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AZ-204 Practice Question: Event Hubs consumer groups for multiple…
Three analytics pipelines each need to read every event from the same Azure Event Hub: one pipeline archives events to cold storage, one computes real-time aggregations, and one feeds a machine learning model. How should the developer configure Event Hubs to allow all three to consume independently without interfering with each other?
⚠ Common exam trap
Watch out — candidates often confuse consumer groups with partitions, thinking that multiple consumers must use different partitions to avoid interference, but partitions are for scaling throughput, not for independent offset tracking—consumer groups are the correct abstraction for independent consumption.
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
✓
Create a separate consumer group for each pipeline; each group tracks its own offset independently
A is correct because each consumer group in Event Hubs maintains its own independent offset and checkpoint, allowing multiple consumers to read the same event stream without interfering. By creating a separate consumer group for each pipeline (archival, real-time aggregation, ML), each pipeline can process events at its own pace and from its own position in the stream, ensuring no consumer's progress affects another.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create a separate consumer group for each pipeline; each group tracks its own offset independently
Why this is correct
With three consumer groups, each pipeline reads the full stream from its own position. The archiving pipeline, aggregation pipeline, and ML pipeline each checkpoint independently. If one falls behind or restarts, it resumes from its own saved offset without disturbing the others.
- ✗
Create three separate Event Hubs in the same namespace and replicate events between them with Event Hubs Capture
Why it's wrong here
Event Hubs Capture writes events to Azure Storage or Data Lake in Avro format for cold archival — it is not a replication mechanism between Event Hubs. Creating three separate hubs with event replication would add latency, cost, and management overhead unnecessarily.
- ✗
Use a single consumer group and route events to different pipelines by partition key prefix
Why it's wrong here
A single consumer group allows only one active consumer per partition. If three pipelines share a consumer group, they must coordinate or one consumes events and the others miss them. Consumer groups, not partition key filtering, are the correct mechanism for multiple independent consumers.
- ✗
Enable Event Hubs Capture for all three pipelines so they read from the captured Avro files in storage instead of the Event Hub directly
Why it's wrong here
Capture is an archival feature. Reading from captured Avro files in storage introduces significant latency and requires the ML and aggregation pipelines to read flat files rather than a streaming endpoint. It defeats the real-time purpose of Event Hubs for those consumers.
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