Free Professional-Cloud-Developer – Professional Cloud Developer Practice Test Question

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  Determine whether your file system is corrupted.

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  Access Compute Engine as a different SSH user.

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  Troubleshoot firewall rules or routes on an instance.

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  Check whether your instance boot disk is completely full.

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  Check whether network traffic to or from your instance is being dropped.
  

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  Specify the resource limits and requests in the object specifications.

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  Create a namespace for each team, and attach resource quotas to each namespace.

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  Create a LimitRange to specify the default compute resource requirements for each namespace.

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  Create a Kubernetes service account (KSA) for each application, and assign each KSA to the namespace.

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  Use the Anthos Policy Controller to enforce label annotations on all namespaces. Use taints and tolerations to allow resource sharing for namespaces.
  
  

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  Use the service account attached to the GKE node.

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  Enable Workload Identity in the cluster via the gcloud command-line tool.

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  Access the Google service account keys from a secret management service.

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  Store the Google service account keys in a central secret management service.

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  Use gcloud to bind the Kubernetes service account and the Google service account using roles/iam.workloadIdentity.
  

Select all that apply, then click Submit answer.

• ○

  Determine whether your file system is corrupted.

• ○

  Access Compute Engine as a different SSH user.

• ○

  Troubleshoot firewall rules or routes on an instance.

• ○

  Check whether your instance boot disk is completely full.

• ○

  Check whether network traffic to or from your instance is being dropped.
  
  

Select all that apply, then click Submit answer.

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  Add the label “AUTOSCALE” to the instance group template.

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  Decrease the cool-down period for instances added to the group.

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  Increase the target CPU usage for the instance group autoscaler.

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  Decrease the target CPU usage for the instance group autoscaler.

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  Remove the health-check for individual VMs in the instance group.
  
  

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  Distribute your workload evenly using a multi-zonal node pool.

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  Distribute your workload evenly using multiple zonal node pools.

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  Use cluster autoscaler to resize the number of nodes in the node pool, and use a Horizontal Pod Autoscaler to scale the workload.

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  Create a managed instance group for Compute Engine with the cluster nodes. Configure autoscaling rules for the managed instance group.

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  Create alerting policies in Cloud Monitoring based on GKE CPU and memory utilization. Ask an on-duty engineer to scale the workload by executing a script when CPU and memory usage exceed predefined thresholds.
  

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  Push your source code to Artifact Registry.

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  Submit a Cloud Build job to push the image.

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  Use the pack build command with pack CLI.

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  Include the --source flag with the gcloud run deploy CLI command.

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  Include the --platform=kubernetes flag with the gcloud run deploy CLI command.
  

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  Cloud Run

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  Compute Engine

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  Google Kubernetes Engine

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  App Engine flexible environment
  

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  Traffic Director

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  Service Directory

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  Anthos Service Mesh

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  Internal HTTP(S) Load Balancing
  

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  Cloud Amor

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  Stackdriver Debugger

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  Cloud Security Scanner

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  Stackdriver Error Reporting
  
  

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  Configure Cloud Build to deploy the Cloud Function. If the code passes the tests, a deployment approval is sent to you.

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  Configure Cloud Build to deploy the Cloud Function, using the specific service account as the build agent. Run the unit tests after successful deployment.

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  Configure Cloud Build to run the unit tests. If the code passes the tests, the developer deploys the Cloud Function.

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  Configure Cloud Build to run the unit tests, using the specific service account as the build agent. If the code passes the tests, Cloud Build deploys the Cloud Function.
  

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  Set up a backend with Compute Engine web server instances with a private IP address behind a TCP proxy load balancer.

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  Configure the firewall rules to allow all ingress traffic to connect to the Compute Engine web servers, with each server having a unique external IP address.

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  Configure Cloud Identity-Aware Proxy API for SSH access. Then configure the Compute Engine servers with private IP addresses behind an HTTP(s) load balancer for the application web traffic.

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  Set up a backend with Compute Engine web server instances with a private IP address behind an HTTP(S) load balancer. Set up a bastion host with a public IP address and open firewall ports. Connect to the web instances using the bastion host.
  
  

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  Deploy open source Istio in a multi-cluster deployment on multiple Google Kubernetes Engine (GKE) clusters managed by Anthos.

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  Create a GKE cluster in each environment with Anthos, and use Cloud Run for Anthos to deploy your application to each cluster.

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  Install a GKE cluster in each environment with Anthos, and use Cloud Build to create a Deployment for your application in each cluster.

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  Create a GKE cluster in the cloud and install open-source Kubernetes on-premises. Use an external load balancer service to distribute traffic across the two environments.
  

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  Leave the original Cloud Function as-is and deploy a second Cloud Function with the new API. Use a load balancer to distribute calls between the versions.

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  Leave the original Cloud Function as-is and deploy a second Cloud Function that includes only the changed API. Calls are automatically routed to the correct function.

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  Leave the original Cloud Function as-is and deploy a second Cloud Function with the new API. Use Cloud Endpoints to provide an API gateway that exposes a versioned API.

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  Re-deploy the Cloud Function after making code changes to support the new API. Requests for both versions of the API are fulfilled based on a version identifier included in the call.
  
  

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  Package each component in a separate container. Implement readiness and liveness probes.

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  Package the application in a single container. Use a process management tool to manage each component.

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  Package each component in a separate container. Use a script to orchestrate the launch of the components.

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  Package the application in a single container. Use a bash script as an entrypoint to the container, and then spawn each component as a background job.