Your company runs one batch process in an on-premises server that takes around 30 hours to complete. The task runs monthly, can be performed offline, and must be restarted if interrupted.
You want to migrate this workload to the cloud while minimizing cost. What should you do?

• A. Migrate the workload to a Google Kubernetes Engine cluster with Spot nodes.
• B. Migrate the workload to a Compute Engine Spot VM.
• C. Migrate the workload to a Compute Engine VM. Start and stop the instance as needed.
• D. Create an Instance Template with Spot VMs On. Create a Managed Instance Group from the template and adjust Target CPU Utilization. Migrate the workload.

You assist different engineering teams in deploying their infrastructure on Google Cloud. Your company has defined certain practices required for all workloads. You need to provide the engineering teams with a solution that enables teams to deploy their infrastructure independently without having to know all implementation details of the company's required practices. What should you do?

• A. Provide training for all engineering teams you work with to understand the company's required practices. Allow the engineering teams to provision the infrastructure to best meet their needs.
• B. Configure organization policies to enforce your company's required practices. Ask the teams to provision their infrastructure by using the Google Cloud console.
• C. Write Terraform modules for each component that are compliant with the company's required practices, and ask teams to implement their infrastructure through these modules.
• D. Create a service account per team, and grant the service account the Project Editor role. Ask the teams to provision their infrastructure through the Google Cloud CLI (gcloud CLI), while impersonating their dedicated service account.

You have a batch workload that runs every night and uses a large number of virtual machines (VMs). It is fault-tolerant and can tolerate some of the VMs being terminated. The current cost of VMs is too high.
What should you do?

• A. Run a test using simulated maintenance events.
  If the test is successful, use N1 Standard VMs when running future jobs.
• B. Run a test using N1 standard VMs instead of N2.
  If the test is successful, use N1 Standard VMs when running future jobs.
• C. Run a test using simulated maintenance events.
  If the test is successful, use preemptible N1 Standard VMs when running future jobs.
• D. Run a test using a managed instance group.
  If the test is successful, use N1 Standard VMs in the managed instance group when running future jobs.

You create a Deployment with 2 replicas in a Google Kubernetes Engine cluster that has a single preemptible node pool. After a few minutes, you use kubectlto examine the status of your Pod and observe that one of them is still in Pendingstatus:

What is the most likely cause?

• A. The pending Pod's resource requests are too large to fit on a single node of the cluster.
• B. The node pool is configured with a service account that does not have permission to pull the container image used by the pending Pod.
• C. The pending Pod was originally scheduled on a node that has been preempted between the creation of the Deployment and your verification of the Pods' status. It is currently being rescheduled on a new node.
• D. Too many Pods are already running in the cluster, and there are not enough resources left to schedule the pending Pod.

Your company uses BigQuery to store and analyze data. Upon submitting your query in BigQuery, the query fails with a quotaExceeded error. You need to diagnose the issue causing the error. What should you do? (Choose two.)

• A. Configure Cloud Trace to analyze the issue.
• B. View errors in Cloud Monitoring to analyze the issue.
• C. Search errors in Cloud Audit Logs to analyze the issue.
• D. Use BigQuery BI Engine to analyze the issue.
• E. Use the INFORMATION_SCHEMA views to analyze the underlying issue.