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Google Professional-Cloud-Developer certification is recognized by the industry as a valuable credential for developers who want to advance their careers in cloud computing. Google Certified Professional - Cloud Developer certification exam is designed to test the candidate's knowledge and skills in developing and deploying applications on the Google Cloud Platform, including their ability to design and implement scalable and reliable cloud-based solutions. Professional-Cloud-Developer exam also evaluates the candidate's ability to troubleshoot and diagnose issues in cloud environments.

Google Professional-Cloud-Developer Certification is a highly recognized certification exam that aims to validate an individual’s ability to develop, deploy, and manage applications on Google Cloud Platform (GCP). Google Certified Professional - Cloud Developer certification is designed for developers who are familiar with GCP and have experience in software development, and who want to demonstrate their skills and knowledge.

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The Google Professional-Cloud-Developer exam consists of multiple-choice and multiple-select questions, and candidates have two hours to complete it. To pass the exam, candidates must demonstrate their knowledge of GCP products, services, and features, as well as their ability to apply best practices for building and deploying applications on GCP. Professional-Cloud-Developer Exam also tests candidates on their ability to troubleshoot and optimize applications on GCP.

Google Certified Professional - Cloud Developer Sample Questions (Q191-Q196):

NEW QUESTION # 191
Your development team has been tasked with maintaining a .NET legacy application. The application incurs occasional changes and was recently updated. Your goal is to ensure that the application provides consistent results while moving through the CI/CD pipeline from environment to environment. You want to minimize the cost of deployment while making sure that external factors and dependencies between hosting environments are not problematic. Containers are not yet approved in your organization. What should you do?

A. Deploy the application using MS Web Deploy, and make sure to always use the latest, patched MS Windows Server base image in Compute Engine.
B. Rewrite the application using .NET Core, and deploy to Cloud Run. Use revisions to separate the environments.
C. Use Cloud Build to deploy the application as a new Compute Engine image for each build. Use this image in each environment.
D. Use Cloud Build to package the application, and deploy to a Google Kubernetes Engine cluster.Use namespaces to separate the environments.

Answer: C

Explanation:
https://cloud.google.com/architecture/modernization-path-dotnet-applications-google- cloud#phase_1_rehost_in_the_cloud

NEW QUESTION # 192
Your application requires service accounts to be authenticated to GCP products via credentials stored on its host Compute Engine virtual machine instances. You want to distribute these credentials to the host instances as securely as possible. What should you do?

A. Generate a P12 file from the GCP Console after the instance is deployed, and copy the credentials to the host instance before starting the application.
B. Use the instance's service account Application Default Credentials to authenticate to the required resources.
C. Use HTTP signed URLs to securely provide access to the required resources.
D. Commit the credential JSON file into your application's source repository, and have your CI/CD process package it with the software that is deployed to the instance.

Answer: B

Explanation:
Reference: https://cloud.google.com/compute/docs/api/how-tos/authorization

NEW QUESTION # 193
Your company has a BigQuery dataset named "Master" that keeps information about employee travel and expenses. This information is organized by employee department. That means employees should only be able to view information for their department. You want to apply a security framework to enforce this requirement with the minimum number of steps.
What should you do?

A. Create a dataset named Master dataset. Create a separate view for each department in the Master dataset. Give employees access to the specific view for their department.
B. Create a separate dataset for each department. Create a view with an appropriate WHERE clause to select records from a particular dataset for the specific department. Authorize this view to access records from your Master dataset. Give employees the permission to this department- specific dataset.
C. Create a dataset named Master dataset. Create a separate table for each department in the Master dataset. Give employees access to the specific table for their department.
D. Create a separate dataset for each department. Create a data pipeline for each department to copy appropriate information from the Master dataset to the specific dataset for the department.
Give employees the permission to this department-specific dataset.

Answer: A

Explanation:
Create view is easy on one dataset with appropriate where clause. And give permission to department.
Create different dataset(option A) for department is create more steps where question denying it.

NEW QUESTION # 194
You are designing a schema for a table that will be moved from MySQL to Cloud Bigtable. The MySQL table is as follows:

How should you design a row key for Cloud Bigtable for this table?

A. Set Event_timestamp_Account_id as a key.
B. Set Account_id as a key.
C. Set Account_id_Event_timestamp as a key.
D. Set Event_timestamp as a key.

Answer: C

Explanation:
Include a timestamp as part of your row key if you often need to retrieve data based on the time when it was recorded.
For example, your application might need to record performance-related data, such as CPU and memory usage, once per second for a large number of machines. Your row key for this data could combine an identifier for the machine with a timestamp for the data (for example, machine_4223421#1425330757685). Keep in mind that row keys are sorted lexicographically.
https://cloud.google.com/bigtable/docs/schema-design

NEW QUESTION # 195
Your API backend is running on multiple cloud providers. You want to generate reports for the network latency of your API.
Which two steps should you take? (Choose two.)

A. Use Stackdriver Profiler to generate report.
B. Use Stackdriver Debugger to generate report.
C. Use Zipkin collector to gather data.
D. Use Fluentd agent to gather data.
E. Use Stackdriver Trace to generate reports.

Answer: C,E

Explanation:
Zipkin is used for to gather data for latency issues and SD trace purpose is to enable us to have a better view on the application code latency.
https://cloud.google.com/trace/docs/zipkin

NEW QUESTION # 196
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