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Google Professional Cloud Developer Certification Path

The Google Professional Cloud Developer Certification is the highest level of certification mainly focussing to the Google Professional Cloud Developer.There is no prerequisite for this exam but still it would be best to follow some sequence in order to prove immense knowledge as a Google Professional Cloud Developer.You can complete Google Associate Certifications then approach for the professional certification. For more information related to Google cloud certification track Google-certification-path

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Google Professional-Cloud-Developer certification exam is a challenging but rewarding credential that validates one’s expertise in developing cloud-native applications on the Google Cloud Platform. Google Certified Professional - Cloud Developer certification is ideal for developers who work with Google Cloud technologies and want to demonstrate their skills to potential employers or clients. If you are interested in pursuing this certification, it is recommended that you have a solid understanding of cloud application development principles, containerization technologies, and best practices for building scalable and secure applications.

Google Professional-Cloud-Developer Certification Exam is an important credential for developers who want to demonstrate their expertise in developing cloud-based applications using GCP. Google Certified Professional - Cloud Developer certification is recognized by employers and peers in the industry as a mark of excellence, and it can help developers advance their careers and increase their earning potential. Professional-Cloud-Developer Exam is a rigorous test of a developer's knowledge and skills, and passing it requires significant preparation and study. However, the benefits of obtaining the certification can be significant, both in terms of personal and professional development.

Google Certified Professional - Cloud Developer Sample Questions (Q171-Q176):

NEW QUESTION # 171
You are deploying a microservices application to Google Kubernetes Engine (GKE). The application will receive daily updates. You expect to deploy a large number of distinct containers that will run on the Linux operating system (OS). You want to be alerted to any known OS vulnerabilities in the new containers. You want to follow Google-recommended best practices. What should you do?

A. Use the Container Analysis REST API to call Container Analysis to scan new container images. Review the vulnerability results before each deployment.
B. Use the gcloud CLI to call Container Analysis to scan new container images. Review the vulnerability results before each deployment.
C. Enable Container Analysis, and upload new container images to Artifact Registry. Review the vulnerability results before each deployment.
D. Enable Container Analysis, and upload new container images to Artifact Registry. Review the critical vulnerability results before each deployment.

Answer: A

Explanation:
https://cloud.google.com/container-analysis/docs/automated-scanning-howto
https://cloud.google.com/container-analysis/docs/os-overview says: The Container Scanning API allows you to automate OS vulnerability detection, scanning each time you push an image to Container Registry or Artifact Registry. Enabling this API also triggers language package scans for Go and Java vulnerabilities (Preview).

NEW QUESTION # 172
You configured your Compute Engine instance group to scale automatically according to overall CPU usage. However, your application's response latency increases sharply before the cluster has finished adding up instances. You want to provide a more consistent latency experience for your end users by changing the configuration ot the instance group autoscaler. Which two configuration changes should you make? (Choose two.)

A. Add the label "AUTOSCALE" to the instance group template.
B. Decrease the cool-down period for instances added to the group.
C. Remove the health-check for individual VMs in the instance group.
D. Increase the target CPU usage for the instance group autoscaler.
E. Decrease the target CPU usage for the instance group autoscaler.

Answer: A,D

NEW QUESTION # 173
You are building a CI/CD pipeline that consists of a version control system, Cloud Build, and Container Registry. Each time a new tag is pushed to the repository, a Cloud Build job is triggered, which runs unit tests on the new code builds a new Docker container image, and pushes it into Container Registry. The last step of your pipeline should deploy the new container to your production Google Kubernetes Engine (GKE) cluster. You need to select a tool and deployment strategy that meets the following requirements:
* Zero downtime is incurred
* Testing is fully automated
* Allows for testing before being rolled out to users
* Can quickly rollback if needed
What should you do?

A. Trigger a Spinnaker pipeline configured as an A/B test of your new code and, if it is successful, deploy the container to production.
B. Trigger a Spinnaker pipeline configured as a canary test of your new code and, if it is successful, deploy the container to production.
C. Trigger another Cloud Build job that uses the Kubernetes CLI tools to deploy your new container to your GKE cluster, where you can perform a shadow test.
D. Trigger another Cloud Build job that uses the Kubernetes CLI tools to deploy your new container to your GKE cluster, where you can perform a canary test.

Answer: C

Explanation:
https://cloud.google.com/architecture/implementing-deployment-and-testing-strategies-on-gke#perform_a_shadow_test With a shadow test, you test the new version of your application by mirroring user traffic from the current application version without impacting the user requests.

NEW QUESTION # 174
You migrated some of your applications to Google Cloud. You are using a legacy monitoring platform deployed on-premises for both on-premises and cloud-deployed applications. You discover that your notification system is responding slowly to time-critical problems in the cloud applications. What should you do?

A. Use Cloud Logging and Cloud Monitoring to capture logs, monitor, and send alerts. Send them to your existing platform.
B. Install the Cloud Monitoring agent on your Compute Engine instances.
C. Migrate some traffic back to your old platform. Perform A/B testing on the two platforms concurrently.
D. Replace your monitoring platform with Cloud Monitoring.

Answer: A

NEW QUESTION # 175
Your operations team has asked you to create a script that lists the Cloud Bigtable, Memorystore, and Cloud SQL databases running within a project. The script should allow users to submit a filter expression to limit the results presented. How should you retrieve the data?

A. Run gcloud bigtable instances list, gcloud redis instances list, and gcloud sql databases list. Use a filter within the application, and then display the results
B. Use the HBase API, Redis API, and MySQL connection to retrieve database lists. Combine the results, and then apply the filter to display the results
C. Run gcloud bigtable instances list, gcloud redis instances list, and gcloud sql databases list. Use --filter flag with each command, and then display the results
D. Use the HBase API, Redis API, and MySQL connection to retrieve database lists. Filter the results individually, and then combine them to display the results

Answer: C

Explanation:
Explanation
https://cloud.google.com/sdk/gcloud/reference/topic/filters
Most gcloud commands return a list of resources on success. By default they are pretty-printed on the standard output. The --format=NAME[ATTRIBUTES](PROJECTION) and --filter=EXPRESSION flags along with projections can be used to format and change the default output to a more meaningful result. Use the --format flag to change the default output format of a command. For details run $ gcloud topic formats.

NEW QUESTION # 176
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