Associate-Cloud-Engineer Google Cloud Certified - Associate Cloud Engineer Questions and Answers

Grant the financial team the IAM role of ג€Billing Account Userג€ on the billing account linked to your credit card.

Set up BigQuery billing export and grant your financial department IAM access to query the data.

Create a ticket with Google Billing Support to ask them to send the invoice to your company.

Change the billing account of your projects to the billing account of your company.

Save file automatic first-of-the- month backup for three years Store the backup file in an Archive class Cloud Storage bucket

Convert the automatic first-of-the-month backup to an export file Write the export file to a Coldline class Cloud Storage bucket

Set up an export job for the first of the month Write the export file to an Archive class Cloud Storage bucket

Set up an on-demand backup tor the first of the month Write the backup to an Archive class Cloud Storage bucket

Google Compute Engine

Google App Engine

Cloud Functions

Google Kubernetes Engine

In the Google Cloud console for your organization, select Create role from selection, and choose destination as the startup company's organization

In the Google Cloud console for the startup company, select Create role from selection and choose source as the startup company's Google Cloud organization.

Use the gcloud iam roles copy command, and provide the Organization ID of the startup company's

Google Cloud Organization as the destination.

Use the gcloud iam roles copy command, and provide the project IDs of all projects in the startup company s organization as the destination.

Use Cloud Storage Object Lifecycle Management using Age conditions with SetStorageClass and Delete actions. Set the SetStorageClass action to 90 days and the Delete action to 275 days (365 – 90)

Use Cloud Storage Object Lifecycle Management using Age conditions with SetStorageClass and Delete actions. Set the SetStorageClass action to 90 days and the Delete action to 365 days.

Use gsutil rewrite and set the Delete action to 275 days (365-90).

Use gsutil rewrite and set the Delete action to 365 days.

Use granular logging statements within a Deployment Manager template authored in Python.

Monitor activity of the Deployment Manager execution on the Stackdriver Logging page of the GCP Console.

Execute the Deployment Manager template against a separate project with the same configuration, and monitor for failures.

Execute the Deployment Manager template using the –-preview option in the same project, and observe the state of interdependent resources.

Create an HTTP load balancer with a backend configuration that references an existing instance group. Set the health check to healthy (HTTP).

Create an HTTP load balancer with a backend configuration that references an existing instance group. Define a balancing mode and set the maximum RPS to 10.

Create a managed instance group. Set the Autohealing health check to healthy (HTTP).

Create a managed instance group. Verify that the autoscaling setting is on.

Create a new project, enable the Compute Engine and Cloud SQL APIs in that project, and replicate the setup you have created in the development environment.

Create a new production subnet in the existing VPC and a new production Cloud SQL instance in your existing project, and deploy your application using those resources.

Create a new project, modify your existing VPC to be a Shared VPC, share that VPC with your new project, and replicate the setup you have in the development environment in that new project, in the Shared VPC.

Ask the security team to grant you the Project Editor role in an existing production project used by another division of your company. Once they grant you that role, replicate the setup you have in the development environment in that project.

Migrate the users to Active Directory. Connect the Human Resources system to Active Directory. Turn on Google Cloud Directory Sync (GCDS) for Cloud Identity. Turn on Identity Federation from Cloud Identity to Active Directory.

Organize the users in Cloud Identity into groups. Enforce multi-factor authentication in Cloud Identity.

Turn on identity federation between Cloud Identity and Google Workspace. Enforce multi-factor authentication for domain wide delegation.

Use a third-party identity provider service through federation. Synchronize the users from Google Workplace to the third-party provider in real time.

Create a dataflow job that copies data from Cloud Bigtable and Cloud Storage for specific users.

Create a dataflow job that copies data from Cloud Bigtable and Cloud Spanner for specific users.

Create a Cloud Dataproc cluster that runs a Spark job to extract data from Cloud Bigtable and Cloud Storage for specific users.

Create two separate BigQuery external tables on Cloud Storage and Cloud Bigtable. Use the BigQuery console to join these tables through user fields, and apply appropriate filters.

