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Google Professional-Cloud-Developer Exam Syllabus Topics:

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

>> Professional-Cloud-Developer Pruefungssimulationen <<

Professional-Cloud-Developer Fragenpool - Professional-Cloud-Developer Prüfungsaufgaben

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Google Certified Professional - Cloud Developer Professional-Cloud-Developer Prüfungsfragen mit Lösungen (Q30-Q35):

30. Frage
You work for an organization that manages an ecommerce site. Your application is deployed behind a global HTTP(S) load balancer. You need to test a new product recommendation algorithm. You plan to use A/B testing to determine the new algorithm's effect on sales in a randomized way. How should you test this feature?

Antwort: D

Begründung:
Explanation
https://cloud.google.com/load-balancing/docs/https/traffic-management-global#traffic_actions_weight-based_tra Deploying a new version of an existing production service generally incurs some risk. Even if your tests pass in staging, you probably don't want to subject 100% of your users to the new version immediately. With traffic management, you can define percentage-based traffic splits across multiple backend services.
For example, you can send 95% of the traffic to the previous version of your service and 5% to the new version of your service. After you've validated that the new production version works as expected, you can gradually shift the percentages until 100% of the traffic reaches the new version of your service. Traffic splitting is typically used for deploying new versions, A/B testing, service migration, and similar processes.
https://cloud.google.com/traffic-director/docs/advanced-traffic-management#weight-based_traffic_splitting_for_
https://cloud.google.com/architecture/implementing-deployment-and-testing-strategies-on-gke#split_the_traffic_
https://cloud.google.com/load-balancing/docs/https/traffic-management-global#traffic_actions_weight-based_tra


31. Frage
You are developing an ecommerce application that stores customer, order, and inventory data as relational tables inside Cloud Spanner. During a recent load test, you discover that Spanner performance is not scaling linearly as expected. Which of the following is the cause?

Antwort: C

Begründung:
https://cloud.google.com/spanner/docs/schema-and-data-model#choosing_a_primary_key


32. Frage
You recently deployed a Go application on Google Kubernetes Engine (GKE). The operations team has noticed that the application's CPU usage is high even when there is low production traffic. The operations team has asked you to optimize your application's CPU resource consumption. You want to determine which Go functions consume the largest amount of CPU. What should you do?

Antwort: A

Begründung:
Explanation
https://cloud.google.com/profiler/docs/about-profiler
Cloud Profiler is a statistical, low-overhead profiler that continuously gathers CPU usage and memory-allocation information from your production applications. It attributes that information to the source code that generated it, helping you identify the parts of your application that are consuming the most resources, and otherwise illuminating your applications performance characteristics.
https://cloud.google.com/profiler/docs


33. Frage
You are a developer that works for a local concert venue. Customers use your company's website to purchase tickets for events. You need to provide customers with immediate confirmation when a selected seat has been reserved. How should you design the ticket ordering process?

Antwort: B

Begründung:
Immediate Feedback: This approach allows for synchronous processing, meaning the customer can receive immediate confirmation as soon as the reservation is processed.
Scalability: Using a managed instance group ensures that your application can scale according to demand, handling multiple requests effectively during peak times.
Simplicity: This design keeps the architecture straightforward, allowing for easier debugging and monitoring.
Other options involve asynchronous processing, which may introduce delays in confirmation for the user, making them less suitable for immediate feedback requirements.


34. Frage
Your application is deployed in a Google Kubernetes Engine (GKE) cluster. You want to expose this application publicly behind a Cloud Load Balancing HTTP(S) load balancer. What should you do?

Antwort: C

Begründung:
Reference:
https://cloud.google.com/kubernetes-engine/docs/concepts/ingress


35. Frage
......

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