GCP Professional Cloud Architect Sample Practice Exam Questions - PCA - 001 ( 2025 )

Master your Google Cloud Certified Professional Cloud Architect ( PCA - 001 ) exam with this comprehensive collection of GCP Professional Cloud Architect Sample Questions. Aligned with the GCP Professional Cloud Architect exam dumps, these questions simulate real-world scenarios and provide a thorough understanding of key concepts like cloud architecture, networking, security, and cost management. This resource is designed for those preparing for the Google Cloud Architect certification, including GCP PCA dumps, practice exams, and exam questions. Strengthen

GCP Professional Cloud Architect Sample Questions List :

1. An e-commerce company is building a new platform on Google Cloud Platform (GCP) that will handle order processing, inventory management, and customer notifications. The architecture must be event-driven to allow for decoupling of services, real-time processing, and scalability. The platform needs to handle high volumes of transactions during peak shopping times, such as Black Friday, and ensure that events are processed in the correct order. Additionally, the platform should be resilient to failure and capable of retrying failed events without duplication. Which architecture best supports the application’s design requirements?

1. Implement event-driven microservices using Cloud Functions, with Cloud Pub/Sub for messaging, and Cloud Storage for event persistence.

2. Use Cloud Run for running event-driven microservices, Cloud Pub/Sub for asynchronous messaging, and BigQuery for storing event logs and processing history.

3. Use Google Kubernetes Engine (GKE) to deploy event-driven microservices, Cloud Pub/Sub for event distribution, and Cloud Spanner for transactional data consistency.

4. Implement the architecture using Dataproc for processing events, Bigtable for storing event data, and Cloud Storage for archiving historical events.

2. In your role as a cloud architect, you are in the process of designing a hybrid environment that is future-proof and necessitates a network connection between Google Cloud and your on-premises infrastructure. Your objective is to guarantee compatibility between the Google Cloud environment you are designing and your existing on-premises network environment. What course of action should you take?

1. You should create a custom VPC in Google Cloud in auto mode. Use a Cloud VPN connection between your on-premises environment and Google Cloud.

2. You should create a network plan for your VPC in Google Cloud that uses non-overlapping CIDR ranges with your on-premises environment. Use a Cloud Interconnect connection between your on-premises environment and Google Cloud.

3. You should create a network plan for your VPC in Google Cloud that uses CIDR ranges that overlap with your on-premises environment. Use a Cloud Interconnect connection between your on-premises environment and Google Cloud.

4. You should use the default VPC in your Google Cloud project. Use a Cloud VPN connection between your on-premises environment and Google Cloud.

3. Your company operates a global e-commerce platform that experiences seasonal spikes in traffic, particularly during holidays and sales events. The business requires a highly available and scalable infrastructure to handle traffic surges without any degradation in user experience. Additionally, the platform needs to support real-time data processing for personalized recommendations and analytics. The company plans to expand into new geographic regions over the next 12 months. As the lead architect, you must design a cloud solution architecture that meets the following business requirements: High Availability: Ensure 99.99% uptime for the platform.Scalability: Automatically scale resources to handle sudden traffic spikes.Low Latency: Deliver content with minimal latency to users worldwide.Data Processing: Implement real-time data processing for recommendations and analytics.Cost Optimization: Keep costs within a predetermined budget while ensuring performance.Which combination of architectural decisions best meets the business requirements for your e-commerce platform? (Select two)

1. Implement a single-region deployment with autoscaling enabled.

2. Use pre-provisioned virtual machines to handle expected peak loads.

3. Use a multi-region deployment with load balancing across regions.

4. Deploy a Content Delivery Network (CDN) to cache static content closer to users.

5. Host the database on a single VM to minimize costs.

4. Your company has a hybrid cloud computing model and your current network connection is using 50% of bandwidth. As a cloud architect, you are concerned that you only have one connection that you might lose in the event of a failure. What would you do to minimize this risk?