1. Verify that you are assigned the Project Owners IAM role for this project.

2. Locate the project in the GCP console, click Shut down and then enter the project ID.

1. Verify that you are assigned the Project Owners IAM role for this project.

2. Switch to the project in the GCP console, locate the resources and delete them.

1. Verify that you are assigned the Organizational Administrator IAM role for this project.

2. Locate the project in the GCP console, enter the project ID and then click Shut down.

1. Verify that you are assigned the Organizational Administrators IAM role for this project.

2. Switch to the project in the GCP console, locate the resources and delete them.

Create a health check on port 443 and use that when creating the Managed Instance Group.

Select Multi-Zone instead of Single-Zone when creating the Managed Instance Group.

In the Instance Template, add the label ‘health-check’.

In the Instance Template, add a startup script that sends a heartbeat to the metadata server.

View System Event Logs in Stackdriver. Search for the user’s email as the principal.

View System Event Logs in Stackdriver. Search for the service account associated with the user.

View Data Access audit logs in Stackdriver. Search for the user’s email as the principal.

View the Admin Activity log in Stackdriver. Search for the service account associated with the user.

BigQuery

Cloud SQL

Cloud Spanner

Cloud Datastore

Create a custom role with view-only project permissions. Add the user's account to the custom role.

Create a custom role with view-only service permissions. Add the user's account to the custom role.

Select the built-in IAM project Viewer role. Add the user's account to this role.

Select the built-in IAM service Viewer role. Add the user's account to this role.

Ask the auditor for their Google account, and give them the Viewer role on the project.

Ask the auditor for their Google account, and give them the Security Reviewer role on the project.

Create a temporary account for the auditor in Cloud Identity, and give that account the Viewer role on the project.

Create a temporary account for the auditor in Cloud Identity, and give that account the Security Reviewer role on the project.

Upload the data to BigQuery using the bq command line tool.

Upload the data to Cloud Storage using the gsutil command line tool.

Upload the data into Cloud SQL using the import function in the console.

Upload the data into Cloud Spanner using the import function in the console.

Use gcloud iam roles copy and specify the production project as the destination project.

Use gcloud iam roles copy and specify your organization as the destination organization.

In the Google Cloud Platform Console, use the ‘create role from role’ functionality.

In the Google Cloud Platform Console, use the ‘create role’ functionality and select all applicable permissions.

Create a Data Studio dashboard that uses the related BigQuery tables as a source and give the BI team view access to the Data Studio dashboard.

Create a Service Account for the BI team and distribute a new private key to each member of the BI team.

Use Cloud Scheduler to schedule a batch Dataflow job to copy the data from BigQuery to the BI team's internal data warehouse.

Assign the IAM role of BigQuery User to a Google Group that contains the members of the BI team.

Navigate to Stackdriver Logging and select resource.labels.project_id="*"

Create a Stackdriver Logging Export with a Sink destination to a BigQuery dataset. Configure the table expiration to 60 days.

Create a Stackdriver Logging Export with a Sink destination to Cloud Storage. Create a lifecycle rule to delete objects after 60 days.

Configure a Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery. Configure the table expiration to 60 days.

Use kubectl app deploy .

Use gcloud app deploy .

Create a docker image from the Dockerfile and upload it to Container Registry. Create a Deployment YAML file to point to that image. Use kubectl to create the deployment with that file.

Create a docker image from the Dockerfile and upload it to Cloud Storage. Create a Deployment YAML file to point to that image. Use kubectl to create the deployment with that file.

Upload the image to Cloud Storage and create a Kubernetes Service referencing the image.

Upload the image to Cloud Storage and create a Kubernetes Deployment referencing the image.

Upload the image to Container Registry and create a Kubernetes Service referencing the image.

Upload the image to Container Registry and create a Kubernetes Deployment referencing the image.

Assign the auditor the IAM role roles/logging.privateLogViewer. Perform the export of logs to Cloud Storage.

Assign the auditor the IAM role roles/logging.privateLogViewer. Direct the auditor to also review the logs for changes to Cloud IAM policy.

Assign the auditor’s IAM user to a custom role that has logging.privateLogEntries.list

permission. Perform the export of logs to Cloud Storage.

Assign the auditor’s IAM user to a custom role that has logging.privateLogEntries.list

permission. Direct the auditor to also review the logs for changes to Cloud IAM policy.

