Most Recent Google Professional-Cloud-Architect Exam Dumps

Prepare for the Google Cloud Architect Professional exam with our extensive collection of questions and answers. These practice Q&A are updated according to the latest syllabus, providing you with the tools needed to review and test your knowledge.

QA4Exam focus on the latest syllabus and exam objectives, our practice Q&A are designed to help you identify key topics and solidify your understanding. By focusing on the core curriculum, These Questions & Answers helps you cover all the essential topics, ensuring you're well-prepared for every section of the exam. Each question comes with a detailed explanation, offering valuable insights and helping you to learn from your mistakes. Whether you're looking to assess your progress or dive deeper into complex topics, our updated Q&A will provide the support you need to confidently approach the Google Professional-Cloud-Architect exam and achieve success.

The questions for Professional-Cloud-Architect were last updated on May 1, 2025.

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Question No. 1

You need to implement a network ingress for a new game that meets the defined business and technical

requirements. Mountkirk Games wants each regional game instance to be located in multiple Google Cloud

regions. What should you do?

AConfigure a global load balancer connected to a managed instance group running Compute Engine
instances.

BConfigure kubemci with a global load balancer and Google Kubernetes Engine.

CConfigure a global load balancer with Google Kubernetes Engine.

DConfigure Ingress for Anthos with a global load balancer and Google Kubernetes Engine.

Show Answer

Correct Answer: A

Question No. 2

Your company has a Google Cloud project that uses BlgQuery for data warehousing There are some tables that contain personally identifiable information (PI!) Only the compliance team may access the PH. The other information in the tables must be available to the data science team. You want to minimize cost and the time it takes to assign appropriate access to the tables What should you do?

A1 From the dataset where you have the source data, create views of tables that you want to share, excluding Pll
2 Assign an appropriate project-level IAM role to the members of the data science team
3 Assign access controls to the dataset that contains the view

B1 From the dataset where you have the source data, create materialized views of tables that you want to share excluding Pll
2 Assign an appropriate project-level IAM role to the members of the data science team 3. Assign access controls to the dataset that contains the view.

C1 Create a dataset for the data science team
2 Create views of tables that you want to share excluding Pll
3 Assign an appropriate project-level IAM role to the members of the data science team
4 Assign access controls to the dataset that contains the view
5 Authorize the view to access the source dataset

D1. Create a dataset for the data science team.
2. Create materialized views of tables that you want to share, excluding Pll
3. Assign an appropriate project-level IAM role to the members of the data science team
4 Assign access controls to the dataset that contains the view
5 Authorize the view to access the source dataset

Show Answer

Correct Answer: C

This option can help minimize cost and time by using views and authorized datasets. Views are virtual tables defined by a SQL query that can exclude PII columns from the source tables. Views do not incur storage costs and do not duplicate data. Authorized datasets are datasets that have access to another dataset's data without granting direct access to individual users or groups. By creating a dataset for the data science team and creating views of tables that exclude PII, you can share only the relevant information with the team. By assigning an appropriate project-level IAM role to the members of the data science team, you can grant them access to the BigQuery service and resources. By assigning access controls to the dataset that contains the view, you can grant them access to query the views. By authorizing the view to access the source dataset, you can enable the view to read data from the source tables without exposing PII. The other options are not optimal for this scenario, because they either use materialized views instead of views, which incur storage costs and duplicate data (B, D), or do not create a separate dataset for the data science team, which makes it harder to manage access controls (A). Reference:

https://cloud.google.com/bigquery/docs/views

https://cloud.google.com/bigquery/docs/authorized-datasets

Question No. 3

For this question, refer to the TerramEarth case study. You are asked to design a new architecture for the

ingestion of the data of the 200,000 vehicles that are connected to a cellular network. You want to follow

Google-recommended practices.

Considering the technical requirements, which components should you use for the ingestion of the data?

AGoogle Kubernetes Engine with an SSL Ingress

BCloud IoT Core with public/private key pairs

CCompute Engine with project-wide SSH keys

DCompute Engine with specific SSH keys

Show Answer

Correct Answer: A

https://cloud.google.com/solutions/iot-overview

https://cloud.google.com/iot/quotas

Question No. 4

For this question, refer to the EHR Healthcare case study. EHR has single Dedicated Interconnect

connection between their primary data center and Googles network. This connection satisfies

EHR's network and security policies:

* On-premises servers without public IP addresses need to connect to cloud resources

without public IP addresses

* Traffic flows from production network mgmt. servers to Compute Engine virtual

machines should never traverse the public internet.

You need to upgrade the EHR connection to comply with their requirements. The new

connection design must support business critical needs and meet the same network and

security policy requirements. What should you do?

AAdd a new Dedicated Interconnect connection

BUpgrade the bandwidth on the Dedicated Interconnect connection to 100 G

CAdd three new Cloud VPN connections

DAdd a new Carrier Peering connection

Show Answer

Correct Answer: A

The case does not call out the throughput being an issue. However, to achieve 99.99%, you need to have 4 connections as per Google recommendations. However, in the options only A has the option to add an additional Interconnect connection. https://cloud.google.com/network-connectivity/docs/interconnect/concepts/dedicated-overview#availability

Question No. 5

You are developing your microservices application on Google Kubernetes Engine. During testing, you want to validate the behavior of your application in case a specific microservice should suddenly crash. What should you do?

AAdd a taint to one of the nodes of the Kubernetes cluster. For the specific microservice, configure a pod anti-affinity label that has the name of the tainted node as a value.

BUse Istio's fault injection on the particular microservice whose faulty behavior you want to simulate.

CDestroy one of the nodes of the Kubernetes cluster to observe the behavior.

DConfigure Istio's traffic management features to steer the traffic away from a crashing microservice.

Show Answer

Correct Answer: B

Microservice runs on all nodes. The Micro service runs on Pod, Pod runs on Nodes. Nodes is nothing but Virtual machines. Once deployed the application microservices will get deployed across all Nodes. Destroying one node may not mimic the behaviour of microservice crashing as it may be running in other nodes.

link: https://istio.io/latest/docs/tasks/traffic-management/fault-injection/

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