Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB Practice Test
Build your confidence for Designing and Implementing Cloud-Native Applications Using Microsoft Azure Cosmos DB. Practice the concepts, understand the answers, and strengthen your knowledge one question at a time.
Try a sample questionExam overview and details
This practice test is designed for IT professionals preparing to validate their expertise in designing and implementing cloud-native applications using Azure Cosmos DB for NoSQL. The exam covers five core domains: designing and implementing a Cosmos DB for NoSQL solution, implementing server-side programming constructs such as stored procedures, triggers, and user-defined functions, integrating the solution with other Azure services and client applications, maintaining the solution through monitoring, backup, and disaster recovery, and optimizing performance, cost, and throughput. The test includes 66 questions that mirror the complexity and breadth of the official certification exam. It is intended for developers, solution architects, and database administrators who have hands-on experience with Azure Cosmos DB and are seeking to formalize their skills. Candidates will gain a thorough understanding of how to model data for NoSQL, configure indexing policies, manage consistency levels, implement change feed processing, and tune request units (RUs) for cost efficiency. Successfully mastering this content equips learners to build scalable, globally distributed applications that meet enterprise requirements for latency, availability, and throughput.
Sample Questions
Choose an answer and explore the explanation to see how practice works.
During an Azure Cosmos DB architecture review, the topic is worldwide read/write availability. Which recommendation should be made?
During an Azure Cosmos DB architecture review, the topic is throughput divided across physical partitions. Which recommendation should be made?
During an Azure Cosmos DB architecture review, the topic is vector and hybrid search. Which recommendation should be made?
During an Azure Cosmos DB architecture review, the topic is partition key for throughput distribution. Which recommendation should be made?
During an Azure Cosmos DB architecture review, the topic is regular partition keys. Which recommendation should be made?
Career Opportunities & Salary
Exam insights and study advice
Azure Cosmos DB is a foundational service for modern cloud-native applications that require low-latency access to data at global scale. Mastering its design and implementation directly impacts real-world outcomes: you will be able to architect solutions that handle millions of requests per second, reduce operational costs by optimizing RU consumption, and ensure high availability across regions. This practice test bridges the gap between theoretical knowledge and practical application, helping you avoid common pitfalls such as over-provisioning throughput, poor partition key selection, or inefficient indexing. The skills validated here are immediately applicable to production scenarios, from e-commerce platforms to IoT telemetry pipelines, making you a more effective contributor to any cloud-native team.
What this exam covers
Use the published domain weights to plan your study. Practice results do not predict your certification exam score.
01Design and implement data models
Topics
- Design and implement a non-relational data model for Azure Cosmos DB for NoSQL
- Design a data partitioning strategy for Azure Cosmos DB for NoSQL
- Plan and implement sizing and scaling for a database created with Azure Cosmos DB
Learning objectives
- 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 partition key, id, 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
- 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
- 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 tier; 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
02Maintain an Azure Cosmos DB solution
Topics
- Monitor and troubleshoot an Azure Cosmos DB solution
- Implement backup and restore for an Azure Cosmos DB solution
- Implement security for an Azure Cosmos DB solution
- Implement data movement for an Azure Cosmos DB solution
- Implement a DevOps process for an Azure Cosmos DB solution
Learning objectives
- Monitor and troubleshoot an Azure Cosmos DB solution: Evaluate response status code and failure metrics; Monitor the Normalized RU Consumption metric 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 Monitor resource logs for Azure Cosmos DB; 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 point-in-time restore; Locate a restore point for a point-in-time restore; Restore a database or container from a restore 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 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
- 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
- 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
03Optimize an Azure Cosmos DB solution
Topics
- Optimize query performance when using the API for Azure Cosmos DB for NoSQL
- Design and implement change feeds for Azure Cosmos DB for NoSQL
- Define and implement an indexing strategy for Azure Cosmos DB for NoSQL
Learning objectives
- 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
04Design and implement data distribution
Topics
- Design and implement a replication strategy for Azure Cosmos DB
- Implement a custom conflict resolution policy for Azure Cosmos DB for NoSQL
Learning objectives
- 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; Design and implement multi-region writes
- Implement a custom conflict resolution policy for Azure Cosmos DB for NoSQL
05Integrate an Azure Cosmos DB solution
Topics
- Enable Azure Cosmos DB analytical workloads
- Implement solutions across services
Learning objectives
- Enable Azure Cosmos DB analytical workloads: Configure Azure Cosmos DB Mirroring for Microsoft Fabric; Choose between Azure Cosmos DB Mirroring and the Azure Cosmos DB 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 Change Data Capture in the Azure Cosmos DB analytical store
- 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