GOOGLE-Professional Cloud Architect on Google Cloud Platform Set 4

1.

Your architecture calls for the centralized collection of all admin activity and VM system logs within your project.
How should you collect these logs from both VMs and services?

All admin and VM system logs are automatically collected by Stackdriver. Stackdriver automatically collects admin activity logs for most services. The Stackdriver Logging agent must be installed on each instance to collect system logs. Launch a custom syslogd compute instance and configure your GCP project and VMs to forward all logs to it. Install the Stackdriver Logging agent on a single compute instance and let it collect all audit and access logs for your environment.

2.

You have an App Engine application that needs to be updated. You want to test the update with production traffic before replacing the current application version.
What should you do?

Deploy the update using the Instance Group Updater to create a partial rollout, which allows for canary testing. Deploy the update as a new version in the App Engine application, and split traffic between the new and current versions. Deploy the update in a new VPC, and use Google's global HTTP load balancing to split traffic between the update and current applications. Deploy the update as a new App Engine application, and use Google's global HTTP load balancing to split traffic between the new and current applications.

3.

Your customer runs a web service used by e-commerce sites to offer product recommendations to users. The company has begun experimenting with a machine learning model on Google Cloud Platform to improve the quality of results.
What should the customer do to improve their model's results over time?

Export Cloud Machine Learning Engine performance metrics from Stackdriver to BigQuery, to be used to analyze the efficiency of the model. Build a roadmap to move the machine learning model training from Cloud GPUs to Cloud TPUs, which offer better results. Monitor Compute Engine announcements for availability of newer CPU architectures, and deploy the model to them as soon as they are available for additionalperformance. Save a history of recommendations and results of the recommendations in BigQuery, to be used as training data.

4.

A development team at your company has created a dockerized HTTPS web application. You need to deploy the application on Google Kubernetes Engine (GKE) and make sure that the application scales automatically.
How should you deploy to GKE?

Use the Horizontal Pod Autoscaler and enable cluster autoscaling. Use an Ingress resource to load-balance the HTTPS traffic. Use the Horizontal Pod Autoscaler and enable cluster autoscaling on the Kubernetes cluster. Use a Service resource of type LoadBalancer to load-balance theHTTPS traffic. Enable autoscaling on the Compute Engine instance group. Use an Ingress resource to load balance the HTTPS traffic. Enable autoscaling on the Compute Engine instance group. Use a Service resource of type LoadBalancer to load-balance the HTTPS traffic.

5.

Your company creates rendering software which users can download from the company website. Your company has customers all over the world. You want to minimize latency for all your customers. You want to follow Google-recommended practices.
How should you store the files?

Save the files in a Multi-Regional Cloud Storage bucket. Save the files in a Regional Cloud Storage bucket, one bucket per zone of the region. Save the files in multiple Regional Cloud Storage buckets, one bucket per zone per region. Save the files in multiple Multi-Regional Cloud Storage buckets, one bucket per multi-region.

GOOGLE-Professional Cloud Architect on Google Cloud Platform Set 4

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GOOGLE-Professional Cloud Architect on Google Cloud Platform Set 4

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OTHERS

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