1. You should increase the bandwidth of your current network connection.

2. You should use redundant network connections between the on-premises data center and GCP.

3. You should increase the number of virtual machines for your workload.

4. You should increase the performance of virtual machine disks.

5. In your Compute Engine managed instance group, an outage has occurred where all instances are continuously restarting every 6 seconds. Although you have a configured health check, autoscaling is currently disabled. To address this issue, your Linux expert colleague has offered to investigate. Your task is to ensure that your colleague has appropriate access to the VMs for troubleshooting purposes. What should you do?

1. Disable autoscaling for the instance group. Add his SSH key to the project-wide SSH keys.

2. Grant your colleague the IAM role of project Viewer.

3. Perform a rolling restart on the instance group.

4. Disable the health check for the instance group. Add his SSH key to the project-wide SSH keys.

6. A financial services company is running a high-performance trading application on a Compute Engine VM (n2-highcpu-16) with a 100 GB SSD persistent disk. The application writes thousands of small files per second. Recently, the team has noticed increased write latency. They cannot afford downtime. What is the most effective and cost-efficient action to improve performance?

1. Add a local SSD to the VM instance.

2. Use snapshots to back up the disk and restore it to a new, larger VM.

3. Migrate the application to a Google Kubernetes Engine cluster.

4. Upgrade the VM to a custom machine type with more vCPUs.

7. Your company is developing a multi-region, customer-facing application hosted on Google Cloud. It uses Cloud SQL (PostgreSQL), Compute Engine VMs in managed instance groups behind global HTTP(S) load balancers, and stores assets in Cloud Storage. Recently, customers in Europe have complained about increased latency during peak hours. What is the most effective solution to reduce latency for these customers without duplicating infrastructure or compromising data consistency?

1. Move the Cloud SQL instance to the Europe region and leave the application backend in the US.

2. Create a new instance of the application in a European region and set up active-active database replication.

3. Deploy Cloud CDN in front of the global HTTP(S) load balancer and enable cacheable content delivery from Cloud Storage.

4. Migrate the application backend to App Engine flexible environment with autoscaling in a European region.

8. Your company has multiple GKE clusters running in different regions. You are tasked with setting up a centralized monitoring solution to have a single view of the health and performance of all the clusters. Which approach would you take?

1. Use Anthos to centrally manage and monitor all GKE clusters.

2. Deploy a Prometheus server in each GKE cluster and configure them to push metrics to a central Grafana dashboard.

3. Configure each GKE cluster to export logs and metrics to a central BigQuery dataset and create custom SQL queries to monitor the health.

4. Use Google Cloud's Operations suite and set up a Workspace for each GKE cluster, then create a combined dashboard.

9. Your organization is developing a new multi-tier web application. The application architecture consists of a web front end, a REST API backend, and a relational database. The application is expected to experience heavy traffic, so it needs to be highly scalable and resilient. As a cloud architect, which of the following deployment strategies would you recommend for this application on Google Cloud?

1. Deploy the web front end on Compute Engine, the REST API backend on GKE, and the database on Cloud Bigtable.

2. Deploy the web front end and REST API backend on separate App Engine services, and the database on Cloud Spanner.

3. Deploy the web front end on Cloud Functions, the REST API backend on App Engine, and the database on Firestore.

4. Deploy the entire application on a single GKE cluster, using different namespaces for the front end, the backend, and the database.

10. For this question, refer to the Mountkirk Games case study. https://services.google.com/fh/files/blogs/master-casestudy-mountkirk-games.pdf Mountkirk Games wants to ensure their new gaming platform adheres to Google best practices for security and operational monitoring. They aim to reduce security risks while ensuring their operations teams can monitor and maintain platform health effectively. What actions should you take? (Choose two)

1. Configure BigQuery datasets to allow public access for faster query execution.

2. Ensure all API traffic is logged and monitored using Cloud Audit Logs.

3. Disable workload identity to minimize configuration overhead.

4. Use public GKE clusters to simplify workload accessibility.

5. Use Cloud Identity and Access Management (IAM) to enforce least privilege for service accounts.

11. Your company is designing a multi-region application on Google Cloud. You need to ensure low-latency connectivity and high availability between two Google Cloud regions where your workloads are deployed. You also want to make sure that this setup can scale in the future without major reconfiguration. What should you do?

