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AI-200 Event Driven Integration Practice Question

You are architecting an AI-driven video analytics pipeline using Azure Event Hubs. You need to ensure that frames belonging to the exact same video session are processed in strict chronological order by the same backend stream analytics worker. How should you partition your Event Hub?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Include the video session ID as the Partition Key when publishing events to the Event Hub.

To guarantee ordered processing for a specific entity, you must use a Partition Key when sending events to Event Hubs. All events with the same partition key are automatically routed to the same underlying partition.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Increase the consumer group count to match the number of active video sessions.

    Why it's wrong here

    Consumer groups define independent views of the stream, not partitioning or ordering logic.

  • Set the message TTL to zero and enable capture mode on the Event Hub namespace.

    Why it's wrong here

    Capture mode stores data in Azure Blob Storage; it does not dictate stream consumer ordering.

  • Include the video session ID as the Partition Key when publishing events to the Event Hub.

    Why this is correct

    Event Hubs hashes the partition key to map it to a specific partition, ensuring FIFO order for that key.

  • Deploy an Azure Service Bus Session-enabled queue in front of the Event Hubs ingestion layer.

    Why it's wrong here

    Placing Service Bus in front of Event Hubs introduces unnecessary latency and architectural anti-patterns.

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Written and reviewed by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

Last reviewed August 2026 · checked against the official Microsoft exam blueprint

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