DP-420日本語 exam dumps

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  • Exam Code: DP-420日本語
  • Exam Name: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420日本語版)
  • No. of Questions: 281 Questions and Answers
  • Updated: Aug 05, 2026

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Microsoft DP-420 certification exam is a great way for professionals to demonstrate their expertise in designing and implementing cloud-native applications using Cosmos DB. Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420日本語版) certification is recognized globally and can help professionals stand out in the competitive job market. By passing this certification exam, professionals can demonstrate their skills and knowledge related to designing and implementing cloud-native applications using Cosmos DB, and can increase their chances of getting hired for high-paying jobs in the field of cloud computing.

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Microsoft DP-420 exam, also known as Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB, is an advanced-level certification exam that tests your knowledge of designing and implementing cloud-native applications using Azure Cosmos DB. DP-420J exam is intended for professionals who want to validate their expertise in developing cloud-based applications using Azure Cosmos DB.

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

The DP-420 certification exam covers a range of topics related to the design and implementation of cloud-native applications using Azure Cosmos DB. These topics include data modeling, partitioning, indexing, querying, and managing data at scale. DP-420J exam also covers topics related to the use of Azure Cosmos DB in cloud-native architectures, including the use of Azure Functions, Azure Event Grid, and Azure Service Bus.

Microsoft DP-420日本語 Exam Syllabus Topics:

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

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