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HybridCloudWorks
AssociateDP-420

Designing and Implementing Cloud-Native Applications Using Azure Cosmos DB

Validate expertise designing and implementing data models, data distribution strategies, and solutions using Azure Cosmos DB for NoSQL. From October 6, 2026 the certification is Microsoft Certified: Azure Cosmos DB AI Developer Associate (until then Azure Cosmos DB Developer Specialty), and the exam is updated the same day.

Study Hours
40h
Prep Time
~3 months
Avg. Pass Rate
70%

Topics Covered

Cosmos DB for NoSQL
Data Modeling
Indexing
Query Optimization
Change Feed

Skills measured

Official study guide

Microsoft's own objectives, in the order the exam presents them. Each area links to its section on Microsoft Learn. Checked 2026-10-26.

  1. Design and develop database solutions40–45%
    This area on Microsoft Learn

    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
  2. Secure, optimize, and deploy database solutions30–35%
    This area on Microsoft Learn

    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
  3. Implement AI and analytics capabilities in database solutions20–25%
    This area on Microsoft Learn

    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

Microsoft Learn Modules

1Get started with Azure Cosmos DB for NoSQL2Plan and implement Azure Cosmos DB for NoSQL