Get instant Coupon on our Telegram ChannelBe prepared for the MS Azure Exam DP-420: Designing & Implementing Cloud-Native Apps Using Microsoft Azure Cosmos
Description
In order to set realistic expectations, please note: These questions are NOT official questions that you will find on the official exam. These questions DO cover all the material outlined in the knowledge sections below. Many of the questions are based on fictitious scenarios which have questions posed within them.
The official knowledge requirements for the exam are reviewed routinely to ensure that the content has the latest requirements incorporated in the practice questions. Updates to content are often made without prior notification and are subject to change at any time.
Each question has a detailed explanation and links to reference materials to support the answers which ensures accuracy of the problem solutions.
The questions will be shuffled each time you repeat the tests so you will need to know why an answer is correct, not just that the correct answer was item “B” last time you went through the test.
NOTE: This course should not be your only study material to prepare for the official exam. These practice tests are meant to supplement topic study material.
Should you encounter content which needs attention, please send a message with a screenshot of the content that needs attention and I will be reviewed promptly. Providing the test and question number do not identify questions as the questions rotate each time they are run. The question numbers are different for everyone.
As a candidate for this exam, you should have subject matter expertise designing, implementing, and monitoring cloud-native applications that store and manage data.
Your responsibilities for this role include:
Designing and implementing data models and data distribution.
Loading data into an Azure Cosmos DB database.
Optimizing and maintaining the solution.
As a professional in this role, you integrate the solution with other Azure services. You also design, implement, and monitor solutions that consider security, availability, resilience, and performance requirements.
As a candidate for this exam, you must have solid knowledge and experience with:
Developing apps for Azure.
Working with Azure Cosmos DB database technologies.
Creating server-side objects with JavaScript.
You should be proficient at developing applications that use the Azure Cosmos DB for NoSQL API. You should be able to:
Write efficient SQL queries for the API.
Create appropriate indexing policies.
Interpret JSON.
Read C# or Java code.
Use PowerShell.
Additionally, you should be familiar with provisioning and managing resources in Azure.
Skills at a glance
Design and implement data models (35–40%)
Design and implement data distribution (5–10%)
Integrate an Azure Cosmos DB solution (5–10%)
Optimize an Azure Cosmos DB solution (15–20%)
Maintain an Azure Cosmos DB solution (25–30%)
Design and implement data models (35–40%)
Design and implement a non-relational data model for Azure Cosmos DB for NoSQL
Develop a design by storing multiple entity types in the same container
Develop a design by storing multiple related entities in the same document
Develop a model that denormalizes data across documents
Develop a design by referencing between documents
Identify primary and unique keys
Identify data and associated access patterns
Specify a default time to live (TTL) on a container for a transactional store
Design a data partitioning strategy for Azure Cosmos DB for NoSQL
Choose a partitioning strategy based on a specific workload
Choose a partition key
Plan for transactions when choosing a partition key
Evaluate the cost of using a cross-partition query
Calculate and evaluate data distribution based on partition key selection
Calculate and evaluate throughput distribution based on partition key selection
Construct and implement a synthetic partition key
Design and implement a hierarchical partition key
Design partitioning for workloads that require multiple partition keys
Plan and implement sizing and scaling for a database created with Azure Cosmos DB
Evaluate the throughput and data storage requirements for a specific workload
Choose between serverless and provisioned models
Choose when to use database-level provisioned throughput
Design for granular scale units and resource governance
Evaluate the cost of the global distribution of data
Configure throughput for Azure Cosmos DB by using the Azure portal
Implement client connectivity options in the Azure Cosmos DB SDK
Choose a connectivity mode (gateway versus direct)
Implement a connectivity mode
Create a connection to a database
Enable offline development by using the Azure Cosmos DB emulator
Handle connection errors
Implement a singleton for the client
Specify a region for global distribution
Configure client-side threading and parallelism options
Enable SDK logging
Implement data access by using the SQL language for Azure Cosmos DB for NoSQL
Implement queries that use arrays, nested objects, aggregation, and ordering
Implement a correlated subquery
Implement queries that use array and type-checking functions
Implement queries that use mathematical, string, and date functions
Implement queries based on variable data
Implement data access by using Azure Cosmos DB for NoSQL SDKs
Choose when to use a point operation versus a query operation
Implement a point operation that creates, updates, and deletes documents
Implement an update by using a patch operation
Manage multi-document transactions using SDK Transactional Batch
Perform a multi-document load using Bulk Support in the SDK
Implement optimistic concurrency control using ETags
Override default consistency by using query request options
Implement session consistency by using session tokens