Enable the Node Auto-Repair feature for your GKE cluster.

Enable the Node Auto-Upgrades feature for your GKE cluster.

Select the latest available cluster version for your GKE cluster.

Select “Container-Optimized OS (cos)” as a node image for your GKE cluster.

Add the cluster’s API as a new Type Provider in Deployment Manager, and use the new type to create the DaemonSet.

Use the Deployment Manager Runtime Configurator to create a new Config resource that contains the DaemonSet definition.

With Deployment Manager, create a Compute Engine instance with a startup script that uses kubectl to create the DaemonSet.

In the cluster’s definition in Deployment Manager, add a metadata that has kube-system as key and the DaemonSet manifest as value.

In Google Cloud, configure the VPC as a host for Shared VPC.

In Google Cloud, configure the VPC for VPC Network Peering.

Create bastion hosts both in your on-premises environment and on Google Cloud. Configure both as proxy servers using their public IP addresses.

Set up Cloud VPN between the infrastructure on-premises and Google Cloud.

Provision preemptible Compute Engine instances.

Provision Compute Engine instances with GPUs attached.

Provision Compute Engine instances with local SSDs attached.

Provision Compute Engine instances with M1 machine type.

Filter the Activity log to view the Configuration category. Filter the Resource type to Service Account.

Filter the Activity log to view the Configuration category. Filter the Resource type to Google Project.

Filter the Activity log to view the Data Access category. Filter the Resource type to Service Account.

Filter the Activity log to view the Data Access category. Filter the Resource type to Google Project.

Use Cloud Logging filters to create log-based metrics for firewall and instance actions. Monitor the changes and set up reasonable alerts.

Install Kibana on a compute Instance. Create a log sink to forward Cloud Audit Logs filtered for firewalls and

compute instances to Pub/Sub. Target the Pub/Sub topic to push messages to the Kibana instance. Analyze the logs on Kibana in real time.

Turn on Google Cloud firewall rules logging, and set up alerts for any insert, update, or delete events.

Create a log sink to forward Cloud Audit Logs filtered for firewalls and compute instances to Cloud Storage.

Use BigQuery to periodically analyze log events in the storage bucket.

Use the gsutil to rewrite the storage class for the bucket Change the default storage class for the bucket

Use the gsutil to rewrite the storage class for the bucket Set up Object Lifecycle management on the bucket

Create a new bucket and change the default storage class for the bucket Set up Object Lifecycle management on lite bucket

Create a new bucket and change the default storage class for the bucket import the files from the previous bucket into the new bucket

When creating the VM, use machine type n1-standard-96.

When creating the VM, use Intel Skylake as the CPU platform.

Create the VM using Compute Engine default settings. Use gcloud to modify the running instance to have 96 vCPUs.

Start the VM using Compute Engine default settings, and adjust as you go based on Rightsizing Recommendations.

Cloud Run for Anthos

Cloud Run

App Engine Standard

Cloud Functions.

Use Cloud Bigtable for data storage.

Use Cloud SQL for data storage.

Use Cloud Spanner for data storage.

Use Firestore for data storage.

Create and deploy a Custom Resource Definition per microservice.

Create and deploy a Docker Compose File.

Create and deploy a Job per microservice.

Create and deploy a Deployment per microservice.

Create an alert policy to send a notification when the HTTP response latency exceeds the specified threshold.

Implement an App Engine service which invokes the Cloud Monitoring API and sends a notification in case of anomalies.

Use the Cloud Monitoring dashboard to observe latency and take the necessary actions when the response latency exceeds the specified threshold.

Export Cloud Monitoring metrics to BigQuery and use a Looker Studio dashboard to monitor your web applications latency.

Increase the size of the disk to 1 TB.

Increase the allocated CPU to the instance.

Migrate to use a Local SSD on the instance.

Migrate to use a Regional SSD on the instance.

Create an Instance template with the container image, and deploy a Managed Instance Group with Autoscaling.

Upload Docker images to Artifact Registry, and deploy the application on Google Kubernetes Engine using Standard mode.

Upload Docker images to the Cloud Storage, and deploy the application on Google Kubernetes Engine using Standard mode.

Upload Docker images to Artifact Registry, and deploy the application on Cloud Run.

