Google Certified Professional - Cloud Architect (GCP) : Professional-Cloud-Architect

  • Exam Code: Professional-Cloud-Architect
  • Exam Name: Google Certified Professional - Cloud Architect (GCP)
  • Updated: Nov 09, 2026     Q & A: 353 Questions and Answers

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How much Google Professional Cloud Architect Exam cost

Google Professional Cloud Architect exam cost is $200 USD

Reference: https://cloud.google.com/certification/cloud-architect

Ensuring Operations and Solution Reliability

  • Evaluate quality control measures.
  • Deploy and release management;
  • Monitor, log, profile, and alert solutions;
  • Assist with solutions support within the operation;

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Managing & Provisioning Solution Infrastructures

  • Configure individual storage systems: the areas of focus should include data storage allocation; access management and security; data processing and compute provisioning; data lifecycle management and data retention; network configuration for the data latency and transfer;
  • Configure compute systems: you should understand system provisioning; compute volatility configuration; container orchestration using Kubernetes; technology configuration for infrastructure provisioning; network configuration for the compute nodes.
  • Configure network topologies: the examinees should have the ability to extend to hybrid and on-premises networking and multi-Cloud environment that may entail GCP to GCP communication. It also requires their understanding of data protection and security;

Google Professional Cloud Architect Practice Test Questions, Google Professional Cloud Architect Exam Practice Test Questions

The Google Professional Cloud Architect certification equips the individuals with the ability to leverage Google Cloud technologies for their organizations. It offers the potential candidates an extensive understanding of Google Cloud Platform and Cloud architecture in general. Earning this certificate is a great way to grow your career in the ever-growing Cloud domain.

Google Professional-Cloud-Architect Exam Syllabus Topics:

SectionObjectives
Topic 1: Manage and provision the solution infrastructure- Automate infrastructure deployment
- Provision compute, storage, and network resources
Topic 2: Analyze and optimize technical and business processes- Optimize cost and resource usage
- Monitor, log, and optimize system performance
Topic 3: Design and plan a cloud solution architecture- Design Google Cloud solutions based on business requirements
- Plan security and compliance requirements
- Design for reliability, scalability, and availability
Topic 4: Design for security and compliance- Implement identity and access management (IAM)
- Configure data protection and encryption
Topic 5: Manage implementations of cloud architecture- Ensure solution reliability and operational excellence
- Manage deployment and production systems

Google Certified Professional - Cloud Architect (GCP) Sample Questions:

Question #1

You are migrating third-party applications from optimized on-premises virtual machines to Google Cloud.
You are unsure about the optimum CPU and memory options. The application have a consistent usage patterns across multiple weeks. You want to optimize resource usage for the lowest cost. What should you do?

  • A. Create an instance template with the smallest available machine type, and use an image of the third party application taken from the current on-premises virtual machine. Create a managed instance group that uses average CPU to autoscale the number of instances in the group. Modify the average CPU utilization threshold to optimize the number of instances running.
  • B. Create an App Engine flexible environment, and deploy the third party application using a Docker file and a custom runtime. Set CPU and memory options similar to your application's current on-premises virtual machine in the app.yaml file.
  • C. Create a Compute engine instance with CPU and Memory options similar to your application's current on-premises virtual machine. Install the cloud monitoring agent, and deploy the third party application.
    Run a load with normal traffic levels on third party application and follow the Rightsizing Recommendations in the Cloud Console
  • D. Create multiple Compute Engine instances with varying CPU and memory options. Install the cloud monitoring agent and deploy the third-party application on each of them. Run a load test with high traffic levels on the application and use the results to determine the optimal settings.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #2

For this question, refer to the Mountkirk Games case study.
Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a thorough testing process for new versions of the backend before they are released to the public. You want the testing environment to scale in an economical way. How should you design the process?

  • A. Use the existing infrastructure to test the GCP-based backend at scale.
  • B. Build stress tests into each component of your application using resources internal to GCP to simulate load.
  • C. Create a scalable environment in GCP for simulating production load.
  • D. Create a set of static environments in GCP to test different levels of load - for example, high, medium, and low.
Reveal Solution  Discussion  0

Correct Answer: C  🗳️

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Question #3

Your operations team currently stores 10 TB of data m an object storage service from a third-party provider.
They want to move this data to a Cloud Storage bucket as quickly as possible, following Google- recommended practices. They want to minimize the cost of this data migration. When approach should they use?

  • A. Use the Storage Transfer Service to move the data
  • B. Download the data to a Transfer Appliance and ship it to Google
  • C. Use the gsutil mv command lo move the data
  • D. Download the data to the on-premises data center and upload it to the Cloud Storage bucket
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #4

A lead software engineer tells you that his new application design uses websockets and HTTP sessions that are not distributed across the web servers. You want to help him ensure his application will run property on Google Cloud Platform. What should you do?

  • A. Help the engineer redesign the application to use a distributed user session service that does not rely on websockets and HTTP sessions.
  • B. Review the encryption requirements for websocket connections with the security team.
  • C. Help the engineer to convert his websocket code to use HTTP streaming.
  • D. Meet with the cloud operations team and the engineer to discuss load balancer options.
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #5

You have a Python web application with many dependencies that requires 0.1 CPU cores and 128 MB of memory to operate in production. You want to monitor and maximize machine utilization. You also to reliably deploy new versions of the application. Which set of steps should you take?

  • A. Perform the following:
    1) Create a Kubernetes Engine (GKE) cluster with n1-standard-4 type machines.
    2) Build a Docker image from the master branch will all of the dependencies, and tag it with "latest".
    3) Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to "Always".
    Restart the pods to automatically deploy new production releases.
  • B. Perform the following:
    1) Create a managed instance group with n1-standard-1 type machines.
    2) Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
    3) Rebuild the Compute Engine image, and update the instance template to deploy new production releases.
  • C. Perform the following:
    1) Create a managed instance group with f1-micro type machines.
    2) Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
    3) Restart the instances to automatically deploy new production releases.
  • D. Perform the following:
    1) Create a Kubernetes Engine cluster with n1-standard-1 type machines.
    2) Build a Docker image from the production branch with all of the dependencies, and tag it with the version number.
    3) Create a Kubernetes Deployment with the imagePullPolicy set to "IfNotPresent" in the staging namespace, and then promote it to the production namespace after testing.
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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