1. Use the default VPC and configure subnets in both regions.

2. Use a single custom VPC with subnets in each region, and configure Cloud NAT for outbound access.

3. Use separate VPCs in each region and peer them using VPC Peering.

4. Use separate custom VPCs in each region and connect them using a VPN tunnel.

12. Consider a scenario where a large online retailer needs to implement a highly available and scalable NoSQL solution for its e-commerce platform. The solution must handle large amounts of traffic during peak periods, provide fast and reliable performance, and ensure the security of customer data. What is the most appropriate solution for the large online retailer to implement a highly available and scalable solution for its e-commerce platform while handling large amounts of traffic during peak periods, providing fast and reliable performance, and ensuring the security of customer data?

1. Use Google Kubernetes Engine for the e-commerce platform with autoscaling and use Cloud Firestore for storage.

2. Use Compute Engine with autoscaling and load balancing for the e-commerce platform and use Cloud SQL for storage.

3. Use Compute Engine VM single instance for the e-commerce platform and use Cloud SQL for storage.

4. Use App Engine for the e-commerce platform with a single instance and use Cloud Storage for storage.

13. A company is moving an enterprise application to the Google Cloud. This application runs on a cluster of virtual machines on private data center, and workloads are distributed by a load balancer. Select all true statements. (Choose two)

1. The migration team decided to use containers and the Kubernetes Engine. This migration strategy is called Improve and Move.

2. The migration team decided to use containers and the Kubernetes Engine. This migration strategy is called Lift and Shift.

3. The migration team decided not to make unnecessary changes before moving this application to the cloud. This migration strategy is called Lift and Shift.

4. The migration team decided not to make unnecessary changes before moving this application to the cloud. This migration strategy is called Improve and Move.

5. The migration team decided to use containers and the Kubernetes Engine. This migration strategy is called Remove and Replace.

14. In your role as a cloud architect, you are tasked with designing a large distributed application comprising 20 microservices. Each of these microservices must connect to the database backend. Your objective is to ensure the secure storage of credentials for these connections. What is the recommended storage location for the credentials?

1. In an environment variable

2. In a secret management system

3. In a config file that has restricted access through ACLs

4. In the source code

15. A shipment tracking application receives data from sensors. Sometimes more data arrives than the virtual machines can process. As a cloud architect, you don't want to use additional virtual machines and you also need the most economical solution. What can you do to prevent data loss?

1. You should write data to local SSDs on the Compute Engine virtual machines.

2. You should increase the CPU.

3. You should write data to the Cloud Pub/Sub queue, and the application should read data from the queue.

4. You should write data to Cloud Memorystore, and the application should read data from the cache.

16. You provide a service that you need to open to everyone in your partner network and have a server and an IP address where the application is located. You do not want to have to change the IP address on your DNS server if your server goes down or is replaced. You also want to avoid downtime and deliver a solution with minimal cost and setup. What should you recommend?

1. You should create a script that updates the domain's IP address when the server goes down or is replaced.

2. You should reserve a static external IP address, and assign it using Cloud DNS.

3. You should reserve a static internal IP address, and assign it using Cloud DNS.

4. You should use the Bring Your Own IP (BYOIP) method to use your own IP address.

17. Following your company's acquisition of another company, you have been assigned the task of integrating their existing Google Cloud environment with your company's data center. Upon examination, you uncover that certain RFC 1918 IP address ranges employed in the new company's Virtual Private Cloud (VPC) conflict with the IP address space utilized in your data center. What steps should you take to establish connectivity and prevent any routing conflicts once the connectivity is established?

