PDE System lag Practice Question
Your Dataflow streaming pipeline is experiencing increasing system lag over time. You have enabled autoscaling and the pipeline is using the default streaming engine. Which metric should you monitor in Cloud Monitoring to determine if the pipeline is falling behind due to slow processing or due to a bottleneck in the output sink?
⚠ Common exam trap
Candidates often assume System lag is the single metric for all delays, but to differentiate between processing and sink bottlenecks, you need to combine System lag with Data freshness.
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
✓
Data freshness
In Dataflow streaming pipelines, 'System lag' measures the maximum time an item waits to be processed, but it does not by itself distinguish between a processing bottleneck and a sink bottleneck. To differentiate, monitor 'Data freshness' (the time since the last output was written). If Data freshness is high while System lag is also high, the sink is likely the bottleneck. If System lag is high but Data freshness is low (recent output), the bottleneck is processing. Therefore, the metric that helps determine whether the pipeline is falling behind due to slow processing or a sink bottleneck is Data freshness.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Worker CPU utilization
Why it's wrong here
Worker CPU utilization can indicate if workers are overloaded but does not directly differentiate between processing and sink bottlenecks.
- ✗
System lag
Why it's wrong here
System lag reflects overall processing delay but increases regardless of whether the bottleneck is in processing or the sink; it cannot distinguish between the two.
- ✗
Element count
Why it's wrong here
Element count shows the number of elements processed but does not indicate where the delay occurs.
- ✓
Data freshness
Why this is correct
Data freshness (time since last output) directly indicates whether the sink is keeping up. High Data freshness suggests a sink bottleneck, while low Data freshness despite high System lag suggests a processing bottleneck.
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