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Microsoft DP-420 Exam Syllabus Topics:

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

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q58-Q63):

NEW QUESTION # 58
You need to implement a trigger in Azure Cosmos DB Core (SQL) API that will run before an item is inserted into a container.
Which two actions should you perform to ensure that the trigger runs? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

Answer: A,E

Explanation:
Explanation
C: When triggers are registered, you can specify the operations that it can run with.
F: When executing, pre-triggers are passed in the RequestOptions object by specifying PreTriggerInclude and then passing the name of the trigger in a List object.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/sql/how-to-use-stored-procedures-triggers-udfs


NEW QUESTION # 59
You configure Azure Cognitive Search to index a container in an Azure Cosmos DB Core (SQL) API account as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: country
The country field is filterable.
Note: filterable: Indicates whether to enable the field to be referenced in $filter queries. Filterable differs from searchable in how strings are handled. Fields of type Edm.String or Collection(Edm.String) that are filterable do not undergo lexical analysis, so comparisons are for exact matches only.
Box 2: name
The name field is not Retrievable.
Retrievable: Indicates whether the field can be returned in a search result. Set this attribute to false if you want to use a field (for example, margin) as a filter, sorting, or scoring mechanism but do not want the field to be visible to the end user.
Note: searchable: Indicates whether the field is full-text searchable and can be referenced in search queries.
Reference: https://docs.microsoft.com/en-us/rest/api/searchservice/create-index


NEW QUESTION # 60
You have a container in an Azure Cosmos DB for NoSQL account.
You need to create an alert based on a custom Log Analytics query.
Which signal type should you use?

Answer: A


NEW QUESTION # 61
You are creating a database in an Azure Cosmos DB Core (SQL) API account. The database will be used by an application that will provide users with the ability to share online posts. Users will also be able to submit comments on other users' posts.
You need to store the data shown in the following table.

The application has the following characteristics:
Users can submit an unlimited number of posts.
The average number of posts submitted by a user will be more than 1,000.
Posts can have an unlimited number of comments from different users.
The average number of comments per post will be 100, but many posts will exceed 1,000 comments.
Users will be limited to having a maximum of 20 interests.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box 1: Yes
Non-relational data increases write costs, but can decrease read costs.
Box 2: Yes
Non-relational data increases write costs, but can decrease read costs.
Box 3: No
Non-relational data increases write costs, but can decrease read costs.


NEW QUESTION # 62
You have an Azure subscription that contains an Azure Cosmos DB for NoSQL account named account1.
In account1, you plan to create a container that will store the data items shown in the following table.

Each customer item will have customer sales by month values embedded.
The most executed query will return data for a matrix that aggregates the monthly sales of each business category. The matrix will use customer business categories as columns and months as rows.
You need to configure the partition key for the container. The solution must minimize the request units (RUs) required to run the query.
Which property should you use for the partition key?

Answer: C

Explanation:
The correct property to use for the partition key is customerBusinessCategoryId.
Selecting customerBusinessCategoryId as the partition key minimizes Request Units (RUs) for the following reasons:
Query Alignment: The most frequent query aggregates monthly sales per business category.
Single-Partition Efficiency: By partitioning by customerBusinessCategoryId, all customer records belonging to the same business category are stored within the same logical partition.
Reduced Overhead: The aggregation query can be routed to a single partition (or a specific set of partitions for each category) rather than scanning every partition in the container (a cross-partition query), which significantly lowers RU consumption.
Data Distribution: With 100 unique categories, the data is distributed enough to avoid major performance bottlenecks while still keeping related records together for the specific aggregation required by the matrix.
Incorrect:
Other options like customerName or customerSalesForMonth would result in expensive cross- partition queries because the data needed for a single business category's aggregate would be scattered across many different partitions.
Reference:
https://docs.azure.cn/en-us/cosmos-db/partitioning


NEW QUESTION # 63
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