Objective 2.4

PCA

Leveraging Gemini Enterprise Agent Platform for end-to-end ML workflows

Objective 2.4 sits in Managing and provisioning a cloud solution infrastructure, which carries 17.5% of the Cloud Architect 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.

2-4Managing and provisioning a cloud solution infrastructure

A team trains a model on a framework version that has no prebuilt container image available, and the code depends on a private internal package. Which container approach does that call for?

A prebuilt image with extra dependencies namedAdditional packages can be named, but the base version is still fixed.
A prebuilt image running a single Python fileThat path is for prototyping inside a supported framework version.
A custom image with the dependencies pre-installedCorrect · your answerCorrect. You build the environment, so anything can be in it.
A Python source distribution in a bucketSource distributions are still installed into a prebuilt image.

Correct.

Concept

A managed runtime supplies a fixed set of environments, and the moment your dependencies fall outside that set you take over building the environment yourself, trading setup effort for control.

Why C

Custom container images are recommended for non-Python training applications, private or custom dependencies, and frameworks or framework versions with no prebuilt image, at a higher setup effort.

Source

The following table shows the differences between prebuilt and custom container images: Specifications Prebuilt container images Custom container images ML framework Each container image is specific to an ML framework. Use any ML framework or use none. ML framework version Each container image is specific to an ML framework version. Use any ML framework version, including minor versions and nightly builds. Application dependencies Common dependencies for the ML framework are pre-installed. You can specify additional dependencies to install in your training application. Pre-install the…

Serverless training overview, Agent Platform documentation, checked August 2026
#gcp#ml-training#containers#mlops

Now you: objective 2.4 questions

No account needed. The explanation opens when you answer.

Sample question 1 of 2

2-4Managing and provisioning a cloud solution infrastructure

A finance lead asks whether the virtual machines behind a managed training job stay allocated once the run finishes. What does the job do with them?

Sample question 2 of 2

2-4Managing and provisioning a cloud solution infrastructure

A team supplies a range of values for a model setting and wants the service to search that range rather than guessing one value. Which job type does that work?

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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 Managing and provisioning a cloud solution infrastructure