Microsoft · DP-420
Microsoft Certified: Azure Cosmos DB Developer Specialty (DP-420) Practice Tests
Write efficient queries, create indexing policies, manage, and provision resources in the SQL API and SDK with Microsoft Azure Cosmos DB.
Exam Details
Practice Questions
677
≈ 13 practice exams
Duration
100 minutes
Passing Score
700/1000
Difficulty
SpecialtyLast Updated
Jan 2025
Topics Covered
Design and implement data modelsDesign and implement data distributionIntegrate an Azure Cosmos DB solutionOptimize an Azure Cosmos DB solutionMaintain an Azure Cosmos DB solution
Microsoft Certified: Azure Cosmos DB Developer Specialty (DP-420) Practice Exam Preparation
Use this DP-420 practice exam to prepare for Microsoft Certified: Azure Cosmos DB Developer Specialty (DP-420) with realistic questions, detailed explanations, and focused study modes. The practice bank includes 677 questions for Microsoft DP-420, so you can review the exam steadily instead of relying on one long cram session.
As you practice, pay extra attention to recurring topics such as Design and implement data models, Design and implement data distribution, Integrate an Azure Cosmos DB solution, Optimize an Azure Cosmos DB solution, and Maintain an Azure Cosmos DB solution. Start with short sessions to identify weak areas, then move into timed quizzes once your accuracy is consistent.
The explanations are especially useful when you want to connect exam wording to the responsibilities and scenarios described in the official certification guidance. Use the free preview first, then unlock the full question bank when you are ready to build a complete study routine.
Exam Domain Breakdown
Design and implement data models38%
Design and implement data distribution8%
Integrate an Azure Cosmos DB solution8%
Optimize an Azure Cosmos DB solution18%
Maintain an Azure Cosmos DB solution28%
Exam Overview
The Microsoft Certified: Azure Cosmos DB Developer Specialty (DP-420) validates subject matter expertise in designing, implementing, and monitoring cloud-native applications that store and manage data using Azure Cosmos DB. The certification covers the full development lifecycle: modeling non-relational data, selecting partition keys, managing throughput and scaling, implementing the SQL API and .NET/Java SDKs, writing server-side JavaScript (stored procedures, triggers, user-defined functions), and integrating Cosmos DB with other Azure services such as Azure Functions, Azure Synapse Link, and Event Hubs.
The exam was last updated on January 27, 2025, and reflects current platform capabilities including hierarchical partition keys, the integrated cache, Always Encrypted, and Azure Synapse Link with Change Data Capture. Candidates are assessed on their ability to optimize query performance through indexing strategies and cost analysis, implement change feeds, configure backup and restore, enforce security controls using Microsoft Entra ID and Azure RBAC, and automate operations using Azure Resource Manager templates and PowerShell/CLI.
Who Should Take This Exam
This certification is intended for developers and data engineers with hands-on experience building Azure applications that rely on Azure Cosmos DB for NoSQL as their primary data store. Suitable job titles include Azure Developer, Cloud Application Developer, and Data Engineer. Candidates typically have two or more years of experience working with Azure services and are comfortable reading C# or Java application code, writing SQL queries for the Cosmos DB NoSQL API, and interpreting JSON documents.
Professionals pursuing this certification often work in roles where they are responsible for both the data modeling decisions and the operational health of a Cosmos DB solution—including security, availability, resilience, and performance. It is particularly relevant for those building globally distributed, high-throughput applications such as IoT platforms, e-commerce systems, and real-time analytics pipelines.
Prerequisites
Microsoft does not enforce formal prerequisites for DP-420, but candidates are expected to have practical experience developing applications for Azure and working with Azure Cosmos DB database technologies. Specifically, candidates should be proficient with the Azure Cosmos DB for NoSQL API, able to write efficient SQL queries against it, create and tune indexing policies, and use the Azure Cosmos DB SDK (C# or Java). Familiarity with JSON structure and the ability to write server-side JavaScript for stored procedures and triggers is also required.
A solid understanding of Azure fundamentals—including resource provisioning, Azure role-based access control (RBAC), Azure Monitor, and ARM templates—is strongly recommended. Candidates who have completed the AZ-900 (Azure Fundamentals) or AZ-204 (Azure Developer Associate) certification will find much of this background knowledge directly applicable. Microsoft's free learning path DP-420T00 (Design and Implement Cloud-Native Applications with Azure Cosmos DB) is the official preparatory course.
Exam Format
Exam DP-420 is a proctored assessment delivered through Pearson VUE, available both online (remote proctored) and at Pearson VUE test centers. Candidates are given 100 minutes to complete the exam. The number of questions is not publicly disclosed and may vary, but the exam may include multiple question types such as multiple choice, drag-and-drop, build-list, case studies, and interactive lab components. A score of 700 or higher on a scale of 100–1000 is required to pass.
The exam is available in English, Japanese, Chinese (Simplified), Chinese (Traditional), Korean, German, French, Spanish, Portuguese (Brazil), and Italian. If taking the exam in a non-English localization, candidates may request an additional 30 minutes. The certification expires annually and can be renewed at no cost by passing a free online assessment on Microsoft Learn. The exam price is approximately $165 USD, varying by country or region of the testing location.
