You work with a data engineering team that has developed a pipeline to clean your dataset and save it in a Cloud Storage bucket. You have created an ML model and want to use the data to refresh your model as soon as new data is available. As part of your CI/CD workflow, you want to automatically run a Kubeflow Pipelines training job on Google Kubernetes Engine (GKE). How should you architect this workflow?
Select one answer.
Marked answer: C
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Chose C1
C) PUB/sub trigger from Cloud Storage & Cloud Function
Chose C1
C - This is the google reccomended method.
Chose C1
C- because you don't want to re-engineer the pipeline
