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Microsoft DP-420 Korean Braindumps - in .pdf Free Demo

  • Exam Code: DP-420-KR
  • Exam Name: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420 Korean Version)
  • Last Updated: Aug 20, 2026
  • Q & A: 281 Questions and Answers
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  • Exam Code: DP-420-KR
  • Exam Name: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420 Korean Version)
  • Last Updated: Aug 20, 2026
  • Q & A: 281 Questions and Answers
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Skills measured

  • Integrate an Azure Cosmos DB solution (5–10%)
  • Optimize an Azure Cosmos DB solution (15–20%)
  • The English language version of this exam will be updated on August 4, 2022. Please download the exam skills outline below to see what’s changing.
  • Maintain an Azure Cosmos DB solution (25–30%)
  • Design and implement data distribution (5–10%)
  • Design and implement data models (35–40%)

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

Hit the link below, to know more about the Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (beta)

Official link of the Microsoft DP-420 Certification Exam

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You can also use DP-420 Dumps. It will help you to get a clear idea about your preparation. You should also take a mock test periodically. You should also compare your performance with other candidates. It will help you to get a clear idea about your preparation. In the end, you should practice the DP-420 Certification Exam by using the practice test software. It will help you to get a clear idea about your preparation. You should also practice the questions and answers of the DP-420 Certification Exam. You should try to solve the questions as soon as you finish reading the question.

Microsoft DP-420 Korean Exam Syllabus Topics:

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

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