PMLE Automating and Orchestrating ML Pipelines Practice Question
A team is building a CI/CD pipeline for an ML model. They want to automatically trigger a Vertex AI pipeline for retraining whenever new training data arrives in a Cloud Storage bucket, but only if a specific Pub/Sub notification is published by a data ingestion process. Which approach meets these requirements with minimal operational overhead?
⚠ Common exam trap
The trap here is that candidates may over-engineer the solution by choosing Dataflow (Option D) because it sounds 'streaming' and 'real-time', but the simplest serverless event-driven approach (Eventarc + Cloud Function) meets the requirement with minimal operational overhead.
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
✓
Use Eventarc to route the Pub/Sub notification to a Cloud Function that calls the Vertex AI pipeline creation API.
Eventarc can directly listen to a Pub/Sub topic and route matching messages to a Cloud Function, which then calls the Vertex AI pipeline creation API. This serverless approach triggers the pipeline only when the specific Pub/Sub notification is published, meeting the requirement with zero infrastructure to manage and no polling overhead.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Cloud Scheduler to run a job every hour that checks for new files in Cloud Storage and starts the pipeline if new files exist.
Why it's wrong here
Hourly polling introduces latency and misses the event-driven requirement, since the pipeline should fire on the specific Pub/Sub notification rather than on a schedule. Cloud Scheduler suits recurring batch jobs, not reacting to individual data-arrival events.
- ✗
Configure a Cloud Build trigger that listens to the Pub/Sub topic and executes a build step that submits the pipeline run.
Why it's wrong here
Cloud Build triggers listening to Pub/Sub alone cannot satisfy the requirement for new training data arriving in a Cloud Storage bucket. The scenario demands a dual condition: both the Pub/Sub notification and the data arrival must be present to trigger the Vertex AI pipeline. While Cloud Build is excellent for initiating CI/CD processes, such as code deployment or running tests, directly from Pub/Sub messages, it does not natively combine Pub/Sub and Cloud Storage event conditions into a single trigger for this specific orchestration.
- ✓
Use Eventarc to route the Pub/Sub notification to a Cloud Function that calls the Vertex AI pipeline creation API.
Why this is correct
Eventarc natively consumes Pub/Sub messages and delivers them to a Cloud Function, which then invokes the Vertex AI pipeline creation API. This event-driven path avoids polling or custom infrastructure, meeting the trigger condition with minimal operational overhead.
- ✗
Create a Dataflow streaming pipeline that reads from Pub/Sub and triggers the Vertex AI pipeline via a custom sink.
Why it's wrong here
Dataflow adds a continuously running streaming job to maintain, contradicting the minimal-operational-overhead requirement when Eventarc can route the Pub/Sub notification to the pipeline directly. Dataflow suits transforming high-volume streams, not acting as a lightweight trigger relay.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.