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Google Professional-Cloud-DevOps-Engineer Test Sample Online & Exam Professional-Cloud-DevOps-Engineer Outline

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With the Google Professional-Cloud-DevOps-Engineer certification exam you will get an opportunity to learn new and in-demand skills. In this way, you will stay updated and competitive in the market and advance your career easily. To do this you just need to pass the Google Cloud Certified - Professional Cloud DevOps Engineer Exam Professional-Cloud-DevOps-Engineer Certification Exam.

Who should take the Google Professional Cloud DevOps Engineer exam

Individuals should pursue the Professional Cloud DevOps Engineer practice exam if they want to demonstrate their expertise and ability to design plan, and prototype a GCP DevOps, implement a GCP Virtual Private Cloud (VPC), implement DevOps security. It's perfect for DevOps engineers, systems administrators or operations team members, or simply any professional who wants in on this specific area of IT and cloud.

Google Professional-Cloud-DevOps-Engineer Certification Exam is a professional-level certification offered by Google Cloud. Google Cloud Certified - Professional Cloud DevOps Engineer Exam certification is designed to validate the skills and expertise of professionals who are responsible for designing, implementing, and managing DevOps practices and processes on the Google Cloud Platform.

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The Google Professional-Cloud-DevOps-Engineer exam covers a wide range of topics including continuous integration and delivery, infrastructure as code, monitoring and logging, automation, and security. It is a comprehensive exam that tests the candidate's ability to design and implement efficient cloud-based systems using Google Cloud technologies. Professional-Cloud-DevOps-Engineer Exam is intended for individuals who have a strong understanding of the DevOps principles and practices and are looking to enhance their skills in cloud-based systems management.

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Sample Questions (Q148-Q153):

NEW QUESTION # 148
You are monitoring a service that uses n2-standard-2 Compute Engine instances that serve large files. Users have reported that downloads are slow. Your Cloud Monitoring dashboard shows that your VMS are running at peak network throughput. You want to improve the network throughput performance. What should you do?

A. Change the machine type for your VMS to n2-standard-8.
B. Deploy a Cloud NAT gateway and attach the gateway to the subnet of the VMS.
C. Deploy the Ops Agent to export additional monitoring metrics.
D. Add additional network interface controllers (NICs) to your VMS.

Answer: A

Explanation:
Explanation
The correct answer is C. Change the machine type for your VMs to n2-standard-8.
According to the Google Cloud documentation, the network throughput performance of a Compute Engine VM depends on its machine type1. The n2-standard-2 machine type has a maximum egress bandwidth of 4 Gbps, which can be a bottleneck for serving large files. By changing the machine type to n2-standard-8, you can increase the maximum egress bandwidth to 16 Gbps, which can improve the network throughput performance and reduce the download time for users. You also need to enable per VM Tier_1 networking performance, which is a feature that allows VMs to achieve higher network performance than the default settings2.
The other options are incorrect because they do not improve the network throughput performance of your VMs. Option A is incorrect because Cloud NAT is a service that allows private IP addresses to access the internet, but it does not increase the network bandwidth or speed3. Option B is incorrect because adding additional network interfaces (NICs) or IP addresses per NIC does not increase ingress or egress bandwidth for a VM1. Option D is incorrect because deploying the Ops Agent can help you monitor and troubleshoot your VMs, but it does not affect the network throughput performance4.

NEW QUESTION # 149
You are building an application that runs on Cloud Run The application needs to access a third-party API by using an API key You need to determine a secure way to store and use the API key in your application by following Google-recommended practices What should you do?

A. Save the API key in Secret Manager as a secret Reference the secret as an environment variable in the Cloud Run application
B. Save the API key in Secret Manager as a secret key Mount the secret key under the /sys/api_key directory and decrypt the key in the Cloud Run application
C. Save the API key in Cloud Key Management Service (Cloud KMS) as a key Reference the key as an environment variable in the Cloud Run application
D. Encrypt the API key by using Cloud Key Management Service (Cloud KMS) and pass the key to Cloud Run as an environment variable Decrypt and use the key in Cloud Run

Answer: A

Explanation:
The best option for storing and using the API key in your application by following Google-recommended practices is to save the API key in Secret Manager as a secret and reference the secret as an environment variable in the Cloud Run application. Secret Manager is a service that allows you to store and manage sensitive data, such as API keys, passwords, and certificates, in Google Cloud. A secret is a resource that represents a logical secret, such as an API key. You can save the API key in Secret Manager as a secret and use IAM policies to control who can access it. You can also reference the secret as an environment variable in the Cloud Run application by using the ${SECRET_NAME} syntax. This way, you can securely store and use the API key in your application without exposing it in your code or configuration files.

NEW QUESTION # 150
Your applications performance in Google Cloud has degraded since the last release You suspect that downstream dependencies might be causing some requests to take longer to complete You need to investigate the issue with your application to determine the cause What should you do?

A. Configure Cloud Trace in your application
B. Configure Error Reporting in your application
C. Configure Cloud Profiler in your application
D. Configure Google Cloud Managed Service for Prometheus in your application

Answer: A

Explanation:
Explanation
The best option for investigating the issue with your application's performance in Google Cloud is to configure Cloud Trace in your application. Cloud Trace is a service that allows you to collect and analyze latency data from your application. You can use Cloud Trace to trace requests across different components of your application, such as downstream dependencies, and identify where they take longer to complete. You can also use Cloud Trace to compare latency data across different versions of your application, and detect any performance degradation or improvement. By using Cloud Trace, you can diagnose and troubleshoot performance issues with your application in Google Cloud.

NEW QUESTION # 151
You support a multi-region web service running on Google Kubernetes Engine (GKE) behind a Global HTTP'S Cloud Load Balancer (CLB). For legacy reasons, user requests first go through a third-party Content Delivery Network (CDN). which then routes traffic to the CLB. You have already implemented an availability Service Level Indicator (SLI) at the CLB level. However, you want to increase coverage in case of a potential load balancer misconfiguration. CDN failure, or other global networking catastrophe. Where should you measure this new SLI?
Choose 2 answers

A. GKE health checks for your application servers
B. Instrumentation coded directly in the client
C. Your application servers' logs
D. Metrics exported from the application servers
E. A synthetic client that periodically sends simulated user requests

Answer: A,E

NEW QUESTION # 152
You work for a global organization and are running a monolithic application on Compute Engine You need to select the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps You want to use historical system metncs to identify the machine type for the application to use You want to follow Google-recommended practices What should you do?

A. Create an Agent Policy to automatically install Ops Agent in all VMs
B. Use the Recommender API and apply the suggested recommendations
C. Review the Cloud Monitoring dashboard for the VM and choose the machine type with the lowest CPU utilization
D. Install the Ops Agent in a fleet of VMs by using the gcloud CLI

Answer: B

Explanation:
The best option for selecting the machine type for the application to use that optimizes CPU utilization by using the fewest number of steps is to use the Recommender API and apply the suggested recommendations.
The Recommender API is a service that provides recommendations for optimizing your Google Cloud resources, such as Compute Engine instances, disks, and firewalls. You can use the Recommender API to get recommendations for changing the machine type of your Compute Engine instances based on historical system metrics, such as CPU utilization. You can also apply the suggested recommendations by using the Recommender API or Cloud Console. This way, you can optimize CPU utilization by using the most suitable machine type for your application with minimal effort.

NEW QUESTION # 153
......

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