Your company uses Azure Stream Analytics to monitor devices.
The company plans to double the number of devices that are monitored.
You need to monitor a Stream Analytics job to ensure that there are enough processing resources to handle the additional load.
Which metric should you monitor?

A. Input Deserialization Errors

B. Early Input Events

C. Late Input Events

D. Watermark delay








 

Suggested Answer: D

There are a number of other resource constraints that can cause the streaming pipeline to slow down. The watermark delay metric can rise due to:
✑ Not enough processing resources in Stream Analytics to handle the volume of input events.
✑ Not enough throughput within the input event brokers, so they are throttled.
✑ Output sinks are not provisioned with enough capacity, so they are throttled. The possible solutions vary widely based on the flavor of output service being used.
Incorrect Answers:
A: Deserialization issues are caused when the input stream of your Stream Analytics job contains malformed messages.
Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-time-handling

This question is in DP-200 Microsoft Azure Data Engineer Exam
For getting Microsoft Certified: Azure Data Engineer Associate Certificate



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