Professional Cloud Architect Free Practice Questions — Page 14
Question 127
Your development team has created a mobile game app. You want to test the new mobile app on Android and iOS devices with a variety of configurations. You need to ensure that testing is efficient and cost-effective. What should you do?
A. Upload your mobile app to the Firebase Test Lab, and test the mobile app on Android and iOS devices.
B. Create Android and iOS VMs on Google Cloud, install the mobile app on the VMs, and test the mobile app.
C. Create Android and iOS containers on Google Kubernetes Engine (GKE), install the mobile app on the containers, and test the mobile app.
D. Upload your mobile app with different configurations to Firebase Hosting and test each configuration.
Show Answer
Correct Answer: A
Explanation: Firebase Test Lab is a managed, cloud-based testing service specifically designed for mobile apps. It allows you to test Android and iOS apps on a wide range of real devices and configurations efficiently and cost-effectively. The other options are impractical or unsupported for mobile OS testing (VMs, containers, or Firebase Hosting are not suitable for realistic mobile device testing).
Question 128
Your company is developing a new application that will allow globally distributed users to upload pictures and share them with other selected users. The application will support millions of concurrent users. You want to allow developers to focus on just building code without having to create and maintain the underlying infrastructure. Which service should you use to deploy the application?
A. App Engine
B. Cloud Endpoints
C. Compute Engine
D. Google Kubernetes Engine
Show Answer
Correct Answer: A
Explanation: The key requirement is that developers can focus only on writing code without creating or maintaining infrastructure, while supporting massive scale. App Engine is a fully managed PaaS that handles provisioning, scaling, load balancing, and availability automatically. Compute Engine and Google Kubernetes Engine require infrastructure and operational management, and Cloud Endpoints is only an API management service, not a deployment platform. Therefore, App Engine best fits the scenario.
Question 129
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?
A. Configure Cloud NAT on the subnet where the instance is hosted. Create an SSH connection to the Cloud NAT IP address to reach the instance.
B. Add all instances to an unmanaged instance group. Configure TCP Proxy Load Balancing with the instance group as a backend. Connect to the instance using the TCP Proxy IP.
C. Configure Identity-Aware Proxy (IAP) for the instance and ensure that you have the role of IAP-secured Tunnel User. Use the gcloud command line tool to ssh into the instance.
D. Create a bastion host in the network to SSH into the bastion host from your office location. From the bastion host, SSH into the desired instance.
Show Answer
Correct Answer: C
Explanation: Instances must not have public IPs and there is no VPN from the office. Identity-Aware Proxy (IAP) TCP forwarding allows SSH access to a specific VM over an authenticated, encrypted tunnel without exposing the VM to the public internet or requiring a bastion host. Cloud NAT does not support inbound SSH, load balancing is inappropriate for admin access, and a bastion host would itself need a public IP, violating the requirement.
Question 130
Your development teams release new versions of games running on Google Kubernetes Engine (GKE) daily. You want to create service level indicators (SLIs) to evaluate the quality of the new versions from the user's perspective. What should you do?
A. Create CPU Utilization and Request Latency as service level indicators.
B. Create GKE CPU Utilization and Memory Utilization as service level indicators.
C. Create Request Latency and Error Rate as service level indicators.
D. Create Server Uptime and Error Rate as service level indicators.
Show Answer
Correct Answer: C
Explanation: Service level indicators should reflect user-perceived quality rather than internal system health. From a user’s perspective, the most important factors are whether requests succeed and how long they take. Request latency captures responsiveness, and error rate captures failed interactions. CPU, memory, or uptime are internal or coarse metrics that do not directly represent user experience.
Question 132
Mountkirk Games wants to limit the physical location of resources to their operating Google Cloud regions. What should you do?
A. Configure an organizational policy which constrains where resources can be deployed.
B. Configure IAM conditions to limit what resources can be configured.
C. Configure the quotas for resources in the regions not being used to 0.
D. Configure a custom alert in Cloud Monitoring so you can disable resources as they are created in other regions.
Show Answer
Correct Answer: A
Explanation: To restrict where Google Cloud resources can be physically created, you should use Organization Policy Service location constraints. An organization policy can explicitly allow or deny specific regions or locations for supported services, enforcing the restriction proactively at creation time. IAM conditions, quotas, or monitoring alerts do not reliably prevent resource creation in disallowed regions.
Question 133
Your team is developing a web application that will be deployed on Google Kubernetes Engine (GKE). Your CTO expects a successful launch and you need to ensure your application can handle the expected load of tens of thousands of users. You want to test the current deployment to ensure the latency of your application stays below a certain threshold. What should you do?
A. Use a load testing tool to simulate the expected number of concurrent users and total requests to your application, and inspect the results.
B. Enable autoscaling on the GKE cluster and enable horizontal pod autoscaling on your application deployments. Send curl requests to your application, and validate if the auto scaling works.
C. Replicate the application over multiple GKE clusters in every Google Cloud region. Configure a global HTTP(S) load balancer to expose the different clusters over a single global IP address.
D. Use Cloud Debugger in the development environment to understand the latency between the different microservices.
Show Answer
Correct Answer: A
Explanation: The goal is to verify that the current GKE deployment can handle tens of thousands of users while keeping latency below a defined threshold. The correct way to validate this is to perform load testing that simulates realistic concurrent users and request volumes and then measure latency and error rates. Autoscaling or multi‑region deployment are implementation choices, not validation methods, and Cloud Debugger is for code inspection, not performance testing. Therefore, using a load testing tool is the appropriate approach.
