Your company runs a streaming job in Azure Stream Analytics that ingests data from Event Hubs and outputs to Azure Synapse Analytics. The job is failing with a 'Watermark delay' alert and the output to Synapse is delayed by over 30 minutes. The input rate is 5,000 events per second. The job uses a 1-minute tumbling window. What is the most likely cause of the delay?
Insufficient SUs cause backpressure and watermark delay.
Why this answer
A watermark delay alert in Azure Stream Analytics indicates that the job is falling behind in processing incoming data. With an input rate of 5,000 events per second and a 1-minute tumbling window, the job requires sufficient Streaming Units (SUs) to keep up. Under-provisioned SUs cause backpressure, leading to output delays exceeding 30 minutes.
Exam trap
The trap here is that candidates may confuse a watermark delay alert with late-arriving events (Option B), but the alert indicates the job is falling behind overall, not just handling late data, and the 30-minute delay points to insufficient compute resources rather than data timing issues.
How to eliminate wrong answers
Option A is wrong because a schema mismatch between Stream Analytics output and Synapse would cause data write errors or failures, not a watermark delay alert or a 30-minute output delay. Option B is wrong because a large number of late-arriving events would increase the watermark delay but the alert specifically indicates the job is falling behind overall processing, not just handling late data; late events are managed by the late arrival policy and do not inherently cause a 30-minute delay. Option C is wrong because a 1-minute tumbling window is small and appropriate for real-time analytics; a larger window would reduce processing frequency, not cause delay.