Professional Cloud Architect Free Practice Questions — Page 8
Question 71
Your company has a Google Cloud project that uses BigQuery for data warehousing on a pay-per-use basis. You want to monitor queries in real time to discover the most costly queries and which users spend the most. What should you do?
A. 1. In the BigQuery dataset that contains all the tables to be queried, add a label for each user that can launch a query. 2. Open the Billing page of the project. 3. Select Reports. 4. Select BigQuery as the product and filter by the user you want to check.
B. 1. Create a Cloud Logging sink to export BigQuery data access logs to BigQuery. 2. Perform a BigQuery query on the generated table to extract the information you need.
C. 1. Create a Cloud Logging sink to export BigQuery data access logs to Cloud Storage. 2. Develop a Dataflow pipeline to compute the cost of queries split by users.
D. 1. Activate billing export into BigQuery. 2. Perform a BigQuery query on the billing table to extract the information you need.
Show Answer
Correct Answer: B
Explanation: Export BigQuery Data Access audit logs to BigQuery via a Cloud Logging sink, then query those logs. The audit logs include the user, job details, and bytes processed/billed information needed to estimate query cost in near real time, which matches the requirement to monitor costly queries and user spend. Billing export is intended for billing analysis but does not provide the same per-query, near-real-time operational visibility.
Question 72
Your company recently acquired a company that has infrastructure in Google Cloud. Each company has its own Google Cloud organization. Each company is using a Shared Virtual Private Cloud (VPC) to provide network connectivity for its applications. Some of the subnets used by both companies overlap. In order for both businesses to integrate, the applications need to have private network connectivity. These applications are not on overlapping subnets. You want to provide connectivity with minimal re-engineering. What should you do?
A. Set up VPC peering and peer each Shared VPC together.
B. Migrate the projects from the acquired company into your company's Google Cloud organization. Re-launch the instances in your companies Shared VPC.
C. Set up a Cloud VPN gateway in each Shared VPC and peer Cloud VPNs.
D. Configure SSH port forwarding on each application to provide connectivity between applications in the different Shared VPCs.
Show Answer
Correct Answer: C
Explanation: VPC Network Peering cannot be established if the VPCs have overlapping subnet IP ranges. Because the two companies have some overlapping subnets, option A is not viable even if the specific applications are on non-overlapping subnets. Establishing Cloud VPN between the Shared VPCs allows private connectivity, and you can exchange only the required non-overlapping routes. Migrating and relaunching workloads requires significant re-engineering, and SSH port forwarding is not an appropriate network integration solution.
Question 74
You are managing several projects on Google Cloud and need to interact on a daily basis with BigQuery, Bigtable, and Kubernetes Engine using the gcloud CL tool. You are travelling a lot and work on different workstations during the week. You want to avoid having to manage the gcloud CLI manually. What should you do?
A. Use Google Cloud Shell in the Google Cloud Console to interact with Google Cloud.
B. Create a Compute Engine instance and install gcloud on the instance. Connect to this instance via SSH to always use the same gcloud installation when interacting with Google Cloud.
C. Install gcloud on all of your workstations. Run the command gcloud components auto-update on each workstation
D. Use a package manager to install gcloud on your workstations instead of installing it manually.
Show Answer
Correct Answer: A
Explanation: Google Cloud Shell provides a browser-based, fully managed gcloud CLI that is preinstalled, kept up to date by Google, and includes support for common Google Cloud tools such as kubectl and BigQuery utilities. Because it is tied to your Google account and accessible from any workstation with a browser, it avoids manually installing and maintaining the CLI across multiple machines. Running your own Compute Engine VM or installing gcloud on every workstation still requires you to manage the environment.
Question 75
You have a Compute Engine managed instance group that adds and removes Compute Engine instances from the group in response to the load on your application. The instances have a shutdown script that removes REDIS database entries associated with the instance. You see that many database entries have not been removed, and you suspect that the shutdown script is the problem. You need to ensure that the commands in the shutdown script are run reliably every time an instance is shut down. You create a Cloud Function to remove the database entries. What should you do next?
A. Modify the shutdown script to wait for 30 seconds before triggering the Cloud Function.
B. Do not use the Cloud Function. Modify the shutdown script to restart if it has not completed in 30 seconds.
C. Set up a Cloud Monitoring sink that triggers the Cloud Function after an instance removal log message arrives in Cloud Logging.
D. Modify the shutdown script to wait for 30 seconds and then publish a message to a Pub/Sub queue.
Show Answer
Correct Answer: C
Explanation: The most reliable approach is to decouple the cleanup from the VM shutdown process. Shutdown scripts are best-effort and have no guaranteed execution window during instance termination. Triggering a Cloud Function based on the instance deletion/removal event recorded in Cloud Logging (typically via a log sink to Pub/Sub in practice) ensures the cleanup runs independently of the terminating VM. Options that depend on waiting in the shutdown script or publishing from the shutting-down instance still rely on the unreliable shutdown window.
Question 76
Your company and one of its partners each have a Google Cloud project in separate organizations. Your company's project (prj-a) runs in Virtual Private Cloud
(vpc-a). The partner's project (prj-b) runs in vpc-b. There are two instances running on vpc-a and one instance running on vpc-b. Subnets defined in both VPCs are not overlapping. You need to ensure that all instances communicate with each other via internal IPs, minimizing latency and maximizing throughput. What should you do?
