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You are creating a CI/CD pipeline to perform Terraform deployments of Google Cloud resources Your CI/CD tooling is running in Google Kubernetes Engine (GKE) and uses an ephemeral Pod for each pipeline run You must ensure that the pipelines that run in the Pods have the appropriate Identity and Access Management (1AM) permissions to perform the Terraform deployments You want to follow Google-recommended practices for identity management What should you do?

Choose 2 answers

ACreate a new Kubernetes service account, and assign the service account to the Pods Use Workload Identity to authenticate as the Google service account

BCreate a new JSON service account key for the Google service account store the key as a Kubernetes secret, inject the key into the Pods, and set the boogle_application_credentials environment variable

CCreate a new Google service account, and assign the appropriate 1AM permissions

DCreate a new JSON service account key for the Google service account store the key in the secret management store for the CI/CD tool and configure Terraform to use this key for authentication

EAssign the appropriate 1AM permissions to the Google service account associated with the Compute Engine VM instances that run the Pods

Question 2

Your application services run in Google Kubernetes Engine (GKE). You want to make sure that only images from your centrally-managed Google Container Registry (GCR) image registry in the altostrat-images project can be deployed to the cluster while minimizing development time. What should you do?

ACreate a custom builder for Cloud Build that will only push images to gcr.io/altostrat-images.

BUse a Binary Authorization policy that includes the whitelist name pattern gcr.io/attostrat-images/.

CAdd logic to the deployment pipeline to check that all manifests contain only images from gcr.io/altostrat-images.

DAdd a tag to each image in gcr.io/altostrat-images and check that this tag is present when the image is deployed.

Question 3

Your organization has a containerized web application that runs on-premises As part of the migration plan to Google Cloud you need to select a deployment strategy and platform that meets the following acceptance criteria

1 The platform must be able to direct traffic from Android devices to an Android-specific microservice

2 The platform must allow for arbitrary percentage-based traffic splitting

3 The deployment strategy must allow for continuous testing of multiple versions of any microservice

What should you do?

ADeploy the canary release of the application to Cloud Run Use traffic splitting to direct 10% of user traffic to the canary release based on the revision tag

BDeploy the canary release of the application to App Engine Use traffic splitting to direct a subset of user traffic to the new version based on the IP address

CDeploy the canary release of the application to Compute Engine Use Anthos Service Mesh with Compute Engine to direct 10% of user traffic to the canary release by configuring the virtual service.

DDeploy the canary release to Google Kubernetes Engine with Anthos Sen/ice Mesh Use traffic splitting to direct 10% of user traffic to the new version based on the user-agent header configured in the virtual service

Question 4

You have deployed a fleet Of Compute Engine instances in Google Cloud. You need to ensure that monitoring metrics and logs for the instances are visible in Cloud Logging and Cloud Monitoring by your company's operations and cyber

security teams. You need to grant the required roles for the Compute Engine service account by using Identity and Access Management (IAM) while following the principle of least privilege. What should you do?

AGrant the logging.editor and monitoring.metricwriter roles to the Compute Engine service accounts.

BGrant the Logging. admin and monitoring . editor roles to the Compute Engine service accounts.

CGrant the logging. logwriter and monitoring. editor roles to the Compute Engine service accounts.

DGrant the logging. logWriter and monitoring. metricWriter roles to the Compute Engine service accounts.

Answer : A

The correct answer is D. Grant the logging.logWriter and monitoring.metricWriter roles to the Compute Engine service accounts.

According to the Google Cloud documentation, the Compute Engine service account is a Google-managed service account that is automatically created when you enable the Compute Engine API1.This service account is used by default to run your Compute Engine instances and access other Google Cloud services on your behalf1.To ensure that monitoring metrics and logs for the instances are visible in Cloud Logging and Cloud Monitoring, you need to grant the following IAM roles to the Compute Engine service account23:

The logging.logWriter role allows the service account to write log entries to Cloud Logging4.

The monitoring.metricWriter role allows the service account to write custom metrics to Cloud Monitoring5.

These roles grant the minimum permissions that are needed for logging and monitoring, following the principle of least privilege. The other roles are either unnecessary or too broad for this purpose.For example, the logging.editor role grants permissions to create and update logs, log sinks, and log exclusions, which are not required for writing log entries6. The logging.admin role grants permissions to delete logs, log sinks, and log exclusions, which are not required for writing log entries and may pose a security risk if misused. The monitoring.editor role grants permissions to create and update alerting policies, uptime checks, notification channels, dashboards, and groups, which are not required for writing custom metrics.

Service accounts, Service accounts.Setting up Stackdriver Logging for Compute Engine, Setting up Stackdriver Logging for Compute Engine.Setting up Stackdriver Monitoring for Compute Engine, Setting up Stackdriver Monitoring for Compute Engine.Predefined roles, Predefined roles.Predefined roles, Predefined roles.Predefined roles, Predefined roles. [Predefined roles], Predefined roles. [Predefined roles], Predefined roles.

Question 5

You recently created a Cloud Build pipeline for deploying Terraform code stored in a GitHub repository. You make Terraform code changes in short-lived branches and sometimes use tags during development. You tag releases with a semantic version when they are ready for deployment. You require your pipeline to apply the Terraform code whenever there is a new release, and you need to minimize operational overhead. What should you do?

ACreate a build trigger with the * branch pattern.

BCreate a build trigger with the \d+\.\d+\.\d* tag pattern.

CCreate a build trigger with the .* tag pattern.

DCreate a build trigger with the \d*\.\d+\.\d* branch pattern.

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