Microsoft Azure Developer Associate AZ-204 Practice Question
You are building a .NET worker service that will process inserts and updates in a Cosmos DB container named "sales" by using the Azure Cosmos DB change feed processor library. The solution must support scaling to several worker instances and must resume from the last processed position after a crash or redeployment. Before starting the processor, which action should you perform to meet these requirements?
Enable full-fidelity change feed mode for the Cosmos DB account.
Enable analytical store on the "sales" container to store change events separately.
Change the database consistency level to Session so the processor can track checkpoints.
Create a dedicated lease container in the same database and specify it when configuring the ChangeFeedProcessor.
The change feed processor coordinates work and saves its progress by writing lease documents to a separate "lease" container. Each worker instance claims leases on individual partitions so it can scale out safely, and on restart the processor reads its own leases to continue from the last processed continuation token. The lease container is created ahead of time, typically with /id as its partition key, and does not need to share the same partition key definition as the monitored container. Enabling analytical store, full-fidelity mode, or changing the database consistency level does not provide the coordination or checkpoint persistence required.
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What is a lease container in Azure Cosmos DB?
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How does the Change Feed Processor ensure fault tolerance?
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Why is enabling analytical store or full-fidelity mode not sufficient for Change Feed processing?
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Microsoft Azure Developer Associate AZ-204
Develop for Azure storage
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