Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB valid torrent & DP-420 prep dumps & Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB latest vce

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Microsoft DP-420 Exam Syllabus Topics:

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

>> DP-420 Test Prep <<

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Microsoft Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Sample Questions (Q60-Q65):

NEW QUESTION # 60
Hotspot Question
You have the indexing policy shown in the following exhibit.
\

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

Answer:

Explanation:

Explanation:
Box 1: ORDER BY c.name DESC, c.age DESC
Queries that have an ORDER BY clause with two or more properties require a composite index.
The following considerations are used when using composite indexes for queries with an ORDER BY clause with two or more properties:
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.
The composite index also supports an ORDER BY clause with the opposite order on all paths.
Box 2: At the same time as the item creation
Azure Cosmos DB supports two indexing modes:
Consistent: The index is updated synchronously as you create, update or delete items. This means that the consistency of your read queries will be the consistency configured for the account.
None: Indexing is disabled on the container.
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/index-policy


NEW QUESTION # 61
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:

Explanation:

Box 1: Serverless capacity mode
Azure Cosmos DB serverless best fits scenarios where you expect intermittent and unpredictable traffic with long idle times. Because provisioning capacity in such situations isn ' t required and may be cost-prohibitive, Azure Cosmos DB serverless should be considered in the following use-cases:
Getting started with Azure Cosmos DB
Running applications with bursty, intermittent traffic that is hard to forecast, or low ( < 10%) average-to-peak traffic ratio Developing, testing, prototyping and running in production new applications where the traffic pattern is unknown Integrating with serverless compute services like Azure Functions Box 2: Provisioned throughput capacity mode and autoscale throughput The use cases of autoscale include:
Variable or unpredictable workloads: When your workloads have variable or unpredictable spikes in usage, autoscale helps by automatically scaling up and down based on usage. Examples include retail websites that have different traffic patterns depending on seasonality; IOT workloads that have spikes at various times during the day; line of business applications that see peak usage a few times a month or year, and more. With autoscale, you no longer need to manually provision for peak or average capacity.
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 # 62
Hotspot Question
You have an Azure Cosmos DB account named account1 that has a default consistency level of session.
You have an app named App1.
You need to ensure that the read operations of App1 can request either bounded staleness or consistent prefix consistency.
What should you modify for each consistency level? To answer, select the appropriate options in the answer area.

Answer:

Explanation:

Explanation:
Consistency can only be relaxed at the SDK instance or request level. To move from weaker to stronger consistency, update the default consistency for the Azure Cosmos DB account.
https://learn.microsoft.com/en-us/azure/cosmos-db/nosql/how-to-manage-consistency?tabs=portal%2Cdotnetv2%2Capi-async


NEW QUESTION # 63
You have a database in an Azure Cosmos DB Core (SQL) API account.
You plan to create a container that will store employee data for 5,000 small businesses. Each business will have up to 25 employees. Each employee item will have an emailAddress value.
You need to ensure that the emailAddress value for each employee within the same company is unique.
To what should you set the partition key and the unique key? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Box 1: CompanyID
After you create a container with a unique key policy, the creation of a new or an update of an existing item resulting in a duplicate within a logical partition is prevented, as specified by the unique key constraint. The partition key combined with the unique key guarantees the uniqueness of an item within the scope of the container.
For example, consider an Azure Cosmos container with Email address as the unique key constraint and CompanyID as the partition key. When you configure the user's email address with a unique key, each item has a unique email address within a given CompanyID. Two items can't be created with duplicate email addresses and with the same partition key value.
Box 2: emailAddress
Reference: https://docs.microsoft.com/en-us/azure/cosmos-db/unique-keys


NEW QUESTION # 64
You have an Azure Cosmos DB container named container1.
You need to insert an item into contained. The solution must ensure that the item is deleted automatically after two hours.
How should you complete the item definition? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:


NEW QUESTION # 65
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