1. Create a Cloud VPN connection from the new VPC to the data center, create a Cloud Router, and apply a custom route advertisement to block the overlapping IP space.

2. Create a Cloud VPN connection from the new VPC to the data center, create a Cloud Router, and apply new IP addresses so there is no overlapping IP space.

3. Create a Cloud VPN connection from the new VPC to the data center, and apply a firewall rule that blocks the overlapping IP space.

4. Create a Cloud VPN connection from the new VPC to the data center, and create a Cloud NAT instance to perform NAT on the overlapping IP space.

18. As a cloud architect, you set up the optimal combination of CPU and memory resources for nodes in a Kubernetes cluster. You want to be notified whenever CPU utilization exceeds 80% for 5 minutes or when memory utilization exceeds 90% for 1 minute. What do you need to specify to receive such notifications?

1. A logging message specification

2. An alerting policy

3. Cloud Pub/Sub topic

4. An alerting condition

19. Your client wants to offload their existing on-premises archive of 80 TB of customer support call transcripts to the cloud. These files will rarely be accessed, but should be searchable using SQL for quarterly business reviews. What two solutions best meet these requirements with minimal operational overhead and cost? (Choose two)

1. Use BigQuery external tables to query data stored in Cloud Storage.

2. Upload files to Cloud Storage in Archive or Coldline class.

3. Use Cloud Dataflow to transform the data and stream it into Pub/Sub.

4. Upload files into Persistent Disks attached to Compute Engine instances.

5. Load data into BigQuery using federated data sources.

20. As a cloud architect, you are faced with the situation where you have recently deployed an application on a single Compute Engine virtual machine instance, but its popularity is not meeting your initial expectations. Your goal now is to minimize costs associated with this scenario. What would be the optimal deployment location for your application?

1. You should containerize your application an deploy with Cloud Run.

2. You should deploy your application with Kubernetes Engine with horizontal pod autoscaling and cluster autoscaler enabled.

3. You should deploy your application with App Engine Flexible.

4. In this case, it is not possible to reduce costs.

21. You are the cloud architect for a multinational corporation which has decided to migrate its on-premises data warehouse to Google Cloud. The data warehouse needs to handle several petabytes of data, with frequent, unpredictable spikes in query activity. What approach should you recommend for scalable data warehouse solution on GCP?

1. Use Cloud Storage for data storage, with scheduled queries running in Dataflow.

2. Use Bigtable for data storage, with analysis using Data Studio.

3. Use BigQuery for both data storage and analysis.

4. Use Cloud SQL for data storage, with Dataflow for analysis.

22. A global online retail company is designing a new cloud-native application to support its expanding business. The application must handle high traffic during flash sales, provide a seamless user experience worldwide, and ensure that data is secure and compliant with regional regulations. The development team is building the application using a microservices architecture, with services deployed in containers. The company is particularly concerned about optimizing the application design for performance, security, and scalability. The business requirements include: Global Availability: Ensure low-latency access for users worldwide. Scalability: Automatically scale to handle spikes in traffic during flash sales.Security: Protect customer data and ensure compliance with regional data protection laws. Resilience: Minimize downtime and quickly recover from failures. Which architectural decisions best support the application design for the global online retail company? (Choose three)

1. Implement a multi-region database with strong consistency guarantees using Cloud Spanner.

2. Deploy the application in a single region with a global load balancer.

3. Use Google Kubernetes Engine (GKE) to manage microservices in multiple regions.

4. Use a single Cloud SQL instance for the database to reduce complexity.

5. Leverage Google Cloud's Secret Manager for storing and accessing sensitive configuration data.

23. As a cloud architect, you are tasked with designing an architecture for an application that will operate on Compute Engine. It is essential to create a disaster recovery plan that ensures the application can seamlessly switch to another region in the event of a regional outage. What course of action should you take?