A. Set up a network peering between vpc-a and vpc-b.
B. Set up a VPN between vpc-a and vpc-b using Cloud VPN.
C. Configure IAP TCP forwarding on the instance in vpc-b, and then launch the following gcloud command from one of the instances in vpc-a gcloud: gcloud compute start-iap-tunnel INSTANCE_NAME_IN_VPC_8 22 \ --local-host-port=localhost:22
D. 1. Create an additional instance in vpc-a. 2. Create an additional instance in vpc-b. 3. Install OpenVPN in newly created instances. 4. Configure a VPN tunnel between vpc-a and vpc-b with the help of OpenVPN.
Show Answer
Correct Answer: A
Explanation: VPC Network Peering is the preferred solution for connecting two Google Cloud VPC networks, including across different projects and different organizations, when subnet IP ranges do not overlap. It provides private internal IP connectivity over Google's backbone with lower latency and higher throughput than VPN. Cloud VPN adds encryption overhead and is intended when peering is not suitable. IAP TCP forwarding is for administrative access, not network connectivity between all instances, and self-managed OpenVPN is unnecessarily complex.
Question 77
Your company uses Google Kubernetes Engine (GKE) as a platform for all workloads. Your company has a single large GKE cluster that contains batch, stateful, and stateless workloads. The GKE cluster is configured with a single node pool with 200 nodes. Your company needs to reduce the cost of this cluster but does not want to compromise availability. What should you do?
A. Create a second GKE cluster for the batch workloads only. Allocate the 200 original nodes across both clusters.
B. Configure CPU and memory limits on the namespaces in the cluster. Configure all Pods to have a CPU and memory limits.
C. Configure a HorizontalPodAutoscaler for all stateless workloads and for all compatible stateful workloads. Configure the cluster to use node auto scaling.
D. Change the node pool to use preemptible VMs.
Show Answer
Correct Answer: C
Explanation: Horizontal Pod Autoscaling combined with GKE Cluster Autoscaler (node autoscaling) allows the cluster to scale pods and nodes up and down based on demand, reducing infrastructure cost while maintaining availability. Creating a second cluster does not reduce node costs, resource limits alone do not reduce the number of nodes, and using preemptible VMs for a mixed cluster with stateful workloads would compromise availability.
Question 78
Your company has an application running as a Deployment in a Google Kubernetes Engine (GKE) cluster. When releasing new versions of the application via a rolling deployment, the team has been causing outages. The root cause of the outages is misconfigurations with parameters that are only used in production. You want to put preventive measures for this in the platform to prevent outages. What should you do?
A. Configure liveness and readiness probes in the Pod specification.
B. Configure health checks on the managed instance group.
C. Create a Scheduled Task to check whether the application is available.
D. Configure an uptime alert in Cloud Monitoring.
Show Answer
Correct Answer: A
Explanation: Readiness probes prevent new Pods from receiving traffic until they are actually ready, which is critical during rolling updates when production-only configuration errors may prevent correct startup. Liveness probes help restart unhealthy containers. Health checks on the underlying managed instance group are not the mechanism for Kubernetes application rollout safety, and scheduled checks or uptime alerts only detect problems after they occur rather than preventing traffic from reaching unhealthy Pods.
Question 79
You are managing several internal applications that are deployed on Compute Engine. Business users inform you that an application has become very slow over the past few days. You want to find the underlying cause in order to solve the problem. What should you do first?
A. Inspect the logs and metrics from the instances in Cloud Logging and Cloud Monitoring.
B. Change the Compute Engine Instances behind the application to a machine type with more CPU and memory.
C. Restore a backup of the application database from a time before the application became slow.
D. Deploy the applications on a managed instance group with autoscaling enabled. Add a load balancer in front of the managed instance group, and have the users connect to the IP of the load balancer.
Show Answer
Correct Answer: A
Explanation: The first step in diagnosing a newly degraded application is to gather evidence. Cloud Logging and Cloud Monitoring provide logs, metrics, and resource utilization data to identify whether the issue is caused by CPU, memory, disk, network, application errors, or other factors. The other options are remediation actions that make changes without first determining the root cause.
Question 80
Your customer runs a web service used by e-commerce sites to offer product recommendations to users. The company has begun experimenting with a machine learning model on Google Cloud Platform to improve the quality of results.
What should the customer do to improve their model's results over time?
A. Export Cloud Machine Learning Engine performance metrics from Stackdriver to BigQuery, to be used to analyze the efficiency of the model.
B. Build a roadmap to move the machine learning model training from Cloud GPUs to Cloud TPUs, which offer better results.
C. Monitor Compute Engine announcements for availability of newer CPU architectures, and deploy the model to them as soon as they are available for additional performance.
D. Save a history of recommendations and results of the recommendations in BigQuery, to be used as training data.
Show Answer
Correct Answer: D
Explanation: Improving a machine learning model over time primarily requires collecting and incorporating new labeled or feedback data for retraining. Saving the history of recommendations along with their outcomes creates a feedback dataset that can be used to continuously retrain and improve the recommendation model. The other options focus on infrastructure performance or monitoring rather than improving prediction quality.
Question 82
For this question, refer to the Helicopter Racing League (HRL) case study. Recently HRL started a new regional racing league in Cape Town, South Africa. In an effort to give customers in Cape Town a better user experience, HRL has partnered with the Content Delivery Network provider, Fastly. HRL needs to allow traffic coming from all of the Fastly IP address ranges into their Virtual Private Cloud network (VPC network). You are a member of the HRL security team and you need to configure the update that will allow only the Fastly IP address ranges through the External HTTP(S) load balancer. Which command should you use?
A.
B.
C.
D.
Show Answer
Correct Answer: D
Explanation: Use a Cloud Armor security policy rule with the preconfigured Fastly source IP list via evaluatePreconfiguredExpr('sourceiplist-fastly'). Firewall rules do not apply at the external HTTP(S) load balancer layer, and option A incorrectly allows all source IPs with --src-ip-ranges *.
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