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: Sep 16, 2026
  • Q&As: 281 Questions and Answers

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DP-420日本語 exam dumps

Following is the info about the Passing Score, Duration & Questions for the Microsoft DP-420 Exam

Information about the Passing Score, Duration & Questions for the Microsoft DP-420 Exam is given in the DP-420 Dumps. The overview of that info is as given below:

  • Time Duration: 60 minutes
  • Number of Questions: 40-60
  • Languages: English
  • The passing scores: 70%

What are the prerequisites to take the Microsoft DP-420 Certification Exam?

There are no prerequisites for the Microsoft DP-420 Certification Exam.

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

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What is the Microsoft DP-420 Certification Exam and why it is created?

DP-420 Certification Exam is also known as Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (beta). DP-420 Certification Exam is authorized by Microsoft and is an IT professional certification exam that is designed to test the knowledge and skills of the candidates for designing and implementing cloud-native applications using Microsoft Azure Cosmos DB database technologies. This certification exam is a part of the Microsoft IT Professional certification program and is the final certification exam for Azure SQL Database Administration. DP-420 Dumps is the most reliable and easiest way to pass the DP-420 exam.

Microsoft DP-420日本語 Exam Syllabus Topics:

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

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