Microsoft DP-420日本語 real dump : Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420日本語版)

  • Exam Code: DP-420J
  • Exam Name: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420日本語版)
  • Updated: Aug 09, 2026
  • Q&As: 281 Questions and Answers

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Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/dp-420?WT.mc_id=Azure_blog-wwl

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Exam DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB

Candidates for this exam must have solid knowledge and experience developing apps for Azure and working with Azure Cosmos DB database technologies. They should be proficient at developing applications by using the Core (SQL) API and SDKs, writing efficient queries and creating appropriate index policies, provisioning and managing resources in Azure, and creating server-side objects with JavaScript. They should be able to interpret JSON, read C# or Java code, and use PowerShell.

The English language version of this exam will be updated on August 4, 2022. Please download the skills measured document below to see what’s changing. If a localized version of this exam is available, it will be updated approximately eight weeks after this date.

Passing score: 700. Learn more about exam scores.

Part of the requirements for: Microsoft Certified: Azure Cosmos DB Developer Specialty

Download exam skills outline

Microsoft DP-420日本語 Exam Syllabus Topics:

SectionWeightObjectives
Maintain an Azure Cosmos DB solution25-30%- Monitor and troubleshoot Azure Cosmos DB solutions
  • 1. Implement backup and recovery strategies
  • 2. Troubleshoot throughput issues
  • 3. Monitor performance and availability
  • 4. Monitor metrics and logs
Integrate an Azure Cosmos DB solution5-10%- Implement solutions across services
  • 1. Integrate Azure Functions and Event Hubs
  • 2. Implement Azure AI Search integration
  • 3. Aggregate and archive data
  • 4. Use Change Feed for denormalization
  • 5. Enforce referential integrity
- Enable analytical workloads
  • 1. Query analytical store from Synapse
  • 2. Write data back from Spark
  • 3. Configure Azure Cosmos DB Mirroring
  • 4. Enable analytical store
Design and implement data distribution5-10%- Design and implement multi-region writes
  • 1. Implement conflict resolution policies
  • 2. Choose when to use multi-region writes
  • 3. Implement multi-region writes
- Design and implement replication strategy
  • 1. Choose when to distribute data
  • 2. Perform manual failovers
  • 3. Evaluate consistency model impacts
  • 4. Choose a consistency model
  • 5. Define automatic failover policies
Design and implement data models35-40%- Design and implement a non-relational data model for Azure Cosmos DB for NoSQL
  • 1. Identify partition key, id, and unique keys
  • 2. Store multiple related entities in the same document
  • 3. Store multiple entity types in the same container
  • 4. Denormalize data across documents
  • 5. Identify data and associated access patterns
  • 6. Reference between documents
- Implement server-side programming
  • 1. Implement user-defined functions
  • 2. Write and deploy stored procedures
  • 3. Implement triggers
- Implement client connectivity options
  • 1. Configure client-side threading and logging
  • 2. Implement singleton client
  • 3. Choose gateway or direct connectivity mode
  • 4. Handle connection errors
  • 5. Create database connections
  • 6. Use Azure Cosmos DB emulator
- Design a data partitioning strategy
  • 1. Evaluate throughput and data distribution
  • 2. Implement synthetic partition keys
  • 3. Choose a partitioning strategy
  • 4. Choose a partition key
  • 5. Plan for transactions with partition keys
  • 6. Evaluate cross-partition query cost
- Plan and implement sizing and scaling
  • 1. Evaluate global distribution costs
  • 2. Choose between serverless, provisioned, and free tier
  • 3. Evaluate throughput and storage requirements
  • 4. Design resource governance and scaling
  • 5. Configure throughput
- Implement data access
  • 1. Implement optimistic concurrency control
  • 2. Implement SQL queries with arrays and aggregation
  • 3. Implement patch operations
  • 4. Use consistency and query request options
  • 5. Use SDKs for CRUD operations
  • 6. Manage transactional batch operations
Optimize an Azure Cosmos DB solution15-20%- Design and implement change feeds
  • 1. Consume change feeds using SDK
  • 2. Develop Azure Functions triggers
  • 3. Implement aggregation persistence
  • 4. Manage change feed instances
- Optimize query performance
  • 1. Retrieve request unit cost
  • 2. Implement integrated cache
  • 3. Adjust indexing policies
  • 4. Calculate query cost
- Define and implement indexing strategy
  • 1. Choose read-heavy or write-heavy indexing
  • 2. Implement composite indexes
  • 3. Configure custom indexing policies
  • 4. Choose appropriate index types
  • 5. Optimize index performance

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