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Microsoft DP-420 Exam Syllabus Topics:

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

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB 認定 DP-420 試験問題 (Q201-Q206):

質問 # 201
You have a database in an Azure Cosmos DB SQL API Core (SQL) account that is used for development.
The database is modified once per day in a batch process.
You need to ensure that you can restore the database if the last batch process fails. The solution must minimize costs.
How should you configure the backup settings? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解：

解説：


質問 # 202
You are troubleshooting the current issues caused by the application updates.
Which action can address the application updates issue without affecting the functionality of the application?

正解：A

解説：
Explanation
Bounded staleness is frequently chosen by globally distributed applications that expect low write latencies but require total global order guarantee. Bounded staleness is great for applications featuring group collaboration and sharing, stock ticker, publish-subscribe/queueing etc.
Scenario: Application updates in con-product frequently cause HTTP status code 429 "Too many requests".
You discover that the 429 status code relates to excessive request unit (RU) consumption during the updates.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels


質問 # 203
You have a container in an Azure Cosmos DB Core (SQL) API account.
You need to use the Azure Cosmos DB SDK to replace a document by using optimistic concurrency.
What should you include in the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解：

解説：

Explanation:

Box 1: ConsistencyLevel
The ItemRequestOptions Class ConsistencyLevel property gets or sets the consistency level required for the request in the Azure Cosmos DB service.
Azure Cosmos DB offers 5 different consistency levels. Strong, Bounded Staleness, Session, Consistent Prefix and Eventual - in order of strongest to weakest consistency.
Box 2: _etag
The ItemRequestOptions class helped us implement optimistic concurrency by specifying that we wanted the SDK to use the If-Match header to allow the server to decide whether a resource should be updated. The If- Match value is the ETag value to be checked against. If the ETag value matches the server ETag value, the resource is updated.
Reference:
https://docs.microsoft.com/en-us/dotnet/api/microsoft.azure.cosmos.itemrequestoptions
https://cosmosdb.github.io/labs/dotnet/labs/10-concurrency-control.html


質問 # 204
You have an Azure Cosmos DB Core (SQL) API account named account1 that has the disableKeyBasedMetadataWriteAccess property enabled.
You are developing an app named App1 that will be used by a user named DevUser1 to create containers in account1. DevUser1 has a non-privileged user account in the Azure Active Directory (Azure AD) tenant.
You need to ensure that DevUser1 can use App1 to create containers in account1.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

正解：

解説：

Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/secure-access-to-data
https://docs.microsoft.com/en-us/rest/api/resources/


質問 # 205
You have an application named App1 that reads the data in an Azure Cosmos DB Core (SQL) API account.
App1 runs the same read queries every minute. The default consistency level for the account is set to eventual.
You discover that every query consumes request units (RUs) instead of using the cache.
You verify the IntegratedCacheiteItemHitRate metric and the IntegratedCacheQueryHitRate metric. Both metrics have values of 0.
You verify that the dedicated gateway cluster is provisioned and used in the connection string.
You need to ensure that App1 uses the Azure Cosmos DB integrated cache.
What should you configure?

正解：C

解説：
Because the integrated cache is specific to your Azure Cosmos DB account and requires significant CPU and memory, it requires a dedicated gateway node. Connect to Azure Cosmos DB using gateway mode.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/integrated-cache-faq


質問 # 206
......

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