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Microsoft DP-420 Exam Syllabus

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

Last Update Dec 30, 2024
Total Questions : 136

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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
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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 Syllabus:

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