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Note
We’re updating the certification’s name and level to reflect the evolving role of Azure Cosmos DB developers. The updated certification will be Microsoft Certified: Azure Cosmos DB AI Developer Associate. This change will go into effect on October 6, 2026. No action is required. Learn more.
Purpose of this document
This study guide should help you understand what to expect on the exam and includes a summary of the topics the exam might cover and links to additional resources. The information and materials in this document should help you focus your studies as you prepare for the exam.
| Useful links | Description |
|---|---|
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| Your Microsoft Learn profile | Connecting your certification profile to Microsoft Learn allows you to schedule and renew exams and share and print certificates. |
| Exam scoring and score reports | A score of 700 or greater is required to pass. |
| Exam sandbox | You can explore the exam environment by visiting our exam sandbox. |
| Request accommodations | If you use assistive devices, require extra time, or need modification to any part of the exam experience, you can request an accommodation. |
| Take a free Practice Assessment | Test your skills with practice questions to help you prepare for the exam. |
Updates to the exam
Our exams are updated periodically to reflect skills that are required to perform a role.
We always update the English language version of the exam first. Some exams are localized into other languages, and those are updated approximately eight weeks after the English version is updated. Other available languages are listed in the Schedule Exam section of the Exam Details webpage. If the exam isn't available in your preferred language, you can request an additional 30 minutes to complete the exam.
Note
The bullets that follow each of the skills measured are intended to illustrate how we are assessing that skill. Related topics may be covered in the exam.
Note
Most questions cover features that are general availability (GA). The exam may contain questions on Preview features if those features are commonly used.
Skills measured as of October 6, 2026
Audience profile
As an Azure Cosmos DB Developer Associate, you design, build, and optimize cost effective high-performance scalable applications that use Azure Cosmos DB including system of record for agent memory, conversation state, retrieval indexes, grounding data, and application data.
Your responsibilities include:
Designing and implementing data models and data distribution
Ingesting and querying data with Azure Cosmos DB database
Optimizing application performance, scalability, and cost
Implementing secure and production-ready applications
Building AI retrieval and RAG solutions
Designing and implementing agent memory systems
Integration of Azure Cosmos DB with Microsoft Fabric for analytical querying and operational insights
In this role, you collaborate with AI engineers, application developers, solution architects, data engineers, and security professionals to design and implement cost effective high-performance scalable applications.
You should have experience developing applications by using C# or Python. You should be familiar with Azure services, generative AI concepts, retrieval-based systems, and application development practices.
Skills at a glance
Design and develop database solutions (40–45%)
Secure, optimize, and deploy database solutions (30–35%)
Implement AI and Analytics capabilities in database solutions (20–25%)
Design and develop database solutions (40–45%)
Evaluate resource models and SDK solutions
Evaluate consistency levels
Evaluate Request Unit (RU) consumption requirements
Evaluating and configuring appropriate throughput
Configure account-level and container-level settings
Create and manage database and containers
Initialize SDK clients and connections
Implement database operations
Implement queries, parameterized queries, paging, and continuation tokens
Implement point read operations
Implement create, replace, update, patch and delete operations
Implement bulk, batch, and transactional operations
Configure Time to Live (TTL)
Implement concurrency control mechanisms
Design and implement data models and partitioning strategies
Design data models for access patterns and operational requirements
Design and select partition keys based on cardinality, access patterns, and write distribution requirements
Determine when to embed or reference related data
Evaluate the impact of partition key selection on scalability and performance
Implement hierarchical partition keys (HPKs) and multi-tenant partitioning strategies
Implement synthetic partition keys
Identify partitioning anti-patterns and partitioning issues during solution reviews
Estimate workload cost requirements
Implement change feed
Implement change feed operations
Differentiate between change feed processor and pull mode models
Configure lease containers
Implement change feed processing using latest mode or all versions and delete
Implement copy container jobs
Design and implement Azure Cosmos DB solutions by using AI-assisted tools
Implement Agent Kit to follow Azure Cosmos DB development recommended solutions
Implement Agent Kit to accelerate AI application development
Secure, optimize, and deploy database solutions (30–35%)
Implement database security controls
Configure authentication mechanisms
Configure authorization controls
Configure network security
Configure dynamic data masking
Implement availability and recovery solutions
Configure backup and restore solutions
Implement multi-region read and write configurations
Configure partition failover solutions
Optimize and remediate database performance
Optimize query performance
Analyze query performance metrics
Analyze index performance metrics
Monitor end-to-end latency against service objectives
Configure Azure Monitor alerts
Analyze diagnostic logs in Log Analytics
Implement Fleet management and monitoring across multiple accounts and subscriptions
Configure Fleet level throughput management
Configure Fleet monitoring with fleet analytics
Implement AI and analytics capabilities in database solutions (20–25%)
Design and implement AI retrieval
Design and implement full-text search
Design for vector data, including vector data type, vector indexes, and size
Design and implement vector partitioning and sharded DiskANN implementations
Implement vector search
Design and implement hybrid search
Optimize full-text and vector performance
Design and implement Retrieval-Augmented Generation (RAG)
Design and implement agent memory stores
Design durable memory stores
Implement conversation state
Implement semantic memory
Design and implement operational analytics on Azure Cosmos DB
Choose between Azure Cosmos DB and Cosmos DB in Microsoft Fabric
Configure and monitor data mirroring into Microsoft Fabric
Query Azure Cosmos DB mirrored JSON data in Microsoft Fabric with T-SQL and Spark
Read and write data into Azure Cosmos DB from Microsoft Fabric with Cosmos DB Spark connector
Study resources
We recommend that you train and get hands-on experience before you take the exam. We offer self-study options and classroom training as well as links to documentation, community sites, and videos.
