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Exam Number: DP-420

Exam Title: Designing and Implementing Native Applications Using Microsoft Azure Cosmos DB

Passing Score: 700 (Total Score: 1000)(Tips: You should pass 70% for each section of the exam (bar on the chart), or else you still faild the exam even your total score more than 700 )

Origin Provider: ExamKiller

Total Questions: 81 QAs

Type: Real Exam Questions

Guarantee: 100% Pass Guarantee

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Microsoft DP-420 Exam Objectives

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 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 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 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
• 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 Azure Active Directory (Azure AD)
• 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

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