Microsoft DP-420日本語 dumps - in .pdf

DP-420日本語 pdf
  • 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)
  • Updated: Aug 18, 2026
  • Q & A: 281 Questions and Answers
  • PDF Price: $69.99
  • Free Demo

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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)
  • Updated: Aug 18, 2026
  • Q & A: 281 Questions and Answers
  • PDF Version + PC Test Engine + Online Test Engine
  • Value Pack Total: $139.98  $89.99
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Microsoft DP-420日本語 dumps - Testing Engine

DP-420日本語 Testing Engine
  • 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)
  • Updated: Aug 18, 2026
  • Q & A: 281 Questions and Answers
  • Software Price: $69.99
  • Testing Engine

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

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

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Microsoft DP-420日本語 Exam Syllabus Topics:

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