- Lab
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Libraries: If you want this lab, consider one of these libraries.
- Cloud
- Data
Storage and Cosmos DB
Provision the Azure resources that will store inbound support tickets and the structured outputs your pipeline produces. You'll create an Azure Storage account with a blob container for ticket ingestion and a Cosmos DB account with a NoSQL database and container configured for AI-generated documents. The configuration choices you make here (access tier, API selection, throughput mode, partition key) directly shape how the pipeline performs and what it costs once code is deployed against it in later labs.
Lab Info
Table of Contents
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Challenge
Configure Azure Blob Storage as the ingestion point for raw support tickets
Decide on an appropriate redundancy and access tier for unpredictable, write-heavy ticket arrival. Create a dedicated container for inbound tickets and confirm it can receive blob uploads.
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Challenge
Provision Cosmos DB with the NoSQL API for storing structured AI outputs
Select the NoSQL API, choose between serverless and provisioned throughput based on the pipeline's expected load profile, and create the Cosmos DB account.
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Challenge
Configure a Cosmos DB container with a partition key suited to the document shape
Set a partition key path that distributes write load across logical partitions without creating hot spots. Confirm the database and container are ready to accept documents from pipeline code deployed in later labs.
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