Migrate from MySQL to Cloud SQL, from Kafka to Memorystore, and from Cloud SQL for PostgreSQL to Cloud SQL

Migrate from MySQL to Cloud Spanner, from Kafka to Memorystore, and from Cloud SOL for PostgreSQL to Cloud SQL

Migrate from MySQL to Cloud SOL, from Kafka to Pub/Sub, and from Cloud SOL for PostgreSQL to BigQuery.

Migrate from MySQL to Cloud Spanner, from Kafka to Pub/Sub. and from Cloud SQL for PostgreSQL to BigQuery

Configure the Horizontal Pod Autoscaler for availability and configure the cluster autoscaler for suggestions.

Configure the Horizontal Pod Autoscaler for availability and configure the Vertical Pod Autoscaler recommendations for suggestions.

Configure the Vertical Pod Autoscaler recommendations for availability and configure the Cluster autoscaler for suggestions.

Configure the Vertical Pod Autoscaler recommendations for availability and configure the Horizontal Pod Autoscaler for suggestions.

1. Update your instances’ metadata to add the following value: snapshot–schedule: 0 1 * * *

2. Update your instances’ metadata to add the following value: snapshot–retention: 30

1. In the Cloud Console, go to the Compute Engine Disks page and select your instance’s disk.

2. In the Snapshot Schedule section, select Create Schedule and configure the following parameters:

–Schedule frequency: Daily

–Start time: 1:00 AM – 2:00 AM

–Autodelete snapshots after 30 days

1. Create a Cloud Function that creates a snapshot of your instance’s disk.

2.Create a Cloud Function that deletes snapshots that are older than 30 days.

3.Use Cloud Scheduler to trigger both Cloud Functions daily at 1:00 AM.

1. Create a bash script in the instance that copies the content of the disk to Cloud Storage.

2.Create a bash script in the instance that deletes data older than 30 days in the backup Cloud Storage bucket.

3.Configure the instance’s crontab to execute these scripts daily at 1:00 AM.

Deploy the new version in the same application and use the --migrate option.

Deploy the new version in the same application and use the --splits option to give a weight of 99 to the current version and a weight of 1 to the new version.

Create a new App Engine application in the same project. Deploy the new version in that application. Use the App Engine library to proxy 1% of the requests to the new version.

Create a new App Engine application in the same project. Deploy the new version in that application. Configure your network load balancer to send 1% of the traffic to that new application.

Organize projects under folders for each department. Configure both organization policies and log sinks on the folders

Organize projects under folders for each department. Configure organization policies on the organization and log sinks on the folders.

Use a standard naming convention for projects that includes the department name. Configure organization policies on the organization and log sinks on the projects.

Use a standard naming convention for projects that includes the department name. Configure both organization policies and log sinks on the projects.

Use the command gcloud auth login and point it to the private key

Use the command gcloud auth activate-service-account and point it to the private key

Place the private key file in the installation directory of the Cloud SDK and rename it to "credentials ison"

Place the private key file in your home directory and rename it to ‘’GOOGLE_APPUCATION_CREDENTiALS".

Run gcloud iam roles list. Review the output section.

Run gcloud iam service-accounts list. Review the output section.

Navigate to the project and then to the IAM section in the GCP Console. Review the members and roles.

Navigate to the project and then to the Roles section in the GCP Console. Review the roles and status.

• Create a custom role with Compute Engine, Cloud Functions, and Cloud SQL permissions in one project within the Google Cloud organization.

• Copy the role across all projects created within the organization with the gcloud iam roles copy command.

• Assign the role to developers in those projects.

• Add all developers to a Google group in Google Groups for Workspace.

• Assign the predefined role of Compute Admin to the Google group at the Google Cloud organization level.

• Add all developers to a Google group in Cloud Identity.

• Assign predefined roles for Compute Engine, Cloud Functions, and Cloud SQL permissions to the Google group for each project in the Google Cloud organization.

• Add all developers to a Google group in Cloud Identity.

• Create a custom role with Compute Engine, Cloud Functions, and Cloud SQL permissions at the Google Cloud organization level.

• Assign the custom role to the Google group.

