Online Access Free Professional-Cloud-Developer Exam Questions

Your teammate has asked you to review the code below. Its purpose is to efficiently add a large number of small rows to a BigQuery table.

Which improvement should you suggest your teammate make?

• A.Write each row to a Cloud Storage object in parallel, then load into BigQuery.
• B.Write each row to a Cloud Storage object, then load into BigQuery.
• C.Perform the inserts in parallel by creating multiple threads.
• D.Include multiple rows with each request.

You recently deployed an Apigee API proxy to your organization across two regions. Both regions are configured with a separate backend that is hosting the API. You need to configure Apigee to route traffic to the appropriate local region backend. What should you do?

• A.Configure a regional internal Application Load Balancer in each region, and use health checks to verify that each backend is active. Create a DNS A record that contains the IP addresses of both regions' load balancers. Configure a TargetServer for each region that uses this DNS name.
• B.Configure a TargetServer for each region's backend host names. Configure the API proxy to choose the TargetServer based on the system.region.name flow variable.
• C.Configure a global external Application Load Balancer and configure each region's backend with a different regional backend service. Each region communicates to this single global external Application Load Balancer as its TargetServer.
• D.Create a TargetEndpoint with a weighted load balancing algorithm. Configure the API proxy to use the same weights for each region's backend.

You have containerized a legacy application that stores its configuration on an NFS share. You need to deploy this application to Google Kubernetes Engine (GKE) and do not want the application serving traffic until after the configuration has been retrieved. What should you do?

• A.Create a PersistentVolumeClaim on the GKE cluster. Access the configuration files from the volume, and start the service using an ENTRYPOINT script.
• B.Use the COPY statement in the Dockerfile to load the configuration into the container image.
  Verify that the configuration is available, and start the service using an ENTRYPOINT script.
• C.Add a startup script to the GKE instance group to mount the NFS share at node startup. Copy the configuration files into the container, and start the service using an ENTRYPOINT script.
• D.Use the gsutil utility to copy files from within the Docker container at startup, and start the service using an ENTRYPOINT script.

You are currently pushing container images to Artifact Registry and deploying a containerized microservices application to GKE. After deploying the application, you notice that the services do not behave as expected. You use the kubectl get pods command to inspect the state of the application Pods, and discover that one of the Pods has a state of CrashLoopBackoff. How should you troubleshoot the Pod?

• A.Execute the gcloud projects get-iam-policy PROJECT_ID command where the PROJECT_ID parameter is the name of the project where your Artifact Registry resides. Inspect the IAM bindings of the node pool's service account. Validate if the service account has the roles/artifactregistry.reader role.
• B.In the Google Cloud console, navigate to Cloud Logging in the project of the cluster's VPC. Enter a filter to show denied egress traffic to the Private Google Access CIDR range. Validate if egress traffic is denied from your GKE cluster to the Private Google Access CIDR range.
• C.Run the kubectl logs POD_NAME command where the POD_NAME parameter is the name of the problematic Pod. Analyze the logs of the Pod from previous runs to determine the root cause of failed start attempts of the Pod.
• D.Connect to the problematic Pod by running the kubectl exec -it POD_NAME - /bin/bash command where the POD_NAME parameter is the name of the problematic Pod. Inspect the logs in the
  /var/log/messages folder to determine the root cause.

You are developing a new API that creates requests on an asynchronous message service.
Requests will be consumed by different services. You need to expose the API by using a gRPC interface while minimizing infrastructure management overhead. How should you deploy the API?

• A.Deploy your API as a Cloud Run service. Create a Pub/Sub topic, and configure your API to push messages to the topic.
• B.Deploy your API to a GKE cluster. Create a Kafka cluster, and configure your API to write messages to the cluster.
• C.Deploy your API on a Compute Engine instance. Create a Kafka cluster, and configure your API to write messages to the cluster.
• D.Deploy your API to App Engine. Create a Pub/Sub topic, and configure your API to push messages to the topic.