Question 134
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. 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.
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. 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.
Show Answer
Correct Answer: C
Explanation: The requirement is an automated CI/CD process that triggers on pushes to the develop branch, runs tests, builds container images, and deploys successfully tested code automatically to the development environment, while preventing manual or bypassed deployments. A Cloud Build trigger satisfies this by centrally enforcing build and test steps. Separating build from deployment with a deployment pipeline that watches for new images and restricting deploy permissions ensures only validated artifacts are deployed. Options A and B rely on developer actions and cannot guarantee enforcement. Option D is incorrect because vulnerability scanning does not replace running tests.
Question 135
You are moving an application that uses MySQL from on-premises to Google Cloud. The application will run on Compute Engine and will use Cloud SQL. You want to cut over to the Compute Engine deployment of the application with minimal downtime and no data loss to your customers. You want to migrate the application with minimal modification. You also need to determine the cutover strategy. What should you do?
A. 1. Set up Cloud VPN to provide private network connectivity between the Compute Engine application and the on-premises MySQL server. 2. Stop the on-premises application. 3. Create a mysqldump of the on-premises MySQL server. 4. Upload the dump to a Cloud Storage bucket. 5. Import the dump into Cloud SQL. 6. Modify the source code of the application to write queries to both databases and read from its local database. 7. Start the Compute Engine application. 8. Stop the on-premises application.
B. 1. Set up Cloud SQL proxy and MySQL proxy. 2. Create a mysqldump of the on-premises MySQL server. 3. Upload the dump to a Cloud Storage bucket. 4. Import the dump into Cloud SQL. 5. Stop the on-premises application. 6. Start the Compute Engine application.
C. 1. Set up Cloud VPN to provide private network connectivity between the Compute Engine application and the on-premises MySQL server. 2. Stop the on-premises application. 3. Start the Compute Engine application, configured to read and write to the on-premises MySQL server. 4. Create the replication configuration in Cloud SQL. 5. Configure the source database server to accept connections from the Cloud SQL replica. 6. Finalize the Cloud SQL replica configuration. 7. When replication has been completed, stop the Compute Engine application. 8. Promote the Cloud SQL replica to a standalone instance. 9. Restart the Compute Engine application, configured to read and write to the Cloud SQL standalone instance.
D. 1. Stop the on-premises application. 2. Create a mysqldump of the on-premises MySQL server. 3. Upload the dump to a Cloud Storage bucket. 4. Import the dump into Cloud SQL. 5. Start the application on Compute Engine.
Show Answer
Correct Answer: C
Explanation: The requirement is minimal downtime, no data loss, and minimal application changes. Dump-and-restore options (A, B, D) require stopping writes for the duration of the dump and import, which causes significant downtime and risk. Option C uses an external replica promotion strategy: the on‑premises MySQL remains the primary while Cloud SQL is set up as a replica over VPN. The application is first moved to Compute Engine without changing its database (still pointing to on‑prem), replication keeps Cloud SQL in sync, and at cutover the replica is promoted to primary with only a brief application restart. This achieves near‑zero downtime, no data loss, and minimal code changes.
Question 136
Your company is running its application workloads on Compute Engine. The applications have been deployed in production, acceptance, and development environments. The production environment is business-critical and is used 24/7, while the acceptance and development environments are only critical during office hours. Your CFO has asked you to optimize these environments to achieve cost savings during idle times. What should you do?
A. Create a shell script that uses the gcloud command to change the machine type of the development and acceptance instances to a smaller machine type outside of office hours. Schedule the shell script on one of the production instances to automate the task.
B. Use Cloud Scheduler to trigger a Cloud Function that will stop the development and acceptance environments after office hours and start them just before office hours.
C. Deploy the development and acceptance applications on a managed instance group and enable autoscaling.
D. Use regular Compute Engine instances for the production environment, and use preemptible VMs for the acceptance and development environments.
Show Answer
Correct Answer: B
Explanation: Acceptance and development environments are only needed during office hours, so the biggest cost savings come from not running them at all during idle times. Scheduling automatic stop/start of these VMs using Cloud Scheduler (or the built-in instance scheduling feature) ensures they are available when needed and incur zero compute cost outside office hours. Other options either add operational complexity, don’t guarantee shutdown, or introduce reliability risk without maximizing savings.
Question 137
You need to migrate Hadoop jobs for your company's Data Science team without modifying the underlying infrastructure. You want to minimize costs and infrastructure management effort. What should you do?
A. Create a Dataproc cluster using standard worker instances.
B. Create a Dataproc cluster using preemptible worker instances.
C. Manually deploy a Hadoop cluster on Compute Engine using standard instances.
D. Manually deploy a Hadoop cluster on Compute Engine using preemptible instances.
Show Answer
Correct Answer: B
Explanation: The goal is to migrate Hadoop jobs without changing infrastructure while minimizing cost and management effort. Using Google Cloud Dataproc avoids manual Hadoop cluster management, satisfying the low management requirement. To minimize costs, preemptible worker instances are preferred because they are significantly cheaper and suitable for typical Hadoop batch workloads that are fault-tolerant. Manually deploying Hadoop on Compute Engine increases operational overhead, so options C and D are inferior.
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