In the project where the images are stored, grant the Storage Object Viewer IAM role to the service account used by the Kubernetes nodes.

When you create the GKE cluster, choose the Allow full access to all Cloud APIs option under ‘Access scopes’.

Create a service account, and give it access to Cloud Storage. Create a P12 key for this service account and use it as an imagePullSecrets in Kubernetes.

Configure the ACLs on each image in Cloud Storage to give read-only access to the default Compute Engine service account.

Use Deployment Manager templates to describe the proposed changes and store them in a Cloud Storage bucket.

Use Deployment Manager templates to describe the proposed changes and store them in Cloud Source Repositories.

Apply the change in a development environment, run gcloud compute instances list, and then save the output in a shared Storage bucket.

Apply the change in a development environment, run gcloud compute instances list, and then save the output in Cloud Source Repositories.

Deploy the application on GKE, and add a HorizontalPodAutoscaler to the deployment.

Deploy the application on GKE, and add a VerticalPodAutoscaler to the deployment.

Create a GKE cluster with autoscaling enabled on the node pool. Set a minimum and maximum for the size of the node pool.

Create a separate node pool for each application, and deploy each application to its dedicated node pool.

Enable node auto-provisioning on the GKE cluster.

Create a VerticalPodAutscaler for those workloads.

Create a node pool with preemptible VMs and GPUs attached to those VMs.

Create a node pool of instances with GPUs, and enable autoscaling on this node pool with a minimum size of 1.

Configure Cloud Identity-Aware Proxy (or HTTPS resources

Configure Cloud Identity-Aware Proxy for SSH and TCP resources.

Create an SSH keypair and store the public key as a project-wide SSH Key

Create an SSH keypair and store the private key as a project-wide SSH Key

Split the users from business units to multiple projects.

Apply a user- or project-level custom query quota for BigQuery data warehouse.

Create separate copies of your BigQuery data warehouse for each business unit.

Split your BigQuery data warehouse into multiple data warehouses for each business unit.

Change your BigQuery query model from on-demand to flat rate. Apply the appropriate number of slots to each Project.

Configure username and password by using gcloud configure set proxy/username and gcloud configure set proxy/ proxy/password commands.

Encode username and password in sha256 encoding, and save it to a text file. Use filename as a value in the gcloud configure set core/custom_ca_certs_file command.

Provide values for CLOUDSDK_USERNAME and CLOUDSDK_PASSWORD in the gcloud CLI tool configure file.

Set the CLOUDSDK_PROXY_USERNAME and CLOUDSDK_PROXY PASSWORD properties by using environment variables in your command line tool.

Create a service account with an access scope. Use the access scope ‘https://www.googleapis.com/auth/devstorage.write_only’.

Create a service account with an access scope. Use the access scope ‘https://www.googleapis.com/auth/cloud-platform’.

Create a service account and add it to the IAM role ‘storage.objectCreator’ for that bucket.

Create a service account and add it to the IAM role ‘storage.objectAdmin’ for that bucket.

Run gcloud iam roles describe roles/spanner.databaseUser. Add the users to the role.

Run gcloud iam roles describe roles/spanner.databaseUser. Add the users to a new group. Add the group to the role.

Run gcloud iam roles describe roles/spanner.viewer --project my-project. Add the users to the role.

Run gcloud iam roles describe roles/spanner.viewer --project my-project. Add the users to a new group. Add the group to the role.

Build a lifecycle policy to delete Cloud Storage objects after 45 days.

Use signed URLs to allow suppliers limited time access to store their objects.

Set up an SFTP server for your application, and create a separate user for each supplier.

Build a Cloud function that triggers a timer of 45 days to delete objects that have expired.

Develop a script that loops through all Cloud Storage buckets and deletes any buckets that are older than 45 days.

HTTPS Load Balancer

Network Load Balancer

SSL Proxy Load Balancer

Internal TCP/UDP Load Balancer. Add a firewall rule allowing ingress traffic from 0.0.0.0/0 on the target instances.

Add the support team group to the roles/monitoring.viewer role

Add the support team group to the roles/spanner.databaseUser role.

Add the support team group to the roles/spanner.databaseReader role.

Add the support team group to the roles/stackdriver.accounts.viewer role.

