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To prepare for the Google Professional-Cloud-Developer Exam, candidates can take advantage of various resources provided by Google, including training courses, practice exams, and documentation. Candidates can also gain practical experience by working with Google Cloud technologies, such as Google Kubernetes Engine, Google App Engine, and Google Cloud Functions. By passing the Google Professional-Cloud-Developer Exam, candidates can demonstrate their proficiency in cloud development and increase their credibility as a cloud developer.

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As a professional cloud developer, you will be responsible for designing, building, and managing cloud-based applications that scale for use by various organizations. Professional-Cloud-Developer Exam covers knowledge of several cloud services offered by Google, including Google App Engine, Google Container Engine (Kubernetes), and Google Kubernetes Engine. Developers must become proficient in scripting languages such as Python, Java, and JavaScript for a smooth experience in building and deploying applications on Google Cloud.

Google Certified Professional - Cloud Developer Sample Questions (Q231-Q236):

NEW QUESTION # 231
Your company's development teams want to use Cloud Build in their projects to build and push Docker images to Container Registry. The operations team requires all Docker images to be published to a centralized, securely managed Docker registry that the operations team manages.
What should you do?

A. Use Container Registry to create a registry in each development team's project.
Configure the Cloud Build build to push the Docker image to the project's registry.
Grant the operations team access to each development team's registry.
B. Create a separate project for the operations team that has Container Registry configured.
Create a Service Account for each development team and assign the appropriate permissions to allow it access to the operations team's registry.
Store the service account key file in the source code repository and use it to authenticate against the operations team's registry.
C. Create a separate project for the operations team that has the open source Docker Registry deployed on a Compute Engine virtual machine instance.
Create a username and password for each development team.
Store the username and password in the source code repository and use it to authenticate against the operations team's Docker registry.
D. Create a separate project for the operations team that has Container Registry configured.
Assign appropriate permissions to the Cloud Build service account in each developer team's project to allow access to the operation team's registry.

Answer: D

Explanation:
Container Registry is a good choice to store containers in a secure manageable way. It is possible to have ContainerRegistry in One project and push to it from Cloud Build of another project by adding appropriate service account as a member of a Cloud Storage Bucket used to host containers with the role Cloud Build Service Account.

NEW QUESTION # 232
You developed a Python script that retrieves information from files that are uploaded to Cloud Storage and writes the information to Bigtable. You have completed testing on your local environment and created the python-script service account with the Bigtable User IAM role. You want to deploy the code with the appropriate authentication while following Google-recommended practices. What should you do?

A. 1. Deploy your image to Cloud Run. Create a trigger in Cloud Scheduler that triggers the service every minute.
2. Create a service account key for authentication.
B. 1. Deploy your image to Cloud Run. Create a trigger in Cloud Scheduler that triggers the service every minute.
2. Configure IAM binding for authentication.
C. 1. Deploy your code to Cloud Run functions. Create a Cloud Storage trigger.
2. Configure IAM binding for authentication.
D. 1. Deploy your code to Cloud Run functions. Create a Cloud Storage trigger.
2. Create a service account key for authentication

Answer: B

Explanation:
Deploying the Python script to Cloud Run with a Cloud Scheduler trigger allows for flexible, managed execution, while maintaining security best practices. Using IAM binding for authentication avoids the need for managing service account keys, aligning with Google- recommended practices for security by using Application Default Credentials (ADC). Cloud Scheduler can trigger the Cloud Run service at the desired frequency, allowing the script to process new files as needed.
Using Cloud Functions with a Cloud Storage trigger could work, but Cloud Run provides more flexibility and control for containerized applications. Additionally, creating a service account key for authentication is not recommended because managing and securing keys is more complex and less secure than using IAM roles and ADC.

NEW QUESTION # 233
Your company needs a database solution that stores customer purchase history and meets the following requirements:
- Customers can query their purchase immediately after submission.
- Purchases can be sorted on a variety of fields.
- Distinct record formats can be stored at the same time.
Which storage option satisfies these requirements?

A. Cloud Storage using an object read
B. Firestore in Native mode
C. Cloud SQL using a SQL SELECT statement
D. Firestore in Datastore mode using a global query

Answer: B

Explanation:
https://cloud.google.com/datastore/docs/firestore-or-datastore

NEW QUESTION # 234
You have an application running in App Engine. Your application is instrumented with Stackdriver Trace. The /product-details request reports details about four known unique products at /sku-details as shown below. You want to reduce the time it takes for the request to complete. What should you do?

A. Store the /sku-details information in a database, and replace the webservice call with a database query.
B. Change the Persistent Disk type to SSD.
C. Change /product-details to perform the requests in parallel.
D. Increase the size of the instance class.

Answer: C

NEW QUESTION # 235
Your application performs well when tested locally, but it runs significantly slower when you deploy it to App Engine standard environment. You want to diagnose the problem. What should you do?

A. Use Stackdriver Trace to determine which functions within the application have higher latency.
B. Add logging commands to the application and use Stackdriver Logging to check where the latency problem occurs.
C. Use Stackdriver Debugger Snapshots to look at a point-in-time execution of the application.
D. File a ticket with Cloud Support indicating that the application performs faster locally.

Answer: B

NEW QUESTION # 236
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