You are deploying a containerized application to GKE. You have set up a build pipeline by using Cloud Build that builds a Java application and pushes the application container image to Artifact Registry. Your build pipeline executes multiple sequential steps that reference Docker container images with the same layers. You notice that the Cloud Build pipeline runs are taking longer than expected to complete. How should you optimize the Docker image build process?
You have an on-premises containerized service written in the current stable version of Python 3 that is available only to users in the United States. The service has high traffic during the day and no traffic at night. You need to migrate this application to Google Cloud and track error logs after the migration in Error Reporting. You want to minimize the cost and effort of these tasks. What should you do?
You deployed a new application to Google Kubernetes Engine and are experiencing some performance degradation. Your logs are being written to Cloud Logging, and you are using a Prometheus sidecar model for capturing metrics. You need to correlate the metrics and data from the logs to troubleshoot the performance issue and send real-time alerts while minimizing costs. What should you do?
You migrated your applications to Google Cloud Platform and kept your existing monitoring platform. You now find that your notification system is too slow for time critical problems.
What should you do?
You need to copy directory local-scripts and all of its contents from your local workstation to a Compute Engine virtual machine instance.
Which command should you use?
gsutil cp --project "my-gcp-project" -r ~/local-scripts/ gcp-instance-name:~/
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