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

How the Exam Is Structured

Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB (DP-420) validates design and model data solutions for azure cosmos db for nosql, implement azure cosmos db solutions using sdks, queries, and transactions, provision, secure, and manage azure cosmos db resources, monitor, troubleshoot, and optimize azure cosmos db solutions. The ExamPal practice bank includes 12 premium questions and 12 free questions mapped across the official blueprint.

22% of exam

Domain 2: Implement Azure Cosmos DB solutions using SDKs, queries, and transactions

Covers SDK connectivity, local development, item and batch operations, querying, and server-side programming. This domain focuses on implementing and validating application behavior with Azure Cosmos DB for NoSQL using SDKs, queries, transactions, and event processing.

14% of exam

Domain 4: Monitor, troubleshoot, and optimize Azure Cosmos DB solutions

Covers monitoring, troubleshooting, and performance/cost optimization for Azure Cosmos DB solutions. This domain emphasizes using metrics, diagnostics, SDK error handling, and workload tuning to improve reliability and efficiency.

Key Terms to Know

These terms are loaded from the shared terminology pack and appear across the question explanations.

NoSQL document database

A non-relational database model that stores semi-structured data as documents rather than rows and tables.

RU consumption

The amount of request units used by database operations, representing consumed throughput capacity.

authentication

The process of verifying the identity of a user, application, or service before access is granted.

availability

The measure of whether the database service remains accessible and operational for requests.

backoff

A retry strategy that waits progressively longer between attempts to reduce pressure on the service.

backup mode

The Azure Cosmos DB backup configuration option that determines how backups are taken and managed for recovery scenarios.

change feed

A persistent, ordered stream of item changes in a container that applications can process asynchronously.

change feed processing

The application pattern of reading the change feed to react to inserts and updates, such as syncing downstream systems.

co-locating related data

A modeling approach where frequently accessed related information is stored together to reduce query cost and latency.

consistency level

The read consistency guarantee in Cosmos DB that defines the tradeoff between data freshness, latency, and availability.

container

A schema-agnostic unit in Azure Cosmos DB that stores items and defines partitioning, indexing, and throughput settings.

cross-partition query

A query that must read from multiple partitions because the partition key is not sufficiently targeted in the filter.

data modeling

The practice of structuring documents and relationships based on application access patterns and performance goals.

hot partition

A partition that receives disproportionately high traffic or storage, causing uneven load and performance issues.

identity-based access

An authentication and authorization approach that uses Azure identities instead of account keys or embedded secrets.

indexing policy

The container-level rule set that specifies included paths, excluded paths, and index behavior for stored items.

indexing settings

The configuration that controls which item properties are indexed and how queries can efficiently access them.

latency

The time required for a request or query to be processed and return a response.