1. You should deploy the application on two Compute Engine instance groups, each in the same project but in a different region. Use the first instance group to serve traffic, and use the HTTP load balancing service to fail over to the standby instance group in case of a disaster.

2. You should deploy the application on two Compute Engine instance groups, each in a separate project and a different region. Use the first instance group to serve traffic, and use the HTTP load balancing service to fail over to the standby instance group in case of a disaster.

3. You should deploy the application on two Compute Engine instances in the same project but in a different region. Use the first instance to serve traffic, and use the HTTP load balancing service to fail over to the standby instance in case of a disaster.

4. You should deploy the application on a Compute Engine instance. Use the instance to serve traffic, and use the HTTP load balancing service to fail over to an instance on your premises in case of a disaster.

24. Your organization stores sensitive customer data in Cloud Storage. You have been asked to design a solution that both prevents unauthorized data access and ensures regulatory compliance. Which of the following approaches would be the most appropriate?

1. Encrypt data using customer-managed encryption keys (CMEK) and enforce fine-grained access control with Identity and Access Management (IAM).

2. Use Cloud Audit Logs to monitor access to Cloud Storage.

3. Use VPC Service Controls to isolate Cloud Storage.

4. Implement Cloud Identity-Aware Proxy (IAP) to control access to Cloud Storage.

25. For this question, refer to the EHR Healthcare case study. https://services.google.com/fh/files/blogs/master_case_study_ehr_healthcare.pdf EHR Healthcare's data analysis team runs an analytics application to process public health data. The application is currently hosted on-premises but has seen significant growth, leading to performance issues. The team wants to migrate the application to Google Cloud, reduce latency, and ensure security from potential attacks. Additionally, the application must comply with regulations to encrypt data in transit. What should you do?

1. Use App Engine Standard Environment to deploy the application and configure firewall rules to block DDoS traffic.

2. Move the application to Compute Engine, deploy a Cloud VPN to encrypt traffic, and use VPC firewall rules to block untrusted IP addresses.

3. Deploy the application to Google Kubernetes Engine (GKE), expose the application using an external HTTP(S) load balancer, and configure Google Cloud Armor for DDoS protection.

4. Use Compute Engine to deploy virtual machines, configure an internal load balancer, and encrypt traffic using custom SSL certificates.

26. For this question, refer to the Mountkirk Games case study. https://services.google.com/fh/files/blogs/master_case_study_mountkirk_games.pdf Mountkirk Games is migrating their game analytics platform to Google Cloud and wants to ensure that their data pipelines are reliable, scalable, and follow Google Cloud’s operational best practices. You need to recommend an architecture that provides observability and maintains data quality throughout the pipeline. What should you do? (Choose two)

1. Configure Cloud Dataflow pipelines to write logs to local disk for debugging

2. Use Cloud Dataflow for batch and streaming data processing with Cloud Logging enabled

3. Use BigQuery scheduled queries without logging to reduce costs

4. Use Pub/Sub to decouple producers and consumers in the pipeline

5. Deploy a self-managed Apache Hadoop cluster on Compute Engine with custom monitoring agents

27. For this question, refer to the Helicopter Racing League (HRL) case study. https://services.google.com/fh/files/blogs/master_case_study_helicopter_racing_league.pdf HRL wants to ensure that their fans in emerging regions can experience real-time race highlights with minimal latency. Considering the HRL business and technical requirements, what should you do?

1. Deploy Cloud Spanner to store and serve race highlight videos with low-latency global access.

2. Use Cloud CDN to cache race highlight videos for low-latency delivery to fans.

3. Host the videos on a single-region Cloud Storage bucket and use signed URLs to deliver them.

4. Set up video streaming on Google Kubernetes Engine clusters close to user regions.

28. For this question, refer to the TerramEarth case study. https://services.google.com/fh/files/blogs/master_case_study_terramearth.pdf You are a cloud architect for TerramEarth, tasked with implementing a solution that provides real-time insights to improve fleet management while ensuring compliance with regulations for handling telemetry data. The solution must anonymize sensitive telemetry data before analysis. Which approach should you recommend?

