Practice Test 2 | Google Cloud Certified Professional Data Engineer | Dumps | Mock Test
You need to deploy a machine learning model built by data science team in the firm you work for. As a data engineer, you will be responsible of monitoring the health and traffic of the hosted model on the cloud. Some jobs could fail due to several reasons and you should be able to alert data scientists of such failed jobs.
Which of the following approaches is best to implement on Google Cloud?
A. Use Cloud Machine Learning Engine (now called Cloud AI Platform) to host the model. Use Stackdriver to monitor the status of jobs for ‘failed’ status.
B. Use Google Kubernetes Engine to host the model. Use Stackdriver to monitor the status of jobs for ‘failed’ status.
C. Use AutoML Vision to host the model. Use Stackdriver to monitor the status of jobs for ‘failed’ status.
D. Use Google Kubernetes Engine to host the model. Use Stackdriver to monitor the status of operations for ‘error’ status.
Answer: A.
Google Kubernetes Engine is a managed, production-ready environment for deploying containerized applications. It brings our latest innovations in developer productivity, resource efficiency, automated operations, and open source flexibility to accelerate your time to market.
Cloud Machine Learning Engine (now called Cloud AI Platform) is a managed service that lets developers and data scientists build and run superior machine learning models in production. Cloud ML Engine offers training and prediction services, which can be used together or individually.
Google AutoML Vision automates the training of your own custom machine learning (now called Cloud AI Platform) models by simply uploading images and training custom image models with an easy-to-use graphical interface.
In this scenario, You should use Google Machine Learning Engine (now called Cloud AI Platform) to deploy the model to the cloud. So, answers B, C & D are incorrect.
Source(s):
Google AutoML: https://cloud.google.com/automl/
Google Machine Learning Engine: (now called Cloud AI Platform) https://cloud.google.com/ml-engine/
Google Kubernetes Engine: https://cloud.google.com/kubernetes-engine/
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