PMLE Practice Question: Collaborating Within and Across Teams to Manage Data and Models
A company uses Vertex AI Pipelines to orchestrate ML workflows. After a pipeline run, they want to query the lineage of a particular model artifact to find out which dataset and hyperparameters were used to produce it. Which API method should they use?
⚠ Common exam trap
PMLE often tests the difference between a single-node lookup (artifacts.get) and a graph traversal (queryArtifactLineageSubgraph) — candidates pick the simpler get method and miss that lineage requires traversing relationships.
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
✓
projects.locations.metadataStores.artifacts.queryArtifactLineageSubgraph
The queryArtifactLineageSubgraph method returns the lineage subgraph for a given artifact, showing the executions, contexts, and other artifacts connected to it — exactly what is needed to trace which dataset and hyperparameters produced a model. It traverses both upstream (inputs) and downstream (outputs) relationships in the metadata store.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
projects.locations.metadataStores.artifacts.queryArtifactLineageSubgraph
Why this is correct
queryArtifactLineageSubgraph traverses the metadata store's lineage graph in both directions from a given artifact, returning the executions and artifacts that produced or consumed it. This directly satisfies the requirement to trace a model artifact back to its source dataset and hyperparameters.
- ✗
projects.locations.metadataStores.artifacts.get
Why it's wrong here
artifacts.get retrieves an artifact's own metadata and state; it does not traverse lineage edges, so it cannot reveal the producing dataset or hyperparameters. It is tempting because it directly addresses the named model artifact, and would be correct when you only need that artifact's properties.
- ✗
projects.locations.metadataStores.contexts.addContextArtifactsAndExecutions
Why it's wrong here
addContextArtifactsAndExecutions writes links between contexts, artifacts and executions; it creates lineage rather than reading it, so it cannot retrieve the dataset and hyperparameters behind a model. It is tempting when building or backfilling lineage graphs, where attaching artifacts to a context is exactly the required operation.
- ✗
projects.locations.metadataStores.executions.queryExecutionInputsAndOutputs
Why it's wrong here
queryExecutionInputsAndOutputs returns the artifacts consumed and produced by an execution, which identifies the dataset but not the hyperparameters recorded as execution parameters. It is tempting because it traverses lineage from an execution, and would be correct when only input and output artifacts are needed.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
This PMLE practice question is part of Courseiva's free Google Cloud 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 PMLE exam.