The correct answer is to create a materialized view container with a partition key optimized for the read queries. This works because the materialized view pattern with Cosmos DB change feed allows you to pre-join and reshape data into a separate container, where the partition key is chosen specifically to match the most frequent read patterns—reducing both latency and Request Unit (RU) consumption by avoiding full document scans. On the Microsoft Azure Data Fundamentals DP-900 exam, this scenario tests your understanding of how to decouple write-optimized storage from read-optimized views, a common trap being that increasing RUs or using stored procedures addresses symptoms rather than the root design issue. Remember the memory tip: “Reads need their own key”—if your reads query by customer ID, your materialized view’s partition key should be that customer ID, not the original document’s partition key.
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 company uses Azure Cosmos DB with the MongoDB API for a customer profile service. The service handles 10,000 writes per second and 50,000 reads per second. The data is 1 KB per document. The company needs to reduce read latency for frequently accessed customers and minimize RU consumption. Currently, the service reads the entire document for every request. They decide to implement a materialized view pattern using Azure Cosmos DB change feed and a separate container. Which additional step should they take to optimize read performance and cost?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a materialized view container with a partition key optimized for the read queries.
Using a separate container with a different partition key (option B) allows the materialized view to be optimized for the read pattern, reducing RU cost and latency. Option A (increasing RU) does not address the root cause. Option C (adding TTL) would delete data, not improve reads. Option D (using stored procedures) is for transactional logic, not read optimization.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
Create a materialized view container with a partition key optimized for the read queries.
Why this is correct
Materialized views with optimized partition keys reduce RU consumption and latency for common queries.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
✗
Use stored procedures to aggregate data on read.
Why it's wrong here
Stored procedures run on the server but still process full documents, not optimizing read cost.
✗
Increase the provisioned RU/s on the source container.
Why it's wrong here
Increasing RU only helps with throughput, not with read efficiency for partial data.
✗
Enable Time-to-Live (TTL) on the source container to automatically expire old data.
Why it's wrong here
TTL is for data retention, not for read performance.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-900 question in full detail.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DP-900 NAT questions on configuration and troubleshooting.
Describe considerations for working with non-relational data on Azure — This question tests Describe considerations for working with non-relational data on Azure — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Create a materialized view container with a partition key optimized for the read queries. — Using a separate container with a different partition key (option B) allows the materialized view to be optimized for the read pattern, reducing RU cost and latency. Option A (increasing RU) does not address the root cause. Option C (adding TTL) would delete data, not improve reads. Option D (using stored procedures) is for transactional logic, not read optimization.
What should I do if I get this DP-900 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related DP-900 NAT questions on configuration and troubleshooting.
Are there clue words in this question I should notice?
Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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