From the course: Microsoft Azure Cosmos DB Developer Specialty (DP-420) Cert Prep by Microsoft Press
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Learning objective
From the course: Microsoft Azure Cosmos DB Developer Specialty (DP-420) Cert Prep by Microsoft Press
Learning objective
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Welcome to Lesson 14: Define and Implement an Indexing Strategy for an Azure Cosmos DB Core API. In this lesson, we choose when to use a read-heavy versus write-heavy index strategy. We then choose an appropriate index type. Next, we configure a custom indexing policy by using the Azure portal. Lastly, we implement a composite index, and optimize index performance. Let's begin.
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Contents
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Learning objectives42s
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Develop a design by storing multiple entity types in the same container9m 10s
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Develop a design by storing multiple related entities in the same document9m 18s
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Develop a design by referencing between documents4m 57s
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Identify primary and unique keys11m 35s
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Identify data and associated access patterns6m 55s
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Specify a default TTL on a container for a transactional store21m 6s
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Learning objectives37s
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Choose a partition strategy based on a specific workload2m 24s
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Plan for transactions when choosing a partition key9m 18s
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Calculate and evaluate throughput distribution based on partition key selection12m 41s
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Design partitioning for workloads that require multiple partition keys25m 19s
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Learning objectives34s
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Choose between serverless and provisioned models2m 38s
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Choose when to use database-level provisioned throughput1m 53s
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Design for granular scale units and resource governance2m 2s
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Evaluate the cost of the global distribution of data13m 48s
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Configure throughput for Azure Cosmos DB by using Azure Portal20m 49s
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Learning objectives33s
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Implement a connectivity mode2m 16s
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Create a connection to a database2m
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Enable offline development by using the Azure Cosmos DB emulator1m 11s
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Handle connection errors1m 35s
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Configure client-side threading and parallelism options7m 57s
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Enable SDK logging16m 13s
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Learning objectives34s
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Implement queries that use arrays, nested objects, aggregation, and ordering7m 51s
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Implement a correlated subquery1m 18s
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Implement queries that use array and type-checking functions59s
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Implement queries that use mathematical, string, and date functions3m 25s
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Implement queries based on variable data11m 27s
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Learning objectives1m
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Choose when to use a point operation versus a query operation1m 41s
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Implement a point operation that creates, updates, and deletes documents3m 15s
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Implement an update by using a patch operation2m 48s
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Manage multi-document transactions using SDK transactional batch2m 1s
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Perform a multi-document load using SDK bulk1m 33s
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Implement optimistic concurrency control using ETags2m 25s
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Implement session consistency by using session tokens1m 28s
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Implement a query operation that includes pagination2m 3s
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Implement a query operation by using a continuation token1m 21s
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Handle transient errors and 429s2m 36s
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Specify TTL for a document1m 18s
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Retrieve and use query metrics8m 5s
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Learning objectives31s
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Choose when to distribute data4m 4s
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Define automatic failover policies for regional failure for Azure Cosmos DB Core API1m 50s
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Perform manual failovers to move single master write regions1m 51s
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Specify application connections to replicated data11m 20s
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Learning objective42s
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Integrate events with other applications by using Azure Functions and Azure Event Hubs3m 51s
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Denormalize data by using change feed and Azure Functions7m 43s
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Archive data by using change feed and Azure Functions50s
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Implement Azure Cognitive Search for an Azure Cosmos DB solution3m 2s
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Learning objective37s
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Evaluate response status code and failure metrics3m 4s
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Monitor data replication in relation to latency and availability2m 21s
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Configure Azure Monitor alerts for Azure Cosmos DB2m 42s
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Implement and query Azure Cosmos DB logs5m 22s
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Monitor distribution of data across partitions1m 20s
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Monitor security by using logging and auditing12m 13s
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Learning objective49s
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Choose between service-managed and customer-managed encryption keys2m 3s
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Configure network-level access control for Azure Cosmos DB6m 15s
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Configure data encryption for Azure Cosmos DB1m 10s
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Manage control plane access to Azure Cosmos DB by using Azure role-based access control (RBAC)2m 36s
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Manage data plane access to Azure Cosmos DB by using Azure Active Directory1m 38s
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Configure Cross-Origin Resource Sharing (CORS) settings1m 41s
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Manage account keys by using Azure Key Vault1m 19s
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Implement customer-managed keys for encryption53s
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Implement Always Encrypted12m 55s
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Learning objective30s
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Choose a data movement strategy2m 55s
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Move data by using client SDK bulk operations49s
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Move data by using Azure Data Factory and Azure Synapse pipelines1m 32s
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Move data by using a Kafka connector2m 23s
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Move data by using Azure Stream Analytics1m 27s
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Move data by using the Azure Cosmos DB Spark connector20m 32s
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Learning objective41s
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Choose when to use declarative versus imperative operations3m 22s
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Provision and manage Azure Cosmos DB resources by using Azure Resource Manager templates (ARM templates)1m 46s
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Migrate between standard and autoscale throughput by using PowerShell or Azure CLI2m 58s
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Initiate a regional failover by using PowerShell or Azure CLI2m 41s
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Maintain index policies in production by using ARM templates13m 30s
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