- A
currentLowWatermark
Why wrong: Event time progress, not backpressure.
- B
busyTimeMsPerSecond
High busy time indicates operator is overloaded, causing backpressure.
- C
numberOfFailedCheckpoints
Why wrong: Checkpoint failures may be a symptom but not a direct measure of backpressure.
- D
numRecordsInPerSecond
Why wrong: Throughput metric, not directly indicates backpressure.
Question 647 of 1,755
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is using Amazon Kinesis Data Analytics for Apache Flink to process real-time data. The data source is a Kinesis data stream, and the output is written to an S3 bucket. Recently, the processing latency has increased significantly. The team suspects that the Flink application is encountering backpressure. Which metric should the team monitor to confirm backpressure?
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
✓
busyTimeMsPerSecond
The correct metric to confirm backpressure in a Flink application is `busyTimeMsPerSecond`. This metric measures the percentage of time a task is actively processing data versus waiting for input. A high `busyTimeMsPerSecond` value (close to 1000ms) indicates that the task is fully utilized and cannot keep up with the incoming data rate, which is the direct symptom of backpressure. Other metrics like `currentLowWatermark` relate to event time progress, not backpressure.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
currentLowWatermark
Why it's wrong here
Event time progress, not backpressure.
- ✓
busyTimeMsPerSecond
Why this is correct
High busy time indicates operator is overloaded, causing backpressure.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
numberOfFailedCheckpoints
Why it's wrong here
Checkpoint failures may be a symptom but not a direct measure of backpressure.
- ✗
numRecordsInPerSecond
Why it's wrong here
Throughput metric, not directly indicates backpressure.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse `currentLowWatermark` (event time progress) with backpressure detection, or they assume that a high input rate (`numRecordsInPerSecond`) automatically means backpressure, but backpressure is about the operator's inability to keep up, not just the volume of data.
Detailed technical explanation
How to think about this question
Under the hood, `busyTimeMsPerSecond` is computed by Flink's task manager by measuring the time the operator thread spends in the `processElement()` method versus waiting for input from the network buffer. In a real-world scenario, if you see `busyTimeMsPerSecond` consistently above 900ms, it means the operator is saturated and backpressure is propagating upstream. This metric is more reliable than output rate or checkpoint failures because it directly reflects CPU utilization on the processing thread.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
What to study next
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: busyTimeMsPerSecond — The correct metric to confirm backpressure in a Flink application is `busyTimeMsPerSecond`. This metric measures the percentage of time a task is actively processing data versus waiting for input. A high `busyTimeMsPerSecond` value (close to 1000ms) indicates that the task is fully utilized and cannot keep up with the incoming data rate, which is the direct symptom of backpressure. Other metrics like `currentLowWatermark` relate to event time progress, not backpressure.
What should I do if I get this MLS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This MLS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLS-C01 exam.
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