Topic 1 Question 279
You are creating an ML pipeline for data processing, model training, and model deployment that uses different Google Cloud services. You have developed code for each individual task, and you expect a high frequency of new files. You now need to create an orchestration layer on top of these tasks. You only want this orchestration pipeline to run if new files are present in your dataset in a Cloud Storage bucket. You also want to minimize the compute node costs. What should you do?
Create a pipeline in Vertex AI Pipelines. Configure the first step to compare the contents of the bucket to the last time the pipeline was run. Use the scheduler API to run the pipeline periodically.
Create a Cloud Function that uses a Cloud Storage trigger and deploys a Cloud Composer directed acyclic graph (DAG).
Create a pipeline in Vertex AI Pipelines. Create a Cloud Function that uses a Cloud Storage trigger and deploys the pipeline.
Deploy a Cloud Composer directed acyclic graph (DAG) with a GCSObjectUpdateSensor class that detects when a new file is added to the Cloud Storage bucket.
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- 正解だと思う選択肢: C
Option C appears to be the best choice for balancing the requirements of efficient orchestration, cost minimization, and ensuring the pipeline only runs when new files are present. By using a Cloud Function triggered by Cloud Storage events to deploy a Vertex AI Pipeline, you can leverage the event-driven model of Cloud Functions to minimize unnecessary runs and associated costs, while still using the powerful orchestration capabilities of Vertex AI Pipelines.
👍 5fitri0012024/05/26 - 正解だと思う選択肢: C
C
Cloud Function to be triggered by Cloud storage trigger, and then deploy the Vertex AI pipeline.
👍 3Yan_X2024/03/08 Probably C because while D would be good, it specifically says to minimize compute costs which cloud composer does incur whereas C is more serverless.
👍 2juliorevk2024/11/17
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