What are the prerequisites for taking the Professional Cloud Architect exam?

Google recommends having 3+ years of industry experience and 1+ year of hands-on experience with Google Cloud Platform. While there are no strict prerequisites, it's advisable to have completed the Associate Cloud Engineer certification first and be familiar with GCP services, architecture patterns, and cloud solutions.

How long is the Professional Cloud Architect certification exam?

The exam is 2 hours long and consists of approximately 50 multiple-choice and multiple-select questions. You need to score at least 70% to pass, and the exam is proctored either online or at a testing center.

What topics are covered in the Professional Cloud Architect exam?

The exam covers designing and planning cloud architecture solutions, managing and provisioning infrastructure, designing for security and compliance, analyzing and optimizing technical and operational processes, and managing implementation of cloud architecture. Key areas include Compute, Storage, Networking, Databases, and Google Cloud Platform solutions.

How much does the Professional Cloud Architect exam cost?

The exam costs $200 USD, though pricing may vary by region and currency. Google occasionally offers discounts or promotional pricing, so it's worth checking the official Google Cloud certification page for current rates and any available promotions.

How long is the Professional Cloud Architect certification valid?

The certification is valid for 3 years from the date you pass the exam. After 3 years, you'll need to recertify by passing the exam again to maintain your active certification status.

Free Google Professional-Cloud-Architect Exam Questions

Q1 MultipleChoice

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?

ACreate 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

BCreate 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.

CCreate 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.

DCreate 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.

Correct Answer: A

Explanation:

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

https://cloud.google.com/migrate/compute-engine/docs/4.9/concepts/planning-a-migration/cloud-instance-rightsizing?hl=en

Q2 MultipleChoice

You are designing me observability strategy for a new microservices application running on Google Kubernetes Engine (GKE) The application consists of multiple services (e.g.. frontend, orders, payments). During load testing, you observe an error in the frontend service's logs, but you cannot find the corresponding logs in the downstream services to investigate the root cause because the logs are not correlated. You need to implement a solution that allows you to follow a single user request across all microservices involved in the transaction. The solution must not require developers to manually add correlation logic to their application code What should you do?

ARequire developers to generate a unique correlation-id at the frontend. and manually add it as a field to every log message in all services.

BConfigure all containers to write logs to STDOUTSTDERR. and then filter logs by pod name and timestamp m the Logs Explorer

CImplement Cloud Trace by ensuring the traceparent header is propagated between microservice calls to link logs to a single trace

DCreate custom metrics in Cloud Monitoring for error counts in each service and correlate incident spikes using a shared dashboard

Correct Answer: C

Explanation:

To follow a user request through a maze of microservices, you need Distributed Tracing.

Cloud Trace: By ensuring the traceparent (W3C standard) header is propagated (Option C), Google Cloud can automatically link logs from the Frontend, Orders, and Payments services.

Zero Manual Effort: Modern libraries (like OpenTelemetry) handle the 'heavy lifting' of extracting and injecting these headers into outgoing requests, satisfying the requirement to avoid manual correlation logic.

Q3 MultipleChoice

Your company is moving 75 TB of data into Google Cloud. You want to use Cloud Storage and follow Googlerecommended practices. What should you do?

AMove your data onto a Transfer Appliance. Use a Transfer Appliance Rehydrator to decrypt the data into Cloud Storage.

BMove your data onto a Transfer Appliance. Use Cloud Dataprep to decrypt the data into Cloud Storage.

CInstall gsutil on each server that contains data. Use resumable transfers to upload the data into Cloud Storage.

DInstall gsutil on each server containing data. Use streaming transfers to upload the data into Cloud
Storage.

Correct Answer: A

Explanation:

https://cloud.google.com/transfer-appliance/docs/2.0/faq

Q4 MultipleChoice

Your customer support tool logs all email and chat conversations to Cloud Bigtable for retention and analysis.

What is the recommended approach for sanitizing this data of personally identifiable information or payment

card information before initial storage?

AHash all data using SHA256

BEncrypt all data using elliptic curve cryptography

CDe-identify the data with the Cloud Data Loss Prevention API

DUse regular expressions to find and redact phone numbers, email addresses, and credit card numbers

Correct Answer: A

Q5 MultipleChoice

You have deployed an application on Anthos clusters (formerly Anthos GKE). According to the SRE practices at your company you need to be alerted if the request latency is above a certain threshold for a specified amount of time. What should you do?

AEnable the Cloud Trace API on your project and use Cloud Monitoring Alerts to send an alert based on the Cloud Trace metrics

BConfigure Anthos Config Management on your cluster and create a yaml file that defines the SLO and alerting policy you want to deploy in your cluster

CUse Cloud Profiler to follow up the request latency. Create a custom metric in Cloud Monitoring based on the results of Cloud Profiler, and create an Alerting Policy in case this metric exceeds the threshold

DInstall Anthos Service Mesh on your cluster. Use the Google Cloud Console to define a Service Level Objective (SLO)

Correct Answer: D

Explanation:

https://cloud.google.com/service-mesh/docs/overview

https://cloud.google.com/service-mesh/docs/observability/slo-overview

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