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Microsoft DP-420 Exam Syllabus Topics:

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

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q204-Q209):

NEW QUESTION # 204
You have an Azure Cosmos DB for NoSQL account named account1 that has a single read-write region and one additional read region. Account1 uses the strong default consistency level.
You have an application that uses the eventual consistency level when submitting requests to account1.
How will writes from the application be handled?

Answer: A


NEW QUESTION # 205
You plan to deploy two Azure Cosmos DB Core (SQL) API accounts that will each contain a single database. The accounts will be configured as shown in the following table.

How should you provision the containers within each account to minimize costs? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/serverless
https://docs.microsoft.com/en-us/azure/cosmos-db/provision-throughput-autoscale#use-cases-of-autoscale


NEW QUESTION # 206
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.

Answer:

Explanation:

Explanation:

Box 1: Resource tokens
Resource tokens provide access to the application resources within a database. Resource tokens:
Provide access to specific containers, partition keys, documents, attachments, stored procedures, triggers, and UDFs.
Box 2: Azure Resource Manager API
You can use Azure Resource Manager to help deploy and manage your Azure Cosmos DB accounts, databases, and containers.
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/secure-access-to-data
https://docs.microsoft.com/en-us/rest/api/resources/


NEW QUESTION # 207
You have an application that queries an Azure Cosmos DB for NoSQL account.
You discover that the following two queries run frequently.

You need to minimize the request units (RUs) consumed by reads and writes.
What should you create?

Answer: C

Explanation:
You should customize your indexing policy so you can serve all necessary ORDER BY queries.
ORDER BY queries on multiple properties:
The following considerations are used when using composite indexes for queries with an ORDER BY clause with two or more properties:
* The composite index also supports an ORDER BY clause with the opposite order on all paths.
* If the composite index paths do not match the sequence of the properties in the ORDER BY clause, then the composite index can't support the query.
* The order of composite index paths (ascending or descending) should also match the order in the ORDER BY clause.
Consider the following example where a composite index is defined on properties name, age, and
_ts:

Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/index-overview


NEW QUESTION # 208
You need to configure an Apache Kafka instance to ingest data from an Azure Cosmos DB Core (SQL) API account. The data from a container named telemetry must be added to a Kafka topic named iot. The solution must store the data in a compact binary format.
Which three configuration items should you include in the solution? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer: B,D,F

Explanation:
C: Avro is binary format, while JSON is text.
F: Kafka Connect for Azure Cosmos DB is a connector to read from and write data to Azure Cosmos DB. The Azure Cosmos DB sink connector allows you to export data from Apache Kafka topics to an Azure Cosmos DB database. The connector polls data from Kafka to write to containers in the database based on the topics subscription.
D: Create the Azure Cosmos DB sink connector in Kafka Connect. The following JSON body defines config for the sink connector.
Extract:
"connector.class": "com.azure.cosmos.kafka.connect.sink.CosmosDBSinkConnector",
"key.converter": "org.apache.kafka.connect.json.AvroConverter"
"connect.cosmos.containers.topicmap": "hotels#kafka"
Incorrect Answers:
B: JSON is plain text.
Note, full example:
{
"name": "cosmosdb-sink-connector",
"config": {
"connector.class": "com.azure.cosmos.kafka.connect.sink.CosmosDBSinkConnector",
"tasks.max": "1",
"topics": [
"hotels"
],
"value.converter": "org.apache.kafka.connect.json.AvroConverter",
"value.converter.schemas.enable": "false",
"key.converter": "org.apache.kafka.connect.json.AvroConverter",
"key.converter.schemas.enable": "false",
"connect.cosmos.connection.endpoint": "https://<cosmosinstance-name>.documents.azure.com:443/",
"connect.cosmos.master.key": "<cosmosdbprimarykey>",
"connect.cosmos.databasename": "kafkaconnect",
"connect.cosmos.containers.topicmap": "hotels#kafka"
}
}
Reference:
https://docs.microsoft.com/en-us/azure/cosmos-db/sql/kafka-connector-sink
https://www.confluent.io/blog/kafka-connect-deep-dive-converters-serialization-explained/


NEW QUESTION # 209
......

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