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Google Professional-Cloud-Developer Exam Syllabus Topics:

Section	Objectives
Design scalable, available, and reliable cloud-native applications	- Design highly performant applications and APIs 1. Design resilient and scalable application architectures 2. Choose storage options for application data 3. Design secure applications
Deploy applications	- Deploy applications to Google Cloud 1. Deploy applications using Cloud Run 2. Manage application rollout strategies 3. Deploy applications to Google Kubernetes Engine
Manage application performance monitoring	- Monitor and troubleshoot applications 1. Analyze metrics and alerts 2. Optimize application performance 3. Configure logging and tracing
Integrate applications with Google Cloud services	- Integrate with data and storage services 1. Integrate with Google Cloud APIs 2. Implement authentication and authorization 3. Use messaging and event-driven services
Build and test applications	- Manage development environments 1. Perform application testing 2. Build application artifacts 3. Implement CI/CD pipelines

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Google Certified Professional - Cloud Developer Sample Questions (Q382-Q387):

NEW QUESTION # 382
You are writing a single-page web application with a user-interface that communicates with a third-party API for content using XMLHttpRequest. The data displayed on the UI by the API results is less critical than other data displayed on the same web page, so it is acceptable for some requests to not have the API data displayed in the UI. However, calls made to the API should not delay rendering of other parts of the user interface. You want your application to perform well when the API response is an error or a timeout.
What should you do?

A. Set the asynchronous option for your requests to the API to false and omit the widget displaying the API results when a timeout or error is encountered.
B. Set the asynchronous option for your request to the API to true and omit the widget displaying the API results when a timeout or error is encountered.
C. Catch timeout or error exceptions from the API call and keep trying with exponential backoff until the API response is successful.
D. Catch timeout or error exceptions from the API call and display the error response in the UI widget.

Answer: A

NEW QUESTION # 383
Your code is running on Cloud Functions in project A.
It is supposed to write an object in a Cloud Storage
bucket owned by project B.
However, the write call is failing with the error "403 Forbidden".
What should you do to correct the problem?

A. Enable the Cloud Storage API in project B.
B. Grant your user account the roles/iam.serviceAccountUser role for the service-PROJECTA@gcf-adminrobot.
iam.gserviceaccount.com service account.
C. Grant the service-PROJECTA@gcf-admin-robot.iam.gserviceaccount.com service account the roles/ storage.objectCreator role for the Cloud Storage bucket.
D. Grant your user account the roles/storage.objectCreator role for the Cloud Storage bucket.

Answer: B

NEW QUESTION # 384
You have an application in production. It is deployed on Compute Engine virtual machine instances controlled by a managed instance group. Traffic is routed to the instances via a HTTP(s) load balancer. Your users are unable to access your application. You want to implement a monitoring technique to alert you when the application is unavailable.
Which technique should you choose?

A. Managed instance group - heath checks
B. Cloud Load Balancing - heath checks
C. Stackdriver uptime checks
D. Smoke tests

Answer: C

Explanation:
Reference: https://medium.com/google-cloud/stackdriver-monitoring-automation-part-3-uptime-checks-
476b8507f59c

NEW QUESTION # 385
You want to notify on-call engineers about a service degradation in production while minimizing development time.
What should you do?

A. Use Cloud Pub/Sub to monitor resources and raise alerts.
B. Use Stackdriver Error Reporting to capture errors and raise alerts.
C. Use Stackdriver Monitoring to monitor resources and raise alerts.
D. Use Cloud Function to monitor resources and raise alerts.

Answer: D

NEW QUESTION # 386
Your team develops services that run on Google Cloud. You want to process messages sent to a Pub/Sub topic, and then store them. Each message must be processed exactly once to avoid duplication of data and any data conflicts. You need to use the cheapest and most simple solution. What should you do?

A. Process the messages with a Cloud Function, and write the results to a BigQuery location where you can run a job to deduplicate the data.
B. Process the messages with a Dataproc job, and write the output to storage.
C. Process the messages with a Dataflow streaming pipeline using Apache Beam's PubSubIO package, and write the output to storage.
D. Retrieve the messages with a Dataflow streaming pipeline, store them in Cloud Bigtable, and use another Dataflow streaming pipeline to deduplicate messages.

Answer: C

Explanation:
Explanation
https://cloud.google.com/dataflow/docs/concepts/streaming-with-cloud-pubsub

NEW QUESTION # 387
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