Event Hub旨在用于事件源/仅附加日志体系结构

Question

Event Hubs don't let you store messages longer than 7 (maybe up to 30) days. What is Azure's suggested architecture for PaaS Event Sourcing with these limitations? If it's Event Hub + snapshotting, what happens if we somehow need to rebuild that state? Additional, is Event Hub's answer to KSQL/Spark Azure Stream Analytics?

Answer 1

Great Question!

Yes, EventHubs is intended to be used for Event Sourcing or Append-only log pattern. EventHubs can be used as source/sink for stream processing & analytics engines like SPARK and hence not its competitor. In general, EventHubs offers similar capabilities as that of Apache Kafka.

& Yes, to implement rebuilding transactions from the append-only log Snapshotting is definitely the recommended approach!

While shaping EventHubs as a product offering, our considerations for assigning a default value for retentionPeriod - were -

• most of the critical systems create snapshots every few minutes.
• most of the design patterns around this suggest retaining older snapshots for rebuild

So, it was clear that we don't need infinite log, & a timebound of a day will do for most use-cases. Hence, we started with a default 1 day - and gave a knob until 7 days.

If you think, you would have a case, where you will have to go back in time for >7 days to rebuild a snapshot (for ex: for debugging - which is generally not a 99% scenario - but, agreed that designing & accommodating for this is very-wise), recommended approach is to push the data to an archival store.

When our usage Metrics showed that many of our customers have one EventHubs consumer group dedicated for pushing data to archival store - we wanted to enable this capability out-of-the-box & then started to offer - Event Hubs Capture feature .

More on Event Hubs.

Answer 2

Event Hubs are supposed to be used for temporarily storing events while moving them between the data storage instances. You would have to load them to some permanent storage to use for indefinite time period, eg Cosmos DB.

KSQL is somewhat comparable to Azure Stream Analytics. Spark is a much more broad product, but you can use Spark to process Event Hubs data.

PS I'm not an official speaker of Microsoft, so that's just my view.