Ask the other team to grant your default App Engine Service account the role of BigQuery Job User.

Ask the other team to grant your default App Engine Service account the role of BigQuery Data Viewer.

In Cloud IAM of your project, ensure that the default App Engine service account has the role of BigQuery Data Viewer.

In Cloud IAM of your project, grant a newly created service account from the other team the role of BigQuery Job User in your project.

Change the subnet IP range from 10.0.0.0/20 to 10.0.0.0/22.

Change the subnet IP range from 10.0 0.0/20 to 10.0.0.0718.

Add a secondary IP range 10.1.0.0/20 to the subnet.

Convert the subnet IP range from IPv4 to IPv6

In the Google Cloud console, visualize the costs related to the projects in the Reports section.

In the Google Cloud console, visualize the costs related to the projects in the Cost breakdown section.

In the Google Cloud console, use the export functionality of the Cost table. Create a Looker Studiodashboard on top of the CSV export.

Configure Cloud Billing data export to BigOuery for the billing account. Create a Looker Studio dashboard on top of the BigOuery export.

Reserve the IP 10.0.3.21 as a static internal IP address using gcloud and assign it to the licensing server.

Reserve the IP 10.0.3.21 as a static public IP address using gcloud and assign it to the licensing server.

Use the IP 10.0.3.21 as a custom ephemeral IP address and assign it to the licensing server.

Start the licensing server with an automatic ephemeral IP address, and then promote it to a static internal IP address.

Create a Cloud Bigtable cluster and use the HBase API

Deploy MongoDB Alias from the Google Cloud Marketplace

Download a MongoDB installation package and run it on Compute Engine instances

Download a MongoDB installation package, and run it on a Managed Instance Group

Write a script that runs gsutil Is -| – gs://myapp-gcp-ace-logs/** to find and remove items older than 90 days. Schedule the script with cron.

Write a lifecycle management rule in JSON and push it to the bucket with gsutil lifecycle set config-json-file.

Write a lifecycle management rule in XML and push it to the bucket with gsutil lifecycle set config-xml-file.

Write a script that runs gsutil Is -Ir gs://myapp-gcp-ace-logs/** to find and remove items older than 90 days. Repeat this process every morning.

When creating the instances, specify a Service Account for each instance

When creating the instances, assign the name of each Service Account as instance metadata

After starting the instances, use gcloud compute instances update to specify a Service Account for each instance

After starting the instances, use gcloud compute instances update to assign the name of the relevant Service Account as instance metadata

Link the acquired company’s projects to your company's billing account.

Configure the acquired company's billing account and your company's billing account to export the billing data into the same BigQuery dataset.

Migrate the acquired company’s projects into your company’s GCP organization. Link the migrated projects to your company's billing account.

Create a new GCP organization and a new billing account. Migrate the acquired company's projects and your company's projects into the new GCP organization and link the projects to the new billing account.

Review the Compute Engine activity logs Select and review the Admin Event logs

Review the Compute Engine activity logs Select and review the System Event logs

Install the Cloud Logging Agent In Cloud Logging review the Compute Engine syslog logs

Install the Cloud Logging Agent In Cloud Logging, review the Compute Engine operation logs

Expose the application by using an external TCP Network Load Balancer.

Expose the application by using a TCP Proxy Load Balancer.

Expose the application by using an SSL Proxy Load Balancer.

Expose the application by using an internal TCP Network Load Balancer.

For each GCP product in the solution, review the pricing details on the products pricing page. Use the pricing calculator to total the monthly costs for each GCP product.

For each GCP product in the solution, review the pricing details on the products pricing page. Create a Google Sheet that summarizes the expected monthly costs for each product.

Provision the solution on GCP. Leave the solution provisioned for 1 week. Navigate to the Billing Report page in the Google Cloud Platform Console. Multiply the 1 week cost to determine the monthly costs.

Provision the solution on GCP. Leave the solution provisioned for 1 week. Use Stackdriver to determine the provisioned and used resource amounts. Multiply the 1 week cost to determine the monthly costs.

Deploy the container on Cloud Run for Anthos, and set the minimum number of instances to zero

Deploy the container on Cloud Run (fully managed), and set the minimum number of instances to zero.

