Microsoft DP-420 Exam Topics

Microsoft DP-420 Exam

Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB

Total Questions: 111

Last Updated : 19-04-2024

What is Included in the Microsoft DP-420 Exam?

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Microsoft DP-420 Exam Overview :

Exam Name	Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB
Exam Code	DP-420
Exam Registration Price	$165
Official Information	https://docs.microsoft.com/en-us/learn/certifications/exams/dp-420?WT.mc_id=Azure_blog-wwl
See Expected Questions	Microsoft DP-420 Expected Questions in Actual Exam
Take Self-Assessment	Use Microsoft DP-420 Practice Test to Assess your preparation - Save Time and Reduce Chances of Failure

Microsoft DP-420 Exam Topics :

Section	Weight	Objectives
Design and Implement Data Models	35–40%	Design and implement a non-relational data model for Azure Cosmos DB Core API 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 TTL on a container for a transactional store Design a data partitioning strategy for Azure Cosmos DB Core API choose a partition 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 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 Azure Cosmos DB SQL language 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 SQL API 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 SDK Bulk implement optimistic concurrency control using ETags 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 Core API by using JavaScript write, deploy, and call a stored procedure design stored procedures to work with multiple items transactionally implement 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 Core API 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 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 Core API
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 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 in Azure Cosmos DB Core API 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 an Azure Cosmos DB Core API 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 an Azure Cosmos DB Core API 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 accesscontrol (RBAC) manage data plane access to Azure Cosmos DB by using keys manage data plane access to Azure Cosmos DB by using Azure Active Directory 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 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 (ARM templates) migrate between standard and autoscale throughput by using PowerShell or Azure CLI initiate a regional failover by using PowerShell or Azure CLI maintain index policies in production by using ARM templates

Updates in the Microsoft DP-420 Exam Topics:

Microsoft DP-420 exam questions and practice test are the best ways to get fully prepared. Study4exam's trusted preparation material consists of both practice questions and practice test. To pass the actual Azure Cosmos DB Developer Specialty DP-420 exam on the first attempt, you need to put in hard work on these questions as they cover all updated Microsoft DP-420 exam topics included in the official syllabus. Besides studying actual questions, you should take the Microsoft DP-420 practice test for self-assessment and actual exam simulation. Revise actual exam questions and remove your mistakes with the Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB DP-420 exam practice test. Online and Windows-based formats of the DP-420 exam practice test are available for self-assessment.

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