Question 122 of 982

Describe considerations for working with non-relational data on Azure →mediumMultiple ChoiceObjective-mapped

Quick Answer

The answer is to increase the provisioned throughput, measured in Request Units per second (RU/s). This is correct because Azure Cosmos DB allocates processing capacity based on the provisioned RU/s; raising this value directly gives the container more resources to handle concurrent read and query operations, preventing throttling and reducing latency during peak demand. On the Microsoft Azure Data Fundamentals DP-900 exam, this scenario tests your understanding of how throughput scaling directly impacts performance for read-heavy workloads, often appearing as a distractor against options like adding indexes or changing consistency levels—both of which are less immediate fixes for high-throughput degradation. A common trap is to assume indexing alone solves performance issues, but for high-volume reads, RU/s is the primary lever. Memory tip: think of RU/s as the "engine size" of your container—more RU/s means more power to process requests without stalling.

DP-900 Practice Question: Describe considerations for working with non-relational data on Azure

This DP-900 practice question tests your understanding of describe considerations for working with non-relational data on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.

A global social media startup stores user profiles as JSON documents in Azure Cosmos DB. Their application frequently reads profiles by user ID and also runs queries to find users based on location or interests. The workload is read-heavy with high throughput requirements. The operations team notices that query performance degrades during peak hours. Which action would most effectively improve query performance?

Question 1mediummultiple choice

Full question →

A
Increase the number of containers
Why wrong: Incorrect. Adding more containers (collections/tables) without changing throughput doesn't increase overall capacity; it might fragment data.
B
Choose a different API (e.g., switch from SQL API to MongoDB API)
Why wrong: Incorrect. The API affects the query language and data model, but does not directly improve throughput availability.
C
Increase the provisioned throughput (RU/s)
Correct. Provisioned throughput is the key resource controlling the number of operations per second. Increasing RU/s provides more computational power for queries.
D
Switch to a different Azure region
Why wrong: Incorrect. Changing the region might reduce network latency but does not increase the provisioned throughput allocated to the database.

Full breakdown with real-world context →

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

✓

Increase the provisioned throughput (RU/s)

Increasing the provisioned throughput (RU/s) directly allocates more processing capacity to the Cosmos DB container, allowing it to handle higher request volumes and reduce throttling during peak hours. Since the workload is read-heavy and query performance degrades under high throughput demands, raising RU/s is the most effective and immediate action to improve performance.

Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Increase the number of containers
Why it's wrong here
Incorrect. Adding more containers (collections/tables) without changing throughput doesn't increase overall capacity; it might fragment data.
✗
Choose a different API (e.g., switch from SQL API to MongoDB API)
Why it's wrong here
Incorrect. The API affects the query language and data model, but does not directly improve throughput availability.
✓
Increase the provisioned throughput (RU/s)
Why this is correct
Correct. Provisioned throughput is the key resource controlling the number of operations per second. Increasing RU/s provides more computational power for queries.
Related concept
Read the scenario before looking for a memorised answer.
✗
Switch to a different Azure region
Why it's wrong here
Incorrect. Changing the region might reduce network latency but does not increase the provisioned throughput allocated to the database.

Common exam traps

Common exam trap: answer the scenario, not the keyword

The trap here is that candidates may confuse throughput (RU/s) with other scaling mechanisms like partitioning or API choice, but the core issue in a read-heavy, high-throughput scenario is insufficient provisioned capacity, not data organization or protocol differences.

Detailed technical explanation

How to think about this question

Cosmos DB allocates throughput in Request Units (RU) per second, which covers CPU, memory, and IOPS for operations. When provisioned RU/s is exceeded, the service returns HTTP 429 (rate-limiting) responses, causing retries and degraded performance. For read-heavy workloads, enabling indexing policies optimized for common queries (e.g., composite indexes for location or interests) can further reduce RU consumption per query, but increasing RU/s is the direct solution to handle peak-hour demand.

KKey Concepts to Remember

Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.

TExam Day Tips

Watch for words such as best, first, most likely and least administrative effort.
Review why wrong options are wrong, not only why the correct option is correct.

Key takeaway

Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.

Real-world example

How this comes up in practice

A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.

What to study next

Got this wrong? Here's your next step.

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

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FAQ

Questions learners often ask

What does this DP-900 question test?

Describe considerations for working with non-relational data on Azure — This question tests Describe considerations for working with non-relational data on Azure — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Increase the provisioned throughput (RU/s) — Increasing the provisioned throughput (RU/s) directly allocates more processing capacity to the Cosmos DB container, allowing it to handle higher request volumes and reduce throttling during peak hours. Since the workload is read-heavy and query performance degrades under high throughput demands, raising RU/s is the most effective and immediate action to improve performance.

What should I do if I get this DP-900 question wrong?

Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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