An application development team believes their current logging tool will not meet their needs for their new cloud-based product. They want a bettor tool to capture errors and help them analyze their historical log data. You want to help them find a solution that meets their needs, what should you do?

• A.Send them a list of online resources about logging best practices.
• B.Help them define their requirements and assess viable logging tools.
• C.Help them upgrade their current tool to take advantage of any new features.
• D.Direct them to download and install the Google StackDriver logging agent.

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Your company is planning to upload several important files to Cloud Storage. After the upload is completed, they want to verify that the upload content is identical to what they have on- premises. You want to minimize the cost and effort of performing this check. What should you do?

• A.1) Use gsutil -m to upload all the files to Cloud Storage.
  2) Use gsutil cp to download the uploaded files
  3) Use Linux diff to compare the content of the files
• B.1) Use gsutil -m to upload all the files to Cloud Storage.
  2) Develop a custom Java application that computes CRC32C hashes
  3) Use gsutil ls -L gs://[YOUR_BUCKET_NAME] to collect CRC32C hashes of the uploaded files
  4) Compare the hashes
• C.1) Use Linux shasum to compute a digest of files you want to upload
  2) Use gsutil -m to upload all the files to the Cloud Storage
  3) Use gsutil cp to download the uploaded files
  4) Use Linux shasum to compute a digest of the downloaded files 5.Compre the hashes
• D.1) Use gsutil -m to upload all the files to Cloud Storage.
  2) Use gsutil hash -c FILE_NAME to generate CRC32C hashes of all on-premises files
  3) Use gsutil ls -L gs://[YOUR_BUCKET_NAME] to collect CRC32C hashes of the uploaded files
  4) Compare the hashes

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For this question, refer to the Dress4Win case study. You want to ensure that your on-premises
architecture meets business requirements before you migrate your solution.
What change in the on-premises architecture should you make?

• A.Replace RabbitMQ with Google Pub/Sub.
• B.Downgrade MySQL to v5.7, which is supported by Cloud SQL for MySQL.
• C.Resize compute resources to match predefined Compute Engine machine types.
• D.Containerize the micro services and host them in Google Kubernetes Engine.

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You have an application deployed on Kubernetes Engine using a Deployment named echo-deployment. The deployment is exposed using a Service called echo-service. You need to perform an update to the application with minimal downtime to the application. What should you do?

• A.Use kubectl set image deployment/echo-deployment <new-image>
• B.Use the rolling update functionality of the Instance Group behind the Kubernetes cluster
• C.Update the deployment yaml file with the new container image. Use kubectl delete deployment/ echo-deployment and kubectl create -f <yaml-file>
• D.Update the service yaml file which the new container image. Use kubectl delete service/echoservice and kubectl create -f <yaml-file>

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You are working at a sports association whose members range in age from 8 to 30. The association collects a large amount of health data, such as sustained injuries. You are storing this data in BigQuery. Current legislation requires you to delete such information upon request of the subject. You want to design a solution that can accommodate such a request. What should you do?

• A.Use a unique identifier for each individual. Upon a deletion request, delete all rows from BigQuery with this identifier.
• B.When ingesting new data in BigQuery, run the data through the Data Loss Prevention (DLP) API to identify any personal information. As part of the DLP scan, save the result to Data Catalog. Upon a deletion request, query Data Catalog to find the column with personal information.
• C.Create a BigQuery view over the table that contains all dat
  a. Upon a deletion request, exclude the rows that affect the subject's data from this view. Use this view instead of the source table for all analysis tasks.
• D.Use a unique identifier for each individual. Upon a deletion request, overwrite the column with the unique identifier with a salted SHA256 of its value.

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