Professional-Cloud-Developer Google Certified Professional - Cloud Developer exact Exam Questions

Google Certified Professional - Cloud Developer

Last Update 13 hours ago Total Questions : 265

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Question # 31

For this question, refer to the HipLocal case study.

Which Google Cloud product addresses HipLocal’s business requirements for service level indicators and objectives?

Cloud Profiler

Cloud Monitoring

Cloud Trace

Cloud Logging

Question # 32

HipLocal has connected their Hadoop infrastructure to GCP using Cloud Interconnect in order to query data stored on persistent disks.

Which IP strategy should they use?

Create manual subnets.

Create an auto mode subnet.

Create multiple peered VPCs.

Provision a single instance for NAT.

Question # 33

HipLocal wants to reduce the number of on-call engineers and eliminate manual scaling.

Which two services should they choose? (Choose two.)

Use Google App Engine services.

Use serverless Google Cloud Functions.

Use Knative to build and deploy serverless applications.

Use Google Kubernetes Engine for automated deployments.

Use a large Google Compute Engine cluster for deployments.

Question # 34

Which database should HipLocal use for storing user activity?

BigQuery

Cloud SQL

Cloud Spanner

Cloud Datastore

Question # 35

For this question, refer to the HipLocal case study.

HipLocal ' s application uses Cloud Client Libraries to interact with Google Cloud. HipLocal needs to configure authentication and authorization in the Cloud Client Libraries to implement least privileged access for the application. What should they do?

Create an API key. Use the API key to interact with Google Cloud.

Use the default compute service account to interact with Google Cloud.

Create a service account for the applicatio n. Export and deploy the private key for the application. Use the service account to interact with Google Cloud.

Create a service account for the application and for each Google Cloud API used by the application. Export and deploy the private keys used by the application. Use the service account with one Google Cloud API to interact with Google Cloud.

Question # 36

For this question, refer to the HipLocal case study.

How should HipLocal redesign their architecture to ensure that the application scales to support a large increase in users?

Use Google Kubernetes Engine (GKE) to run the application as a microservice. Run the MySQL database on a dedicated GKE node.

Use multiple Compute Engine instances to run MySQL to store state information. Use a Google Cloud-managed load balancer to distribute the load between instances. Use managed instance groups for scaling.

Use Memorystore to store session information and Cloud SQL to store state information. Use a Google Cloud-managed load balancer to distribute the load between instances. Use managed instance groups for scaling.

Use a Cloud Storage bucket to serve the application as a static website, and use another Cloud St orage bucket to store user state information.

Question # 37

HipLocal ' s.net-based auth service fails under intermittent load.

What should they do?

Use App Engine for autoscaling.

Use Cloud Functions for autoscaling.

Use a Compute Engine cluster for the service.

Use a dedicated Compute Engine virtual machine instance for the service.

Question # 38

Which service should HipLocal use for their public APIs?

Cloud Armor

Cloud Functions

Cloud Endpoints

Shielded Virtual Machines

Question # 39

For this question, refer to the HipLocal case study.

How should HipLocal increase their API development speed while continuing to provide the QA team with a stable testing environment that meets feature requirements?

Include unit tests in their code, and prevent deployments to QA until all tests have a passing status.

Include performance tests in their code, and prevent deployments to QA until all tests have a passing status.

Create health checks for the QA environment, and redeploy the APIs at a later time if the environment is unhealthy.

Redeploy the APIs to App Engine using Traffic Splitting. Do not move QA traffic to the new versions if errors are found.