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| Vendor: | |
|---|---|
| Exam Code: | Professional-Cloud-Architect |
| Exam Name: | Google Cloud Architect Professional |
| Exam Questions: | 334 |
| Last Updated: | May 22, 2026 |
| Related Certifications: | Google Cloud Certified |
| Exam Tags: | Professional and Advanced Level Google Cloud ArchitectsGoogle Cloud Administrators |
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You have deployed several instances on Compute Engine. As a security requirement, instances cannot have a public IP address. There is no VPN connection between Google Cloud and your office, and you need to connect via SSH into a specific machine without violating the security requirements. What should you do?
https://cloud.google.com/iap/docs/using-tcp-forwarding#tunneling_with_ssh
Leveraging the BeyondCorp security model. 'This January, we enhanced context-aware access capabilities in Cloud Identity-Aware Proxy (IAP) to help you protect SSH and RDP access to your virtual machines (VMs)---without needing to provide your VMs with public IP addresses, and without having to set up bastion hosts. ' https://cloud.google.com/blog/products/identity-security/cloud-iap-enables-context-aware-access-to-vms-via-ssh-and-rdp-without-bastion-hosts
Your company is expanding its AI-powered operations nationwide and has chosen accelerator-based compute for the AI workloads. The batch image processing workloads are not time-sensitive and can tolerate interruptions. You need to rapidly deploy cost-effective accelerator nodes for these batch tasks, ensuring data persistence when necessary. What should you do?
For batch processing workloads that are 'not time-sensitive' and 'can tolerate interruptions,' Spot VMs (formerly Preemptible VMs) are the Google-recommended best practice for cost optimization. Spot VMs offer the same performance as standard VMs (including support for GPUs and TPUs) at a discount of up to 91%.
However, because Spot VMs can be reclaimed by Google Cloud at any time, the architecture must be fault-tolerant. According to Vertex AI and Compute Engine best practices, using Persistent Disks (rather than Local SSDs, which are wiped upon VM termination) ensures that data is not lost when an instance is preempted. By implementing a checkpointing mechanism, the AI model periodically saves its state (weights, processed image metadata, etc.) to the persistent disk. When a new Spot VM is automatically provisioned by a Managed Instance Group to replace the preempted one, the application can resume from the last saved checkpoint rather than starting from the beginning.
Option C is less ideal because Local SSD data does not persist through preemption/reclamation cycles. Option B uses standard VMs, which fails the requirement for 'cost-effective' deployment. Option D perfectly balances the extreme cost savings of Spot provisioning with the reliability requirements of large-scale batch image processing.
Your web application uses Google Kubernetes Engine to manage several workloads. One workload requires a consistent set of hostnames even after pod scaling and relaunches.
Which feature of Kubernetes should you use to accomplish this?
https://kubernetes.io/docs/tutorials/stateful-application/basic-stateful-set/
Your organization has decided to restrict the use of external IP addresses on instances to only approved instances. You want to enforce this requirement across all of your Virtual Private Clouds (VPCs). What should you do?
https://cloud.google.com/compute/docs/ip-addresses/reserve-static-external-ip-address#disableexternalip
you might want to restrict external IP address so that only specific VM instances can use them. This option can help to prevent data exfiltration or maintain network isolation. Using an Organization Policy, you can restrict external IP addresses to specific VM instances with constraints to control use of external IP addresses for your VM instances within an organization or a project.
You are designing a central, automated infrastructure deployment process tor your organization using Terraform and Cloud Build The security team prohibits the use of long-lived, static service account keys in any CI/CD pipeline Additionally, while developers can propose infrastructure changes for peer review, they must not have permissions to directly apply changes in the production project. You need to design a secure and automated workflow for applying Terraform changes that meets the security team's requirements and ensures proper governance. What should you do?
Security best practices in Google Cloud dictate that you should avoid static JSON keys at all costs.
Impersonation: By using Service Account Impersonation (Option D), the Cloud Build service account 'acts as' a more privileged Terraform service account only during the build. This uses short-lived tokens that expire automatically.
Governance: Running terraform plan on a pull request allows peers to review the exact changes before they happen. Requiring a manual approval step for terraform apply ensures that a human gatekeeper validates the change before it impacts the production environment.
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