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

  • 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 07, 2026     Q & A: 281 Questions and Answers

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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

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

Microsoft DP-420日本語 Exam Syllabus Topics:

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

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