1. Encrypt all telemetry data at rest using customer-managed encryption keys (CMEK).

2. Store telemetry data in Google BigQuery and use SQL queries to mask sensitive fields during analysis.

3. Process all telemetry data on-premises to avoid exposing it to the cloud environment.

4. Use the Cloud Data Loss Prevention (DLP) API to de-identify sensitive telemetry data before storing it in Google BigQuery.

29. You are managing a project that consists of a single Virtual Private Cloud (VPC) and a single subnetwork located in the us-west1 region. Within this subnetwork, there is a Compute Engine instance hosting an application. Now, your development team intends to deploy a new instance within the same project, but in the europe-central2 region. They require access to the application and wish to adhere to Google's best practices. As a cloud architect, what guidance should you provide in this situation?

1. They should create a VPC and a subnetwork in europe-central2 region. Than, peer the 2 VPCs, and finally create a new instance in the new subnetwork and use the first instance's private address as the endpoint.

2. They should create a VPC and a subnetwork in europe-central2 region. Than, expose the application with an internal load balancer, and finally create a new instance in the new subnetwork and use the load balancer's address as the endpoint.

3. They should create a subnetwork in the same VPC, in europe-central2 region. Than, use Cloud VPN to connect these two subnetworks, and finally create a new instance in the new subnetwork and use the first instance's private address as the endpoint.

4. They should create a subnetwork in the same VPC, in europe-central2 region. Than, create a new instance in the new subnetwork and use the first instance's private address as the endpoint.

30. Your organization hosts a 3-tier application (frontend, backend, and database) in Google Cloud using Compute Engine instances in the same Virtual Private Cloud (VPC). The frontend tier should only communicate with the backend tier, and the backend tier should only communicate with the database tier. All inter-tier traffic must follow the principle of least privilege. How should you configure the network to enforce these requirements efficiently?

1. Create separate subnetworks for each tier and configure firewall rules to allow the required traffic.

2. Set up VPC Service Controls to restrict traffic between tiers.

3. Use network tags to assign each tier and configure firewall rules to allow specific traffic flows.

4. Create individual custom routes for each tier to control traffic flow between them.

31. You are designing a data processing pipeline on Google Cloud to handle large-scale batch jobs for a retail company. The pipeline processes sales data once a day, generates daily reports, and stores them in Cloud Storage. The reports are then processed by a BigQuery analytics system. The batch jobs will run on Google Dataproc, and Cloud Storage will be used to store both raw and processed data. You need to estimate the monthly cost of the solution based on the following usage: Dataproc cluster with 5 worker nodes running 4 hours per day. 10 TB of data storage in Cloud Storage (Regional storage). 5 TB of processed data queried daily in BigQuery. Network egress costs to export 1 TB of data monthly to an external service. Which approach is the most accurate for estimating the monthly cost of this solution?

1. Estimate Dataproc cluster costs by calculating the cost of the master node and ignore the worker nodes since they only run for 4 hours per day. Use Cloud Storage Nearline pricing to save costs on storing 10 TB of data. Include BigQuery costs for querying 5 TB of data and network egress charges for exporting 1 TB.

2. Use the Google Cloud Pricing Calculator to estimate costs for the Dataproc cluster, include Cloud Storage costs for storing 10 TB of data, BigQuery pricing for 5 TB of daily queries, and network egress charges for exporting 1 TB of data.

3. Calculate Dataproc costs using the preemptible VMs pricing for worker nodes to reduce costs, estimate Cloud Storage costs using Multi-Regional storage for redundancy, and calculate BigQuery costs assuming a flat-rate pricing model. Ignore network egress costs since they are included in the flat-rate plan.