Implement a query operation that includes pagination
Implement a query operation by using a continuation token
Handle transient errors and 429s
Specify TTL for a document
Retrieve and use query metrics
Implement server-side programming in Azure Cosmos DB for NoSQL by using JavaScript
Write, deploy, and call a stored procedure
Design stored procedures to work with multiple documents transactionally
Implement and call triggers
Implement a user-defined function
Design and implement data distribution (5–10%)
Design and implement a replication strategy for Azure Cosmos DB
Choose when to distribute data
Define automatic failover policies for regional failure for Azure Cosmos DB for NoSQL
Perform manual failovers to move single master write regions
Choose a consistency model
Identify use cases for different consistency models
Evaluate the impact of consistency model choices on availability and associated request unit (RU) cost
Evaluate the impact of consistency model choices on performance and latency
Specify application connections to replicated data
Design and implement multi-region write
Choose when to use multi-region write
Implement multi-region write
Implement a custom conflict resolution policy for Azure Cosmos DB for NoSQL
Integrate an Azure Cosmos DB solution (5–10%)
Enable Azure Cosmos DB analytical workloads
Enable Azure Synapse Link
Choose between Azure Synapse Link and Spark Connector
Enable the analytical store on a container
Implement custom partitioning in Azure Synapse Link
Enable a connection to an analytical store and query from Azure Synapse Spark or Azure Synapse SQL
Perform a query against the transactional store from Spark
Write data back to the transactional store from Spark
Implement solutions across services
Integrate events with other applications by using Azure Functions and Azure Event Hubs
Denormalize data by using Change Feed and Azure Functions
Enforce referential integrity by using Change Feed and Azure Functions
Aggregate data by using Change Feed and Azure Functions, including reporting
Archive data by using Change Feed and Azure Functions
Implement Azure Cognitive Search for an Azure Cosmos DB solution
Optimize an Azure Cosmos DB solution (15–20%)
Optimize query performance when using the API for Azure Cosmos DB for NoSQL
Adjust indexes on the database
Calculate the cost of the query
Retrieve request unit cost of a point operation or query
Implement Azure Cosmos DB integrated cache
Design and implement change feeds for Azure Cosmos DB for NoSQL
Develop an Azure Functions trigger to process a change feed
Consume a change feed from within an application by using the SDK
Manage the number of change feed instances by using the change feed estimator
Implement denormalization by using a change feed
Implement referential enforcement by using a change feed
Implement aggregation persistence by using a change feed
Implement data archiving by using a change feed
Define and implement an indexing strategy for Azure Cosmos DB for NoSQL
Choose when to use a read-heavy versus write-heavy index strategy
Choose an appropriate index type
Configure a custom indexing policy by using the Azure portal
Implement a composite index
Optimize index performance
Maintain an Azure Cosmos DB solution (25–30%)
Monitor and troubleshoot an Azure Cosmos DB solution
Evaluate response status code and failure metrics
Monitor metrics for normalized throughput usage by using Azure Monitor
Monitor server-side latency metrics by using Azure Monitor
Monitor data replication in relation to latency and availability
Configure Azure Monitor alerts for Azure Cosmos DB
Implement and query Azure Cosmos DB logs
Monitor throughput across partitions
Monitor distribution of data across partitions
Monitor security by using logging and auditing
Implement backup and restore for an Azure Cosmos DB solution
Choose between periodic and continuous backup
Configure periodic backup
Configure continuous backup and recovery
Locate a recovery point for a point-in-time recovery
Recover a database or container from a recovery point
Implement security for an Azure Cosmos DB solution
Choose between service-managed and customer-managed encryption keys
Configure network-level access control for Azure Cosmos DB
Configure data encryption for Azure Cosmos DB
Manage control plane access to Azure Cosmos DB by using Azure role-based access control (RBAC)
Manage data plane access to Azure Cosmos DB by using keys
Manage data plane access to Azure Cosmos DB by using Microsoft Entra ID
Configure cross-origin resource sharing (CORS) settings
Manage account keys by using Azure Key Vault
Implement customer-managed keys for encryption
Implement Always Encrypted
Implement data movement for an Azure Cosmos DB solution
Choose a data movement strategy
Move data by using client SDK bulk operations
Move data by using Azure Data Factory and Azure Synapse pipelines
Move data by using a Kafka connector
Move data by using Azure Stream Analytics
Move data by using the Azure Cosmos DB Spark Connector
Configure Azure Cosmos DB as a custom endpoint for an Azure IoT Hub
Implement a DevOps process for an Azure Cosmos DB solution
Choose when to use declarative versus imperative operations
Provision and manage Azure Cosmos DB resources by using Azure Resource Manager templates
Migrate between standard and autoscale throughput by using PowerShell or Azure CLI
Initiate a regional failover by using PowerShell or Azure CLI
Maintain indexing policies in production by using Azure Resource Manager templates
| Total Students | 41 |
|---|---|
| Original Price($) | |
| Sale Price | Free |
| Number of lectures | 0 |
| Number of quizzes | 4 |
| Total Reviews | 5 |
| Global Rating | 4.7 |
| Instructor Name | Wade Henderson |
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