Your development team has installed a new Linux kernel module on the batch servers in Google Compute Engine (GCE) virtual machines (VMs) to speed up the nightly batch process. Two days after the installation,
50% of web application deployed in the same
nightly batch run. You want to collect details on the failure to pass back to the development team. Which three actions should you take? Choose 3 answers

• A.Use Stackdriver Logging to search for the module log entries.
• B.Read the debug GCE Activity log using the API or Cloud Console.
• C.Use gcloud or Cloud Console to connect to the serial console and observe the logs.
• D.Identify whether a live migration event of the failed server occurred, using in the activity log.
• E.Adjust the Google Stackdriver timeline to match the failure time, and observe the batch server metrics.
• F.Export a debug VM into an image, and run the image on a local server where kernel log messages will be displayed on the native screen.

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For this question, refer to the JencoMart case study.
The migration of JencoMart's application to Google Cloud Platform (GCP) is progressing too slowly. The infrastructure is shown in the diagram. You want to maximize throughput. What are three potential bottlenecks? (Choose 3 answers.)

• A.Fewer virtual machines (VMs) in GCP than on-premises machines
• B.A tier of Google Cloud Storage that is not suited for this task
• C.A copy command that is not suited to operate over long distances
• D.A single VPN tunnel, which limits throughput
• E.Complicated internet connectivity between the on-premises infrastructure and GCP
• F.A separate storage layer outside the VMs, which is not suited for this task

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Your team will start developing a new application using microservices architecture on Kubernetes Engine. As part of the development lifecycle, any code change that has been pushed to the remote develop branch on your GitHub repository should be built and tested automatically. When the build and test are successful, the relevant microservice will be deployed automatically in the development environment. You want to ensure that all code deployed in the development environment follows this process. What should you do?

• A.Have each developer install a pre-commit hook on their workstation that tests the code and builds the container when committing on the development branch. After a successful commit, have the developer deploy the newly built container image on the development cluster.
• B.Create a Cloud Build trigger based on the development branch to build a new container image and store it in Container Registry. Rely on Vulnerability Scanning to ensure the code tests succeed. As the final step of the Cloud Build process, deploy the new container image on the development cluster. Ensure only Cloud Build has access to deploy new versions.
• C.Create a Cloud Build trigger based on the development branch that tests the code, builds the container, and stores it in Container Registry. Create a deployment pipeline that watches for new images and deploys the new image on the development cluster. Ensure only the deployment tool has access to deploy new versions.
• D.Install a post-commit hook on the remote git repository that tests the code and builds the container when code is pushed to the development branch. After a successful commit, have the developer deploy the newly built container image on the development cluster.

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

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You write a Python script to connect to Google BigQuery from a Google Compute Engine virtual machine. The script is printing errors that it cannot connect to BigQuery. What should you do to fix the script?

• A.Install the latest BigQuery API client library for Python
• B.Run your script on a new virtual machine with the BigQuery access scope enabled
• C.Create a new service account with BigQuery access and execute your script with that user
• D.Install the bq component for gccloud with the command gcloud components install bq.

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