4. Estimate the Dataproc cluster costs by calculating the hourly rate for 5 nodes, estimate Cloud Storage costs based on Standard storage pricing for 10 TB, and BigQuery costs using the on-demand pricing model for querying 5 TB of data daily. Ignore network egress costs as they are negligible for only 1 TB of data.

32. You are designing a multi-tier application where the front-end services are hosted in a Virtual Private Cloud (VPC) in region A and the back-end services are hosted in a separate VPC in region B. You need to enable communication between the front-end and back-end services while ensuring low latency and cost efficiency. Which networking approach would best meet these requirements?

1. Use Cloud Interconnect to link the two VPCs.

2. Set up VPC Peering between the two VPCs.

3. Set up a public IP for the back-end VPC and route traffic through the public internet.

4. Use Cloud VPN to connect the two VPCs.

33. A global media company needs to build a cloud-based data analytics platform on GCP to analyze viewer data in real-time from multiple regions. The company requires the solution to support stream processing, handle petabytes of data daily, and allow data scientists to run ad-hoc queries efficiently. Data must be stored for at least 5 years for regulatory compliance, and the platform should be cost-effective, especially during off-peak times when data queries are less frequent. Which architecture would best meet the company's requirements?

1. Use Dataproc with Kafka for stream processing, Cloud Storage for storage, and BigQuery for analytics.

2. Implement Pub/Sub for stream processing, Cloud SQL for storage, and Cloud Spanner for analytics.

3. Deploy a Hadoop cluster on GCE for stream processing, Bigtable for storage, and Cloud Storage Nearline for long-term data storage.

4. Use Dataflow for stream processing, BigQuery for storage and analysis, and Cloud Storage for long-term data storage.

34. You are a cloud architect working on a large-scale application that leverages various Google Cloud services, including Bigtable, Firestore, and Pub/Sub. Your development team is transitioning from a monolithic architecture to a microservices architecture, and you are tasked with implementing a testing strategy that includes the use of cloud emulators to ensure each service is properly tested in isolation before integration. Which of the following strategies would be most effective for managing this implementation using Google Cloud emulators?

1. Implement a single emulator that mimics all services (Bigtable, Firestore, and Pub/Sub) to simplify the testing process and reduce resource usage.

2. Only use local machine emulators for development and skip CI/CD integration, relying on developer discipline to conduct necessary tests.

3. Utilize the Google Cloud SDK to deploy emulators for Bigtable, Firestore, and Pub/Sub directly in the production environment for live testing.

4. Configure separate CI/CD pipelines to include stages that set up and tear down emulators for each service, ensuring isolated environment testing during development.

35. As a cloud architect, you need to prepare a resource hierarchy for your company. Suppose your company has two different applications with development and production environment. With Google's best practices in mind, what should you do?

1. You should create four different projects (for each application and environment). This isolates the environments from each other, so changes to the development project don't accidently impact production environment. This also gives you better access control.

2. You should create all applications in one project.

3. You should create two projects, each for one environment.

4. You should create two projects, each for one application.

FAQs

1. What is the GCP Professional Cloud Architect certification?

It is a Google Cloud certification that validates your ability to design, develop, and manage secure, scalable, and highly available cloud solutions on Google Cloud Platform (GCP).

2. Who should take the GCP Cloud Architect certification?

Cloud engineers, architects, and IT professionals responsible for designing or managing GCP-based cloud infrastructure should consider this certification.

3. Is GCP Cloud Architect certification worth it?

Yes, it is one of the most in-demand and respected certifications in the cloud industry, leading to high-paying job roles and strong credibility.

4. What are the benefits of Google Cloud Architect certification?

Benefits include enhanced cloud architecture skills, better job prospects, industry recognition, and access to higher-paying cloud roles.

