Professional-Cloud-Developer 無料問題集「Google Certified Professional - Cloud Developer」

（A）Deploy the website on App Engine as three separate services.

（B）Deploy the website on Cloud Functions as three separate functions.

（C）Deploy the website on App Engine and use traffic splitting.

（D）Deploy the website on Cloud Functions and use traffic splitting.

（A）Set up a VPN tunnel between your company network and your instance's VPC location on Google Cloud. Configure the required firewall rules and routing information to both the on-premises and Google Cloud networks.

（B）Add an HTTP(S) load balancer in front of the instance, and set up Identity-Aware Proxy (IAP).
Configure the IAP settings to allow your company domain to access the website.

（C）Add a public IP address to your instance, and restrict access to the instance using firewall rules. Allow your company's proxy as the only source IP address.

（D）Add a public IP address to your instance, and allow traffic from the internet. Generate a random hash, and create a subdomain that includes this hash and points to your instance. Distribute this DNS address to your company's employees.

（A）Deploy the third-party solution as a DaemonSet

（B）Deploy the third-party solution using Terraform and deploy the logging Pod as a Kubernetes Deployment

（C）Modify your container image to include the monitoring software

（D）Use SSH to connect to the GKE node, and install the software manually

（A）Create a Cron job that runs the following command every 24 hours: gcloud builds submit.

（B）Create a webhook build trigger that runs the build file in response to HTTP POST calls to the webhook URL.

（C）Create a Pub/Sub topic to be notified when code is pushed to the repository. Create a Pub/Sub trigger that runs the build file when an event is published to the topic.

（D）Create a build trigger that runs the build file in response to a repository code being pushed to the development branch.

（A）Move the data to a Cloud Storage bucket, and mount the bucket on the filesystem using Cloud Storage FUSE.

（B）Move the data to a Compute Engine persistent disk, take a snapshot, create multiple disks from the snapshot, and attach each disk to its own instance.

（C）Move the data to a Cloud Storage bucket, and copy the data to the boot disk of the instance via a startup script.

（D）Move the data to a Compute Engine persistent disk, and attach the disk in read-only mode to multiple Compute Engine virtual machine instances.

（A）Assign the Project Owner role.

（B）Assign the Project Editor role.

（C）Assign the Cloud SQL Client role.

（D）Assign the Cloud SQL Editor role.

（A）Instrument your microservices by installing the OpenTelemetry tracing package Update your application code to send traces to Trace for inspection and analysis Create an analysis report on Trace to analyze user requests

（B）Install tcpdump on your GKE nodes. Run tcpdump to capture network traffic over an extended period of time to collect data Analyze the data files using Wireshark to determine the cause of high latency

（C）Configure GKE workload metrics using kubect1 Select all Pods to send their metrics to Cloud Monitoring. Create a custom dashboard of application metrics in Cloud Monitoring to determine performance bottlenecks of your GKE cluster

（D）Update your microservices to log HTTP request methods and URL paths to STDOUT Use the logs router to send container logs to Cloud Logging Create filters in Cloud Logging to evaluate the latency of user requests across different methods and URL paths.

（A）Use Stackdriver Trace to plot query execution time.

（B）Use Stackdriver Monitoring to plot query execution times.

（C）Use Stackdriver Trace to plot API execution time.

（D）Use Stackdriver Monitoring to plot slot usage.

（A）Store the logs in Cloud Logging as custom logs with a custom retention period.

（B）Store the logs in a Cloud Storage bucket with a 3-year retention period.

（C）Store the logs in a Cloud Storage bucket with a 1-year retention period. After 1 year, move the logs to another bucket with a 2-year retention period.

（D）Store the logs in a Cloud Storage bucket with bucket lock turned on.

（A）Debugger

（B）Google Cloud Armor

（C）Web Security Scanner

（D）Error Reporting

（A）Deploy a new Docker registry in a VPC and use Cloud Build worker pools inside the VPC to run the build pipeline.

（B）Add the -cache-from argument to the Docker build step in your build config file.

（C）Store image artifacts in a Cloud Storage bucket in the same region as the Cloud Run instance.

（D）Remove the step that pushes the container to Artifact Registry.

（A）Deploy Zonal clusters

（B）Deploy Regional clusters

（C）Deploy GKE on-premises clusters

（D）Deploy Multi-Zone clusters

（A）hadoop fs cp [LOCAL_OBJECT] gs://[DESTINATION_BUCKET_NAME]/

（B）gcloud dataproc cp [LOCAL_OBJECT] gs://[DESTINATION_BUCKET_NAME]/

（C）gcloud cp [LOCAL_OBJECT] gs://[DESTINATION_BUCKET_NAME]/

（D）gsutil cp [LOCAL_OBJECT] gs://[DESTINATION_BUCKET_NAME]/

（A）Install the Stackdriver Logging Agent and configure it to send the application logs.

（B）Change the application to log to /var/log so that its logs are automatically sent to Stackdriver Logging.

（C）Use a Stackdriver Logging Library to log directly from the application to Stackdriver Logging.

（D）Provide the log file folder path in the metadata of the instance to configure it to send the application logs.

（A）Use a proxyless Traffic Director configuration to connect the application to the service.

（B）Use Traffic Director with a sidecar proxy to connect the application to the service.

（C）Configure the legacy service's firewall to allow health checks originating from the proxy.

（D）Configure the legacy service's firewall to allow health checks originating from the Traffic Director control plane.

（E）Configure the legacy service's firewall to allow health checks originating from the application.