The answer is that the DataAnalysisStartTime and DataAnalysisEndTime parameters are set to a past date, causing the monitoring schedule to find no new data to analyze. SageMaker Model Monitor uses these two parameters to define the fixed time window for data analysis; when both timestamps are historical and have already passed, each hourly execution of the schedule scans that closed window and finds zero new records, so it produces no output to the specified S3 bucket. On the AWS Certified Machine Learning Engineer Associate MLA-C01 exam, this scenario tests your understanding that a monitoring schedule’s frequency (hourly) is independent of its analysis window—a common trap where candidates assume the schedule automatically analyzes the most recent data. Remember the key distinction: the schedule triggers the job, but the time window dictates what data is actually examined. A helpful memory tip is “Window before trigger”—if the window is in the past, the trigger finds nothing to output.
MLA-C01 Deployment and Orchestration of ML Workflows Practice Question
This MLA-C01 practice question tests your understanding of deployment and orchestration of ml workflows. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 machine learning engineer has configured a SageMaker Model Monitor schedule for data quality monitoring as shown in the exhibit. The schedule is set to run hourly. However, the engineer notices that the monitoring jobs are not producing output in the specified S3 bucket. What is the most likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The DataAnalysisStartTime and DataAnalysisEndTime are set to a past date, so no data is analyzed.
Option B is correct because the DataAnalysisStartTime and DataAnalysisEndTime parameters define the time window for which SageMaker Model Monitor analyzes data. When both are set to a past date that has already passed, the monitoring job finds no new data to analyze within that window, resulting in no output being written to the S3 bucket. The schedule runs hourly, but the analysis window is fixed to a historical period, so each execution produces no results.
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.
✗
The output_path is incorrectly placed; it should be under the MonitoringOutputConfig.
Why it's wrong here
The output_path is placed in the Environment, which is acceptable; however, that may not be the cause of missing output.
✓
The DataAnalysisStartTime and DataAnalysisEndTime are set to a past date, so no data is analyzed.
Why this is correct
The monitoring job looks for data within the specified time range; if it's in the past and no data exists, no output is produced.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The MonitoringType should be 'ModelQuality' to enable data quality monitoring.
Why it's wrong here
'DataQuality' is a valid monitoring type for data quality.
✗
The cron expression is incorrectly formatted for an hourly schedule.
Why it's wrong here
The cron expression 'cron(0 * * * ? *)' is correct for running at the start of every hour.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often overlook the significance of the DataAnalysisStartTime and DataAnalysisEndTime parameters, assuming they are optional or default to the current time, when in fact they strictly define the data range and can cause silent failures if set to a past date.
Trap categories for this question
Command / output trap
The output_path is placed in the Environment, which is acceptable; however, that may not be the cause of missing output.
Detailed technical explanation
How to think about this question
SageMaker Model Monitor uses the DataAnalysisStartTime and DataAnalysisEndTime to constrain the data capture window for analysis. If these timestamps are in the past and the monitoring schedule runs repeatedly, each execution will process an empty time range (since no new data falls within the fixed past window), leading to no output. In practice, these parameters should be set to a rolling window (e.g., using the current time minus an offset) to ensure continuous monitoring of new data.
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.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Deployment and Orchestration of ML Workflows — This question tests Deployment and Orchestration of ML Workflows — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The DataAnalysisStartTime and DataAnalysisEndTime are set to a past date, so no data is analyzed. — Option B is correct because the DataAnalysisStartTime and DataAnalysisEndTime parameters define the time window for which SageMaker Model Monitor analyzes data. When both are set to a past date that has already passed, the monitoring job finds no new data to analyze within that window, resulting in no output being written to the S3 bucket. The schedule runs hourly, but the analysis window is fixed to a historical period, so each execution produces no results.
What should I do if I get this MLA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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