5. What is the difference between GCP Cloud Architect and AWS Solutions Architect?

GCP Cloud Architect focuses on Google Cloud services, while AWS Solutions Architect covers AWS infrastructure. Both are valuable, but relevant to different cloud platforms.

6. How many questions are on the GCP Professional Cloud Architect exam?

The exam consists of around 50–60 multiple-choice and multiple-select questions.

7. What is the format of the Google Cloud Architect certification exam?

It’s a 2-hour, proctored exam featuring scenario-based questions in a multiple-choice/multiple-response format.

8. What topics are covered in the GCP Cloud Architect exam?

Topics include:

• Designing cloud solutions

• Managing cloud infrastructure

• Security and compliance

• Business and technical processes

• Solution reliability and scalability

9. Is the GCP Cloud Architect exam multiple choice or hands-on?

It is multiple-choice and multiple-select only. There are no hands-on labs.

10. What is the difficulty level of the GCP Professional Cloud Architect exam?

The exam is moderately difficult to advanced. It requires practical knowledge of GCP services and architecture best practices.

11. What is the cost of the GCP Professional Cloud Architect exam?

The exam fee is $200 USD, excluding applicable taxes.

12. Are there any prerequisites for the Google Cloud Architect certification?

There are no formal prerequisites, but Google recommends 3+ years of industry experience, including 1+ year with GCP.

13. Can beginners take the GCP Cloud Architect certification?

Yes, beginners can attempt it, but prior experience with cloud platforms and hands-on GCP practice is highly recommended.

14. How much experience is required for GCP Professional Cloud Architect?

At least 1 year of hands-on experience with GCP and 3 years of general industry experience is suggested.

15. What is the passing score for the GCP Cloud Architect exam?

Google does not publish an exact passing score, but it is generally estimated to be around 70%.

16. How is the GCP Cloud Architect exam scored?

It uses a scaled scoring system. Candidates are scored based on performance in each section.

17. How often can I retake the GCP Professional Cloud Architect exam?

You can retake the exam after a 14-day waiting period. If you fail again, the wait period increases.

18. What happens if I fail the GCP Cloud Architect certification exam?

You can retake the exam after the mandatory waiting period, but must pay the exam fee again.

19. How do I prepare for the GCP Professional Cloud Architect certification?

To prepare effectively:

• Use CertiMaan’s GCP Cloud Architect sample questions and dumps

• Study official content from Google Cloud training at cloud.google.com/training

20. What are the best study materials for GCP Cloud Architect exam?

Top materials include:

• CertiMaan’s practice exams and preparation guides

• Google Cloud’s Skill Boosts platform and architecture case studies

21. Are there any free resources for GCP Cloud Architect exam preparation?

Yes. You can access:

• CertiMaan’s free sample questions

• Google Cloud’s free learning labs and documentation

22. How long does it take to prepare for the GCP Cloud Architect certification?

It typically takes 4 to 6 weeks of focused study, depending on your background and experience with GCP.

23. How long is the GCP Professional Cloud Architect certification valid?

The certification is valid for 2 years from the date of passing the exam.

24. Does the GCP Cloud Architect certification expire?

Yes, it expires after two years. Recertification is required to maintain active status.

25. How do I renew my Google Cloud Architect certification?

You must retake and pass the current version of the GCP Cloud Architect exam before your certification expires.

26. What jobs can I get with GCP Professional Cloud Architect certification?

You can work as:

• Cloud Solutions Architect

• Cloud Engineer

• Technical Cloud Consultant

• Infrastructure Architect

27. What is the average salary of a GCP Certified Cloud Architect?

Salaries typically range between $130,000 and $180,000 USD annually, based on role and experience.

28. Which companies hire GCP Certified Cloud Architects?

Top employers include Google, Accenture, Deloitte, Infosys, Wipro, and cloud-native startups.

29. Is GCP Cloud Architect certification good for a cloud career?

Yes, it is one of the most respected certifications for cloud professionals and leads to excellent career opportunities.