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Your application images are built using Cloud Build and pushed to Google Container Registry (GCR). You want to be able to specify a particular version of your application for deployment based on the release version tagged in source control. What should you do when you push the image?

A.

Reference the image digest in the source control tag.

B.

Supply the source control tag as a parameter within the image name.

C.

Use Cloud Build to include the release version tag in the application image.

D.

Use GCR digest versioning to match the image to the tag in source control.

You use Terraform to manage an application deployed to a Google Cloud environment The application runs on instances deployed by a managed instance group The Terraform code is deployed by using aCI/CD pipeline When you change the machine type on the instance template used by the managed instance group, the pipeline fails at the terraform apply stage with the following error message

You need to update the instance template and minimize disruption to the application and the number of pipeline runs What should you do?

A.

Delete the managed instance group and recreate it after updating the instance template

B.

Add a new instance template update the managed instance group to use the new instance template and delete the old instance template

C.

Remove the managed instance group from the Terraform state file update the instance template and reimport the managed instance group.

D.

Set the create_bef ore_destroy meta-argument to true in the lifecycle block on the instance template

You are on-call for an infrastructure service that has a large number of dependent systems. You receive an alert indicating that the service is failing to serve most of its requests and all of its dependent systems with hundreds of thousands of users are affected. As part of your Site Reliability Engineering (SRE) incident management protocol, you declare yourself Incident Commander (IC) and pull in two experienced people from your team as Operations Lead (OLJ and Communications Lead (CL). What should you do next?

A.

Look for ways to mitigate user impact and deploy the mitigations to production.

B.

Contact the affected service owners and update them on the status of the incident.

C.

Establish a communication channel where incident responders and leads can communicate with each other.

D.

Start a postmortem, add incident information, circulate the draft internally, and ask internal stakeholders for input.

You are deploying an application to Cloud Run. The application requires a password to start. Your organization requires that all passwords are rotated every 24 hours, and your application must have the latest password. You need to deploy the application with no downtime. What should you do?

A.

Store the password in Secret Manager and send the secret to the application by using environment variables.

B.

Store the password in Secret Manager and mount the secret as a volume within the application.

C.

Use Cloud Build to add your password into the application container at build time. Ensure that Artifact Registry is secured from public access.

D.

Store the password directly in the code. Use Cloud Build to rebuild and deploy the application each time the password changes.

As part of your company's initiative to shift left on security, the infoSec team is asking all teams to implement guard rails on all the Google Kubernetes Engine (GKE) clusters to only allow the deployment of trusted and approved images You need to determine how to satisfy the InfoSec teams goal of shifting left on security. What should you do?

A.

Deploy Falco or Twistlock on GKE to monitor for vulnerabilities on your running Pods

B.

Configure Identity and Access Management (1AM) policies to create a least privilege model on your GKE clusters

C.

Use Binary Authorization to attest images during your CI CD pipeline

D.

Enable Container Analysis in Artifact Registry, and check for common vulnerabilities and exposures (CVEs) in your container images

Your company runs applications in Google Kubernetes Engine (GKE). Several applications rely on ephemeral volumes. You noticed some applications were unstable due to the DiskPressure node condition on the worker nodes. You need

to identify which Pods are causing the issue, but you do not have execute access to workloads and nodes. What should you do?

A.

Check the node/ephemeral_storage/used_bytes metric by using Metrics Explorer.

B.

Check the metric by using Metrics Explorer.

C.

Locate all the Pods with emptyDir volumes. use the df-h command to measure volume disk usage.

D.

Locate all the Pods with emptyDir volumes. Use the du -sh * command to measure volume disk usage.

You are performing a semi-annual capacity planning exercise for your flagship service You expect a service user growth rate of 10% month-over-month for the next six months Your service is fully containerized and runs on a Google Kubemetes Engine (GKE) standard cluster across three zones with cluster autoscaling enabled You currently consume about 30% of your total deployed CPU capacity and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth o' as a result of zone failure while you avoid unnecessary costs How should you prepare to handle the predicted growth?

A.

Verify the maximum node pool size enable a Horizontal Pod Autoscaler and then perform a load lest to verify your expected resource needs

B.

Because you deployed the service on GKE and are using a cluster autoscaler your GKE cluster will scale automatically regardless of growth rate

C.

Because you are only using 30% of deployed CPU capacity there is significant headroom and you do not need to add any additional capacity for this rate of growth

D.

Proactively add 80% more node capacity to account for six months of 10% growth rate and then perform a load test to ensure that you have enough capacity

You are deploying a Cloud Build job that deploys Terraform code when a Git branch is updated. While testing, you noticed that the job fails. You see the following error in the build logs:

Initializing the backend. ..

Error: Failed to get existing workspaces : querying Cloud Storage failed: googleapi : Error

403

You need to resolve the issue by following Google-recommended practices. What should you do?

A.

Change the Terraform code to use local state.

B.

Create a storage bucket with the name specified in the Terraform configuration.

C.

Grant the roles/ owner Identity and Access Management (IAM) role to the Cloud Build service account on the project.

D.

Grant the roles/ storage. objectAdmin Identity and Access Management (IAM) role to the Cloud Build service account on the state file bucket.

Some of your production services are running in Google Kubernetes Engine (GKE) in the eu-west-1 region. Your build system runs in the us-west-1 region. You want to push the container images from your build system to a scalable registry to maximize the bandwidth for transferring the images to the cluster. What should you do?

A.

Push the images to Google Container Registry (GCR) using the gcr.io hostname.

B.

Push the images to Google Container Registry (GCR) using the us.gcr.io hostname.

C.

Push the images to Google Container Registry (GCR) using the eu.gcr.io hostname.

D.

Push the images to a private image registry running on a Compute Engine instance in the eu-west-1 region.

You are running an application on Compute Engine and collecting logs through Stackdriver. You discover that some personally identifiable information (PII) is leaking into certain log entry fields. You want to prevent these fields from being written in new log entries as quickly as possible. What should you do?

A.

Use the filter-record-transformer Fluentd filter plugin to remove the fields from the log entries in flight.

B.

Use the fluent-plugin-record-reformer Fluentd output plugin to remove the fields from the log entries in flight.

C.

Wait for the application developers to patch the application, and then verify that the log entries are no longer exposing PII.

D.

Stage log entries to Cloud Storage, and then trigger a Cloud Function to remove the fields and write the entries to Stackdriver via the Stackdriver Logging API.