Microsoft Certified: Azure Cosmos DB Developer Specialty

Prepare to pass the DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB certification exam to be awarded the Microsoft Certified: Azure Cosmos DB Developer Specialty.

Course Level: Intermediate

Role: Developer

Duration: 4 Days

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Exam DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (beta)

Candidates for this exam must have solid knowledge and experience developing apps for Azure and working with Azure Cosmos DB database technologies. They should be proficient at developing applications by using the Core (SQL) API and SDKs, writing efficient queries and creating appropriate index policies, provisioning and managing resources in Azure, and creating server-side objects with JavaScript. They should be able to interpret JSON, read C# or Java code, and use PowerShell.

Course Outline

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 access control (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

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