Skills Measured
- 1.Design and implement data models (35–40%): Covers non-relational data modeling for the NoSQL API including multi-entity containers, document denormalization, reference patterns, TTL configuration, document versioning, and schema versioning. Also includes partitioning strategy selection, synthetic and hierarchical partition keys, throughput sizing (serverless vs. provisioned), SDK client connectivity (gateway vs. direct mode), SQL query implementation (arrays, aggregation, subqueries, functions), SDK CRUD and patch operations, transactional batch, optimistic concurrency with ETags, session consistency, pagination, and server-side JavaScript (stored procedures, triggers, UDFs).
- 2.Design and implement data distribution (5–10%): Covers global replication strategy including automatic and manual failover policies, consistency model selection (strong, bounded staleness, session, consistent prefix, eventual) and their trade-offs in latency, availability, and RU cost. Also includes multi-region write configuration and custom conflict resolution policies for the NoSQL API.
- 3.Integrate an Azure Cosmos DB solution (5–10%): Covers enabling and querying Azure Synapse Link for analytical workloads, choosing between Synapse Link and the Spark Connector, implementing custom partitioning in Synapse Link, Change Data Capture in the analytical store, and time travel. Also includes integration patterns using Azure Functions with Change Feed for denormalization, referential integrity, aggregation, and archiving, as well as Azure AI Search integration and Event Hubs eventing.
- 4.Optimize an Azure Cosmos DB solution (15–20%): Covers query performance tuning through index adjustments, RU cost calculation for queries and point operations, use of the Azure Cosmos DB integrated cache, change feed processing via Azure Functions triggers and SDK consumers, change feed estimator for scaling, and defining indexing strategies (read-heavy vs. write-heavy, composite indexes, custom indexing policies).
- 5.Maintain an Azure Cosmos DB solution (25–30%): Covers monitoring with Azure Monitor (normalized RU usage, server-side latency, partition distribution, replication metrics), configuring alerts and diagnostic logs, implementing periodic and continuous backup, point-in-time recovery, and security controls including network access, encryption (service-managed and customer-managed keys, Always Encrypted), Microsoft Entra ID data plane access, Azure RBAC for control plane, CORS, Key Vault key management. Also includes data movement strategies (SDK bulk, Azure Data Factory, Kafka connector, Stream Analytics, Spark Connector, IoT Hub) and DevOps automation with ARM templates and PowerShell/CLI.
Study Tips
- Use the official Microsoft Learn learning path DP-420T00 (Design and Implement Cloud-Native Applications with Azure Cosmos DB) as your primary study resource—it maps directly to exam domains and includes hands-on sandbox exercises for SDK operations, indexing, and partitioning.
- Take the free official Practice Assessment on Microsoft Learn (Assessment ID 104) multiple times. It mirrors the style and difficulty of real exam questions and provides explanations that link back to documentation—use it to identify weak domains before exam day.
- Set up a free-tier Azure Cosmos DB account and the Azure Cosmos DB Emulator for offline development. Practice writing NoSQL API queries, configuring composite indexes via the Data Explorer, implementing stored procedures in JavaScript, and using the .NET or Java SDK to perform batch and patch operations.
- Focus significant study time on partitioning and indexing—together these two sub-domains underpin both the Design and implement data models domain (35–40%) and the Optimize domain (15–20%). Work through partition key selection scenarios, calculate RU costs for cross-partition queries, and experiment with custom indexing policies to understand read/write trade-offs.
- Study consistency models in depth: understand the five levels (strong, bounded staleness, session, consistent prefix, eventual), their RU cost implications, latency characteristics, and when to override the account-level consistency at the per-request level using SDK request options.
- Review the Maintain domain (25–30%) carefully—it is the second-largest domain. Practice configuring Azure Monitor diagnostic settings, setting up alerts for 429 (rate-limited) requests, and walking through both periodic and continuous backup/restore workflows in the Azure portal.
- Consult the official DP-420 Study Guide on Microsoft Learn (aka.ms/dp420-StudyGuide) to review the full list of objectives as of January 27, 2025. Pay particular attention to recently added topics such as Always Encrypted, hierarchical partition keys, and Synapse Link Change Data Capture, which reflect the latest exam update.
Career Benefits
Earning the Azure Cosmos DB Developer Specialty positions professionals for roles such as Senior Azure Developer, Cloud-Native Application Architect, and Data Platform Engineer—positions that command premium salaries due to the specialized nature of globally distributed database design. According to industry surveys, Azure-certified developers with specialty credentials typically earn between $120,000 and $165,000 USD annually in North American markets, with variation by region and total experience. Demand for Cosmos DB expertise is driven by enterprises building IoT, gaming, retail, and financial services applications that require low-latency, multi-region access at scale.
