Free Google Professional-Cloud-Security-Engineer Exam Questions

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  • Google Professional-Cloud-Security-Engineer Exam Questions
  • Provided By: Google
  • Exam: Professional Cloud Security Engineer
  • Certification: Google Cloud Certified
  • Total Questions: 299
  • Updated On: Apr 29, 2025
  • Rated: 4.9 |
  • Online Users: 598
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  • Question 1
    • A patch for a vulnerability has been released and a DevOps team in a healthcare technology company needs to update their running containers in Google Kubernetes Engine (GKE). What steps should the DevOps team take to accomplish this task?



      Answer: C
  • Question 2
    • Your organization is building a real-time recommendation engine using ML models that process live user activity data stored in BigQuery and Cloud Storage. Each new model developed is saved to Artifact Registry. This new system deploys models to Google Kubernetes Engine and uses Pub/Sub for message queues. Recent industry news has been reporting attacks exploiting ML model supply chains. You need to enhance the security in this serverless architecture, specifically against risks to the development and deployment pipeline. What should you do? 

      Answer: B
  • Question 3
    • As a member of the security team for a Smart Home Automation company, what steps should you take to reduce the scope of systems subject to PCI audit standards in your GCP project that includes credit card payment processing systems, web applications, and data processing systems?



      Answer: B
  • Question 4
    • You have just created a new log bucket to replace the _Default log bucket. You want to route all log entries that are currently routed to the _Default log bucket to this new log bucket in the most efficient manner. What should you do?

      Answer: D
  • Question 5
    • Your organization is building a real-time recommendation engine using ML models that process live user activity data stored in BigQuery and Cloud Storage. Each new model developed is saved to Artifact Registry. This new system deploys models to Google Kubernetes Engine and uses Pub/Sub for message queues. Recent industry news has been reporting attacks exploiting ML model supply chains. You need to enhance the security in this serverless architecture, specifically against risks to the development and deployment pipeline. What should you do? 

      Answer: B
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