| Study resources | Links to learning and documentation |
|---|---|
| Get trained | Choose from self-paced learning paths and modules or take an instructor-led course |
| Find documentation | Azure Cosmos DB documentation Azure documentation |
| Ask a question | Microsoft Q&A | Microsoft Docs |
| Get community support | Analytics on Azure - Microsoft Tech Community Azure Data Factory - Microsoft Tech Community Azure - Microsoft Tech Community |
| Follow Microsoft Learn | Microsoft Learn - Microsoft Tech Community |
| Find a video | Exam Readiness Zone Data Exposed Browse other Microsoft Learn shows |
Change log
The table below summarizes the changes between the current and previous version of the skills measured. The functional groups are in bold typeface followed by the objectives within each group. The table is a comparison between the previous and current version of the exam skills measured and the third column describes the extent of the changes.
| Skill area prior to October 6, 2026 | Skill area as of October 6, 2026 | Change |
|---|---|---|
| Audience profile | Major | |
| Design and implement data models | Design and develop database solutions | % of exam increased |
| Design and implement a non-relational data model for Azure Cosmos DB for NoSQL | Design and implement data models and partitioning strategies | Minor |
| Design a data partitioning strategy for Azure Cosmos DB for NoSQL | Removed | |
| Plan and implement sizing and scaling for a database created with Azure Cosmos DB | Evaluate resource models and SDK solutions | Major |
| Implement client connectivity options in the Azure Cosmos DB SDK | Removed | |
| Implement data access by using the SQL language for Azure Cosmos DB for NoSQL | Implement database operations | Major |
| Implement data access by using Azure Cosmos DB for NoSQL SDKs | Removed | |
| Implement server-side programming in Azure Cosmos DB for NoSQL by using JavaScript | Removed | |
| Design and implement Azure Cosmos DB solutions by using AI-assisted tools | New | |
| Design and implement data distribution | Removed | |
| Design and develop database solutions | Added | |
| Design and implement a replication strategy for Azure Cosmos DB | Implement availability and recovery solutions | Major |
| Design and implement multi-region write | Removed | |
| Integrate an Azure Cosmos DB solution | Removed | |
| Design and develop database solutions | Added | |
| Enable Azure Cosmos DB analytical workloads | Design and implement operational analytics on Azure Cosmos DB | Major |
| Implement solutions across services | Deleted | |
| Optimize an Azure Cosmos DB solution | Secure, optimize, and deploy database solutions | % of exam increased |
| Optimize query performance when using the API for Azure Cosmos DB for NoSQL | Optimize and remediate database performance | Minor |
| Design and implement change feeds for Azure Cosmos DB for NoSQL | Implement change feed | Minor |
| Define and implement an indexing strategy for Azure Cosmos DB for NoSQL | Optimize and remediate database performance | Major |
| Implement Fleet management and monitoring across multiple accounts and subscriptions | New | |
| Maintain an Azure Cosmos DB solution | Removed | |
| Monitor and troubleshoot an Azure Cosmos DB solution | Optimize and remediate database performance | Major |
| Implement backup and restore for an Azure Cosmos DB solution | Implement availability and recovery solutions | Major |
| Implement security for an Azure Cosmos DB solution | Implement database security controls | Minor |
| Implement data movement for an Azure Cosmos DB solution | Deleted | |
| Implement a DevOps process for an Azure Cosmos DB solution | Deleted | |
| Implement AI and analytics capabilities in database solutions | New | |
| Design and implement AI retrieval | New | |
| Design and implement agent memory stores | New | |
| Design and implement operational analytics on Azure Cosmos DB | New |