There is an Azure Stream Analytics pipeline in your environment.You are using a watermark delay metric for monitoring.
You see a sudden rise in the value of the watermark delay metric.
Which of the following can be a possible reason?
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A. B. C. D.Correct Answers: A, B and C
Watermark delay metric actually works by checking the job health and is agnostic to input and output patterns of job.
There are several reasons which can cause the increase in this metric.
When there is an increase in the volume of input events, the associated resources will not be enough to handle it eventually.
Resources need to be scaled up according to the reading of this metric.
There will be throttling when there is not enough throughput within the input event brokers or when there is not enough Capacity for provisioned output sinks.
Options A, B and C are correct:They are some of the reasons for the increase in the watermark delay metric.
To know more, please refer to the docs below:
The watermark delay metric is used in Azure Stream Analytics to track the progress of the stream processing. It is the difference between the maximum event time processed and the current time. The rise in the value of the watermark delay metric indicates a delay in processing events.
Out of the given options, option A can be a possible reason for the sudden rise in the watermark delay metric. When there are more input events than the resources allocated, the processing of events is delayed, and the watermark delay metric increases. This delay occurs because the system needs to wait for the resources to become available before it can process the incoming events.
Option B, i.e., not enough throughput within the input event brokers, can also cause delays in processing the events, but it would not directly impact the watermark delay metric. The watermark delay metric is affected by delays in processing events, and not by the rate at which events are ingested into the system.
Option C, i.e., not enough capacity for provisioned output sinks, is also not directly related to the watermark delay metric. The output sinks represent the final destination of the processed events, and the delay in processing events may result in a backlog of data to be sent to the output sinks. However, this backlog may not be reflected in the watermark delay metric, as it only tracks the progress of the stream processing.
Therefore, the correct answer is A, i.e., more input events and fewer resources.