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| Section | Objectives |
|---|
| Manage application performance monitoring | - Monitor and troubleshoot applications
- 1. Configure logging and tracing
- 2. Analyze metrics and alerts
- 3. Optimize application performance
|
| 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
|
| Build and test applications | - Manage development environments
- 1. Implement CI/CD pipelines
- 2. Perform application testing
- 3. Build application artifacts
|
| Integrate applications with Google Cloud services | - Integrate with data and storage services
- 1. Implement authentication and authorization
- 2. Use messaging and event-driven services
- 3. Integrate with Google Cloud APIs
|
| 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
|
>> Professional-Cloud-Developer Valid Test Question <<
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Google Certified Professional - Cloud Developer Sample Questions (Q38-Q43):
NEW QUESTION # 38
Your application in App Engine standard environment receives a large amount of traffic. You are concerned that deploying changes to the application could affect all users negatively. You want to avoid full-scale load testing due to cost concerns, but you still want to deploy new features as quickly as possible. Which approach should you take?
- A. Use the local development environment to perform load testing outside Google Cloud Platform.
- B. Use App Engine traffic splitting to have a smaller part of the users test out new features, and slowly adjust traffic splitting until all users get the new features.
- C. Before allowing users to access new features, deploy as a new version and perform smoke tests.
Then enable all users to access the new features. - D. Schedule weekly load tests against the production application.
Answer: B
Explanation:
A is incorrect because there are patterns to perform A/B testing and reduce the need for regular independent load tests.
B is incorrect because it does not accurately simulate the production environment.
C is incorrect because smoke tests are still exposing all users to new features immediately as described.
D is correct because traffic splitting allows real user testing without impacting all users and reduces load testing costs.
http://cloud.google.com/trace
NEW QUESTION # 39
You work for an ecommerce company. You are developing a new application with the following requirements:
- The application must have access to the most up-to-date data at all
times.
- Due to company policy, data older than 30 days must be automatically
deleted.
You need to determine which service should host the database, and how to configure the data deletion. You want to use the most efficient solution. What should you do?
- A. Configure Spanner to host the database. Use Data Catalog to delete data older than 30 days.
- B. Configure Spanner to host the database. Create a time-to-live (TTL) policy that deletes data older than 30 days.
- C. Configure Bigtable to host the database. Create a garbage collection policy in Bigtable that deletes data older than 30 days.
- D. Configure Bigtable to host the database. Create a time-to-live policy that deletes data older than
30 days.
Answer: C
Explanation:
Bigtable is a highly scalable, NoSQL database that supports efficient time-to-live (TTL) policies through garbage collection. By configuring a garbage collection policy, you can automatically delete data older than 30 days, ensuring compliance with the company's data retention policy without additional management overhead.
Using Spanner would be less efficient for this use case, as it is a relational database designed for strong consistency, not for simple TTL-based data expiry. Bigtable's TTL feature with garbage collection is optimized for NoSQL data with automated, policy-driven deletions, making it the most efficient choice for your requirements.
NEW QUESTION # 40
You are developing a microservice-based application that will run on Google Kubernetes Engine (GKE).
Some of the services need to access different Google Cloud APIs. How should you set up authentication of these services in the cluster following Google-recommended best practices? (Choose two.)
- A. Enable Workload Identity in the cluster via the gcloud command-line tool.
- B. Store the Google service account keys in a central secret management service.
- C. Use gcloud to bind the Kubernetes service account and the Google service account using roles/iam.workloadIdentity.
- D. Use the service account attached to the GKE node.
- E. Access the Google service account keys from a secret management service.
Answer: A,C
Explanation:
Explanation
https://cloud.google.com/kubernetes-engine/docs/how-to/workload-identity
NEW QUESTION # 41
Please refer to the following information to answer the questions on the right.
Debra has brought her iPad Pro to you for troubleshooting. She has been experiencing very slow charging of the battery and says the only way she can get a full charge is to leave the iPad alone for more than 12 hours.
She brought in an Apple Power adapter and Lightning to USB cable. When you examine the power adapter, you notice that it is an iPhone power adapter not an iPad power adapter. You also noticed she was using an iPhone 6s while waiting to see you. Debra thinks her iPad is defective because her iPhone has no issue charging with this power adapter and cable.
Based on the information Debra provided, in which problem space does this issue fit?
- A. Environmental
- B. User Data
- C. Educational opportunity
- D. Software
Answer: D
NEW QUESTION # 42
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 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.
- 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 canary test.
- D. Trigger a Spinnaker pipeline configured as a canary test of your new code and, if it is successful, deploy the container to production.
Answer: B
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 # 43
......
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