DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB

Master the skills to design, implement, and monitor cloud-native applications using Azure Cosmos DB through this specialized, role-based certification.

DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Certification & Training

Emigo Networks offers specialized training for the DP-420 certification, designed to equip professionals with the skills to design, develop, and optimize cloud-native applications using Microsoft Azure Cosmos DB. This course covers key concepts such as data modeling, partitioning, and global distribution, enabling participants to build scalable, highly available applications. With expert-led sessions and hands-on labs, learners gain practical experience to excel in modern cloud environments and achieve the DP-420 certification.

Course Overview

The DP-420 course, offered by Emigo Networks, is designed for developers aiming to build scalable and high-performance cloud-native applications using Azure Cosmos DB. This intermediate-level training focuses on leveraging the NoSQL API and SDKs to create efficient data models, implement indexing policies, and manage resources effectively. Participants will gain hands-on experience in provisioning and configuring Azure Cosmos DB for NoSQL, optimizing performance, and integrating solutions with other Azure services. The course prepares learners for the Microsoft Certified: Azure Cosmos DB Developer Specialty certification.

What You'll Learn

Designing and Implementing Data Models and Distribution: Develop efficient data models and implement data distribution strategies to optimize performance and scalability.
Integrating Azure Cosmos DB Solutions: Integrate Azure Cosmos DB with other Azure services to build comprehensive cloud-native applications.
Optimizing and Maintaining Azure Cosmos DB Solutions: Implement best practices for performance tuning, monitoring, and maintaining Azure Cosmos DB solutions to ensure reliability and efficiency.

Thank You for Choosing EMIGO

Syllabus Summary

Design and implement data models (35–40%)

a. 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
Develop a design for versioning documents
Develop a design for document schema versioning

b. 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

c. 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, provisioned and free 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

d. 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

e. 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

f. 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

g. 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%)

a. 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

b. 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%)

a. 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 Change Data Capture in the Azure Cosmos DB analytical store
Implement time travel in Azure Synapse Link for Azure Cosmos DB

b. 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 AI Search for an Azure Cosmos DB solution

Optimize an Azure Cosmos DB solution (15–20%)

a. 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

b. 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

c. 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%)

a. 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

b. 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

c. 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 control plane access to Azure Cosmos DB Data Explorer by using Azure role-based access control (RBAC)
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

d. 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

e. 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

Pre-requisites

Basic understanding of cloud computing concepts and Microsoft Azure services
Experience in developing applications using NoSQL databases and familiarity with JSON
Knowledge of data modeling and programming skills in languages such as C#, Java, Python, or JavaScript
Familiarity with REST APIs and distributed database concepts is beneficial
Prior experience with Azure development and database management is recommended but not mandatory

Required Exams

Exam Codes: DP-420: Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB
Length: 100 minutes
Registration fee: $165 USD (+taxes applicable)

Who Should Attend

Cloud developers and engineers responsible for building scalable, distributed applications using Azure Cosmos DB
Software architects designing cloud-native solutions that require NoSQL database implementations
Database administrators and developers seeking to expand skills in Azure Cosmos DB and cloud data management
IT professionals involved in application modernization and cloud migration projects using Microsoft Azure
Anyone preparing for the DP-420 certification exam aiming to validate their expertise in Cosmos DB solutions

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What does the DP-420 certification focus on?

DP-420 certifies your skills in designing and implementing scalable, cloud-native applications using Microsoft Azure Cosmos DB.

What key topics are covered in Emigo’s DP-420 training?

Training covers Cosmos DB data models, partitioning, security, consistency models, global distribution, and integration with Azure services.

Who should take this certification training?

This course is ideal for developers, database administrators, and cloud solution architects working with NoSQL databases and cloud-native apps on Azure.

What is the official exam fee for the DP-420 certification?

The Microsoft DP-420 exam fee is approximately USD 165, subject to local taxes and currency rates.

Does Emigo offer the DP-420 course online?

Yes, Emigo provides live instructor-led online sessions, allowing flexible learning from any location.

Is onsite training available at Emigo’s Kochi center?

Yes, Emigo conducts classroom training in Kochi with hands-on labs and direct interaction with expert trainers.

Are there corporate training options for DP-420?

Emigo offers customized corporate training to address specific organizational requirements and team skill development.

Can individuals opt for personalized training programs?

Yes, personal and professional learners can choose tailored training paths to suit their experience and career goals.

How long does the DP-420 training typically last?

The course duration ranges from 3 to 5 days, depending on the delivery format and depth of content.

Are any prerequisites recommended for this training?

Basic knowledge of NoSQL databases, Azure fundamentals, and experience with application development is beneficial.

What hands-on experience is included in the training?

Participants engage in real-world labs focused on Cosmos DB provisioning, data modeling, scaling, and troubleshooting.

How can I enroll in DP-420 training at Emigo Kochi?

Enroll by contacting Emigo Networks via their website, phone, or visiting their Kochi training facility for scheduling and details.

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