Try 12 Microsoft Azure Cosmos DB Developer Specialty (DP-420) sample questions and practice-test preview prompts on data modeling, partitioning, consistency, performance, integration, security, and application-design scope.
DP-420 is Microsoft Certified: Azure Cosmos DB Developer Specialty. It focuses on designing, implementing, optimizing, and maintaining cloud-native applications that use Azure Cosmos DB.
IT Mastery coverage for DP-420 is under review. Use this page to try 12 original sample questions, review the exam snapshot, route fit, and closest live Azure practice paths.
Practice option: Sample questions available
Start with the 12 sample questions on this page. Dedicated practice for DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB is not currently included as a full web-app practice page; enter your email to get updates when full practice becomes available or expands for this exam.
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| Area | What to review |
|---|---|
| Data models | modeling, partition keys, distribution, and document design |
| Data distribution | throughput, consistency, global distribution, and scale trade-offs |
| Integration | SDK use, Azure service integration, app patterns, and security |
| Optimization | indexing, query efficiency, performance, and cost behavior |
| Maintenance | monitoring, backup, restore, troubleshooting, and lifecycle operations |
Try these 12 original sample questions for Microsoft DP-420. They are designed for self-assessment and are not official exam questions.
Topic: partition-key choice
A Cosmos DB container stores orders for many tenants. Queries almost always filter by tenant and order date. What should the developer consider first?
Best answer: A
Explanation: Partition-key choice affects scale, performance, and query efficiency. A good key distributes workload and aligns with common access patterns.
What this tests: Designing a Cosmos DB partition strategy.
Topic: consistency level
A global app needs low-latency reads but can tolerate slightly stale data for product catalog browsing. Which design choice should be reviewed?
Best answer: B
Explanation: Cosmos DB consistency levels let designers balance latency, availability, and freshness. Product catalog reads may not require the strongest consistency.
What this tests: Matching consistency to application requirements.
Topic: request units
A query scans many partitions and consumes high request units. What is the best improvement direction?
Best answer: C
Explanation: RU consumption reflects work done by Cosmos DB. Query shape, partitioning, and indexing can materially affect performance and cost.
What this tests: Optimizing query efficiency and RU cost.
Topic: data modeling
An app often reads a customer profile and the customer’s active preferences together. What is a Cosmos DB modeling consideration?
Best answer: D
Explanation: Cosmos DB data modeling is workload-driven. Embedding or denormalizing can be appropriate when it supports common reads and bounded updates.
What this tests: Modeling documents for access patterns.
Topic: indexing policy
A container has heavy writes and only a few query paths. What might improve performance and cost?
Best answer: A
Explanation: Cosmos DB indexing policy affects write cost and query performance. Unnecessary indexing can increase RU usage.
What this tests: Tuning indexing policy for workload needs.
Topic: change feed
A system must react whenever new documents are written to a container and update a search index. Which Cosmos DB feature is a likely fit?
Best answer: B
Explanation: The change feed supports event-driven processing of inserts and updates. It is commonly used to trigger downstream actions.
What this tests: Applying change feed patterns.
Topic: global distribution
A read-heavy app serves users in North America and Europe. Latency is high for European users. What should the architect evaluate?
Best answer: C
Explanation: Cosmos DB global distribution can place data closer to users and improve read latency. The design must still consider consistency and failover.
What this tests: Using global distribution for latency requirements.
Topic: SDK error handling
An application occasionally receives throttling responses from Cosmos DB. What should the developer implement?
Best answer: D
Explanation: Throttling should be handled with appropriate retry behavior and workload tuning. Hot partitions and RU limits must be investigated.
What this tests: Handling Cosmos DB throttling in applications.
Topic: security
A service needs to access Cosmos DB without putting keys in code. What should the team prefer where supported?
Best answer: A
Explanation: Secure application design avoids embedded secrets and limits access. Identity-based access patterns are preferred when available.
What this tests: Securing Cosmos DB access.
Topic: backup and restore
A business requirement asks for recovery after accidental document deletion. What should be reviewed?
Best answer: B
Explanation: Recovery capability depends on configured backup and restore behavior. The requirement should be mapped to a tested recovery plan.
What this tests: Planning Cosmos DB data recovery.
Topic: container granularity
A team wants to put unrelated entities with different scale and access patterns into one container. What should they consider?
Best answer: C
Explanation: Container design affects partitioning, indexing, and throughput management. Unrelated access patterns can create inefficient or risky designs.
What this tests: Evaluating container boundaries.
Topic: operational monitoring
Which metric set is most useful for Cosmos DB operations?
Best answer: D
Explanation: Cosmos DB monitoring should expose performance, cost, availability, and query-health signals. These guide both operations and design tuning.
What this tests: Selecting relevant Cosmos DB monitoring signals.
Use this map to connect the sample questions to the decision pattern Microsoft usually tests for this route.
flowchart LR
S1["Model access patterns"] --> S2
S2["Choose partition key"] --> S3
S3["Set consistency and throughput"] --> S4
S4["Design indexing and queries"] --> S5
S5["Secure application access"] --> S6
S6["Monitor cost and latency"]
| Cue | What to remember |
|---|---|
| Modeling | Start from read and write access patterns, not from relational normalization habits. |
| Partitioning | Choose a partition key that spreads load and supports common queries. |
| Consistency | Balance correctness, latency, and availability with the right consistency level. |
| Throughput | Estimate request units, hot partitions, indexing cost, and autoscale needs. |
| Security | Use identity, keys, network controls, and data protection intentionally. |
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