Compared to the broader AZ-204 (Azure Developer Associate), DP-420 demonstrates deep, focused expertise in a specific high-value technology—making it particularly compelling on a resume for organizations heavily invested in the Azure data platform. The certification is recognized globally and renewable annually at no cost, ensuring that credential holders remain current with platform evolution. It also pairs well with certifications such as DP-203 (Azure Data Engineer Associate) for professionals who straddle application development and data engineering responsibilities.
Sample Questions
5 sample questions with answers and explanations. The full bank has 677 questions, enough for 13 full-length practice exams.
Preview — answers shown1. TechStartup Solutions needs to calculate and evaluate throughput distribution for their social media platform. They have posts, comments, likes, and shares partitioned by user ID. Analysis shows that 5% of users (influencers) generate 40% of content and receive 70% of interactions. Regular users generate 60% of content with 30% of interactions. How should they evaluate throughput distribution based on their current partition key selection?
AThe distribution is balanced since all users have equal partition allocation regardless of their activity patterns
BThroughput distribution is severely skewed with influencer partitions consuming disproportionate RUs compared to regular user partitions
CThe current partitioning provides optimal distribution for read operations even if write operations are uneven
DThroughput skew is acceptable since it reflects natural usage patterns and can be managed with autoscaling
Explanation
Throughput distribution is severely skewed because influencer partitions handle both high content generation and massive interaction volumes, consuming far more RUs than regular user partitions. This creates hot partitions that may experience throttling while other partitions are underutilized. Equal partition allocation doesn't translate to balanced throughput when user activity varies dramatically. While autoscaling can help, it doesn't solve the fundamental hot partition problem. The skew affects both reads and writes since influencer content receives disproportionate interaction activity, making the distribution suboptimal for all operations.
2. ThroughputMonitor Solutions has an Azure Cosmos DB for NoSQL account with a container named ActivityData that processes high-volume IoT writes. They want to configure diagnostic settings to identify hot partitions affecting performance. Which diagnostic log table provides the information needed to identify hot partitions?
AQueryRuntimeStatistics for query performance analysis
BControlPlaneRequests for account management operations
CPartitionKeyRUConsumption for RU usage per partition
DPartitionKeyStatistics for storage distribution metrics
Explanation
PartitionKeyRUConsumption is the diagnostic log table specifically designed for identifying hot partitions by tracking RU consumption per partition key on a per-second basis. This table aggregates throughput usage across logical partitions, making it easy to identify which partitions are consuming disproportionate amounts of RUs and causing throttling issues. QueryRuntimeStatistics focuses on individual query performance metrics rather than partition-level resource consumption. ControlPlaneRequests logs account-level management operations like region additions but doesn't track data-plane partition usage. PartitionKeyStatistics shows storage size distribution across partitions but doesn't indicate RU consumption patterns that identify hot partitions.
3. ProcessInnovation Corp has an Azure Function with Cosmos DB input binding that sometimes receives null items when the requested item doesn't exist. They want to handle missing items gracefully without causing function failures. Which approach provides robust null item handling?
AUse item?.PropertyName syntax for safe property access on potentially null items
BUse try-catch blocks around item property access to handle null references
Cif (item != null) { // process item } else { // handle missing item }
DConfigure the input binding with required: false to make the item optional
Explanation
Simple null checking with if (item != null) provides the most straightforward and reliable approach for handling potentially missing items from input bindings. Point read input bindings return null when the specified item doesn't exist, so explicit null checks allow the function to handle missing items gracefully and implement appropriate business logic.
4. At ProcessOptimal Industries, the team wants to understand the precision-based conflict resolution in indexing policies. They have an included path /product/* and an excluded path /product/images/thumbnails/?. Which path takes precedence and why?
ABoth paths cancel each other out and default indexing is used
BThe paths merge to create a combined indexing rule for the product object
CThe excluded path /product/images/thumbnails/? takes precedence because it is more specific
DThe included path /product/* takes precedence because it was specified first
Explanation
The excluded path /product/images/thumbnails/? takes precedence because it is more specific than the included path /product/*. Azure Cosmos DB resolves conflicts by giving precedence to the path with the most precision. This means all properties under product are indexed except for the specific thumbnails property, which is excluded.
5. DataIndex Solutions has Azure Cosmos DB for NoSQL account index_account with database content_db and container documents_store, plus Azure AI Search service content_search for indexing document data. They need to ensure that deleted documents from documents_store are automatically removed from the search index. What should they implement?
ASoft delete functionality in the documents_store container
BChange feed monitoring for deletion events
CTTL-based automatic cleanup policies
DUser-defined functions (UDFs) to track deletions
Explanation
Soft delete is the required approach for tracking document deletions in Azure AI Search indexers. When a document is soft deleted (marked as deleted rather than physically removed), the indexer can detect this state change and remove the corresponding entry from the search index. Azure AI Search specifically supports soft delete detection policies that monitor for deleted documents using a designated field and value combination. UDFs operate during query execution and can't track or communicate deletion events to external services. Change feed monitoring requires custom application logic and doesn't automatically update search indexes. TTL-based cleanup physically removes documents without providing deletion tracking that search indexers can detect.
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