Objective 5.2

PMLE

Automating model retraining

Objective 5.2 sits in Automating and orchestrating ML pipelines, which carries 18% of the ML Engineer exam. The questions below are original, written from the official objective title above, and each explanation cites the Google Cloud page it rests on.

Objective title verbatim from the official objectives. Google Cloud exam page

A worked example

Shown solved, with the whole explanation open: this is what every question here carries.

5-2Automating and orchestrating ML pipelines

A team pauses a nightly retraining schedule for a week and then resumes it. What decides whether the missed runs are submitted?

The end time set when the schedule was createdThe end time bounds the schedule, not the backlog.
A catch up parameter given when resumingCorrect · your answerCorrect. The decision is made at resume time.
The maximum concurrent run count on the scheduleConcurrency caps parallelism rather than backfilling.
The cron expression evaluated over the gapThe expression describes frequency, not history.

Correct.

Concept

A paused schedule leaves a hole, and there are two defensible things to do with it: pretend the time never passed, or make it up. Neither is always right, so the choice goes to whoever resumes.

Why B

A paused schedule does not create pipeline runs and can be resumed to become active again. On resuming, the catch_up parameter specifies whether skipped runs, the ones that would have been scheduled had the schedule been active, are rescheduled and submitted at the earliest possible schedule.

Source

PAUSED : A paused schedule doesn't create pipeline runs. You can resume a paused schedule to make it active again. When you resume a paused schedule, you can use the catch_up parameter to specify whether skipped runs (runs that would have been scheduled if the schedule had been active) need to be rescheduled and submitted at the earliest possible schedule.

Schedule a pipeline run with scheduler API, Agent Platform documentation, checked August 2026
#gcp#pipelines#scheduling#retraining

Now you: objective 5.2 questions

No account needed. The explanation opens when you answer.

Sample question 1 of 3

5-2Automating and orchestrating ML pipelines

An engineer creates a retraining schedule and leaves the end time unset. What happens once that schedule is running?

Sample question 2 of 3

5-2Automating and orchestrating ML pipelines

A team reaches the end time configured on a pipeline schedule and checks the schedule state afterwards. Which state does it hold?

Sample question 3 of 3

5-2Automating and orchestrating ML pipelines

A team copies a pipeline job request into a schedule template and includes an explicit job identifier in it. What does the scheduler do?

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Read the sources

These are the official pages the questions above cite. Reading them is studying the objective from the primary source, which is what the explanations point you toward anyway.

More objectives in Automating and orchestrating ML pipelines