Deploy the container on App Engine flexible environment with autoscaling. and set the value min_instances to zero in the app yaml

Deploy the container on App Engine flexible environment with manual scaling, and set the value instances to zero in the app yaml

Set up a low-priority (65534) rule that blocks all egress and a high-priority rule (1000) that allows only the appropriate ports.

Set up a high-priority (1000) rule that pairs both ingress and egress ports.

Set up a high-priority (1000) rule that blocks all egress and a low-priority (65534) rule that allows only the appropriate ports.

Set up a high-priority (1000) rule to allow the appropriate ports.

Search for the CMS solution in Google Cloud Marketplace. Use gcloud CLI to deploy the solution.

Search for the CMS solution in Google Cloud Marketplace. Deploy the solution directly from Cloud Marketplace.

Search for the CMS solution in Google Cloud Marketplace. Use Terraform and the Cloud Marketplace ID to deploy the solution with the appropriate parameters.

Use the installation guide of the CMS provider. Perform the installation through your configuration management system.

Check the app.yaml file for your application and check project settings.

Check the web-application.xml file for your application and check project settings.

Go to Deployment Manager and review settings for deployment of applications.

Go to Cloud Shell and run gcloud config list to review the Google Cloud configuration used for deployment.

Implement a Cloud Run job to rotate all service account keys periodically in pj-sa. Enforce an org policy to deny service account key creation with an exception to pj-sa.

Implement a Kubernetes Cronjob to rotate all service account keys periodically. Disable attachment of

service accounts to resources in all projects with an exception to pj-sa.

Enforce an org policy constraint allowing the lifetime of service account keys to be 24 hours. Enforce an org policy constraint denying service account key creation with an exception on pj-sa.

Enforce a DENY org policy constraint over the lifetime of service account keys for 24 hours. Disable attachment of service accounts to resources in all projects with an exception to pj-sa.

Create a Cloud Monitoring Workspace.

Create a VPC network in the project.

Enable the compute googleapis.com API.

Grant yourself the IAM role of Compute Admin.

Select Multi-Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Coldline Storage.

Select Multi-Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Nearline Storage.

Select Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Nearline Storage.

Select Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Coldline Storage.

Using the GCP Console, filter the Activity log to view the information.

Using the GCP Console, filter the Stackdriver log to view the information.

View the bucket in the Storage section of the GCP Console.

Create a trace in Stackdriver to view the information.

Set the maximum number of instances to 1.

Decrease the maximum number of instances to 3.

Use a TCP health check instead of an HTTP health check.

Increase the initial delay of the HTTP health check to 200 seconds.

Create a Google Kubernetes Engine cluster, and use horizontal pod autoscaling to scale the application.

Create an instance template, and use the template in a managed instance group with autoscaling configured.

Create an instance template, and use the template in a managed instance group that scales up and down based on the time of day.

Use a set of third-party tools to build automation around scaling the application up and down, based on Stackdriver CPU usage monitoring.

Create a new service with the new version of the application. Split traffic between this version and the version that is currently running.

Create a new revision with the new version of the application. Split traffic between this version and the version that is currently running.

Create a new service with the new version of the application. Add an HTTP Load Balancer in front of both services.

Create a new revision with the new version of the application. Add an HTTP Load Balancer in front of both revisions.

Select Google Kubernetes Engine. Use a single-node cluster with a small instance type.

Select Google Kubernetes Engine. Use a three-node cluster with micro instance types.

Select Compute Engine. Use preemptible VM instances of the appropriate standard machine type.

Select Compute Engine. Use VM instance types that support micro bursting.

Use service account credentials in your on-premises application.

Use gcloud to create a key file for the service account that has appropriate permissions.

Set up direct interconnect between your data center and Google Cloud Platform to enable authentication for your on-premises applications.

Go to the IAM & admin console, grant a user account permissions similar to the service account permissions, and use this user account for authentication from your data center.

Use a custom mode VPC network, configure static routes, and use active/passive routing

Use an automatic mode VPC network, configure static routes, and use active/active routing

Use a custom mode VPC network use Cloud Router border gateway protocol (86P) routes, and use active/passive routing

Use an automatic mode VPC network, use Cloud Router border gateway protocol (BGP) routes and configure policy-based routing