Description
Skills at a glance
- Design and implement data models (35–40%)
- Design and implement data distribution (5–10%)
- Integrate an Azure Cosmos DB solution (5–10%)
- Optimize an Azure Cosmos DB solution (15–20%)
- Maintain an Azure Cosmos DB solution (25–30%)
Design and implement data models (35–40%)
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
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 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
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
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
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
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%)
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 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%)
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
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%)
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
Maintain an Azure Cosmos DB solution (25–30%)
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
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
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
Who this course is for:
- This certification is ideal for developers and solution architects who design and build cloud-native applications that use Azure Cosmos DB as their primary data store.