Develop an app named App1 that will run from all locations and query the data in account1.

Once multi-region writes are configured, maximize the performance of App1 queries against the data in account1.

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.

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

Azure Cosmos DB supports queries with parameters expressed by the familiar @ notation. Parameterized SQL provides robust handling and escaping of user input, and prevents accidental exposure of data through SQL injection.

For example, you can write a query that takes lastName and address.state as parameters, and execute it for various values of lastName and address.state based on user input.

SELECT *

FROM Families f

WHERE f.lastName = @lastName AND f.address.state = @addressState

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 isB. 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.