Practice Free Associate-Cloud-Engineer Google Cloud Certified - Associate Cloud Engineer Exam Questions Answers With Explanation

– Create Compute Engine resources in us–central1–b.–Balance the load across both us–central1–a and us–central1–b.

– Create a Managed Instance Group and specify us–central1–a as the zone.–Configure the Health Check with a short Health Interval.

– Create an HTTP(S) Load Balancer.–Create one or more global forwarding rules to direct traffic to your VMs.

– Perform regular backups of your application.–Create a Cloud Monitoring Alert and be notified if your application becomes unavailable.–Restore from backups when notified.

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.

In Cloud Identity, set up SSO with Google as an identity provider to access custom SAML apps.

In Cloud Identity, set up SSO with a third-party identity provider with Google as a service provider.

Obtain OAuth 2.0 credentials, configure the user consent screen, and set up OAuth 2.0 for Mobile & Desktop Apps.

Obtain OAuth 2.0 credentials, configure the user consent screen, and set up OAuth 2.0 for Web Server Applications.

Configure Cloud NAT for all subnets of your VPC to be used when egressing from the VM instances.

Create a private zone on Cloud DNS, and configure the applications with the DNS name.

Configure the IP of the database as custom metadata for each instance, and query the metadata server.

Query the Compute Engine internal DNS from the applications to retrieve the IP of the database.

Assign the finance team only the Billing Account User role on the billing account.

Assign the engineering team only the Billing Account User role on the billing account.

Assign the finance team the Billing Account User role on the billing account and the Project Billing Manager role on the organization.

Assign the engineering team the Billing Account User role on the billing account and the Project Billing Manager role on the organization.

Run gcloud builds submit --tag gcr.io/img-278322/acme_track_n_trace

Run gcloud builds submit --tag gcr.io/img-278322/acme_track_n_trace:v1

Run gcloud builds submit --tag gcr.io/prod-278986/acme_track_n_trace

Run gcloud builds submit --tag gcr.io/prod-278986/acme_track_n_trace:v1

Enable OS Login for all VMs. Use IAM roles to grant user permissions.

Enable OS Login for all VMs. Write custom startup scripts to update user permissions.

Require your developers to create public SSH keys. Make the owner of the public key the root user.

Require your developers to create public SSH keys. Write custom startup scripts to update user permissions.

Create two configurations using gcloud config. Write a script that sets configurations as active, individually. For each configuration, use gcloud compute instances list to get a list of compute resources.

Create two configurations using gsutil config. Write a script that sets configurations as active, individually. For each configuration, use gsutil compute instances list to get a list of compute resources.

Go to Cloud Shell and export this information to Cloud Storage on a daily basis.

Go to GCP Console and export this information to Cloud SQL on a daily basis.

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.

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.

Use gcloud to expand the IP range of the current subnet.

Delete the subnet, and recreate it using a wider range of IP addresses.

Create a new project. Use Shared VPC to share the current network with the new project.

Create a new subnet with the same starting IP but a wider range to overwrite the current subnet.

Using the Cloud SDK, create a new project, enable the Compute Engine API in that project, and then create the instance specifying your new project.

Enable the Compute Engine API in the Cloud Console, use the Cloud SDK to create the instance, and then use the ––project flag to specify a new project.

Using the Cloud SDK, create the new instance, and use the ––project flag to specify the new project.Answer yes when prompted by Cloud SDK to enable the Compute Engine API.

Enable the Compute Engine API in the Cloud Console. Go to the Compute Engine section of the Console to create a new instance, and look for the Create In A New Project option in the creation form.

Use Spanner for all data.

Use Cloud SQL for customer data, Cloud Storage (Coldline) for historical logs, and BigQuery for sensor data.

Use Cloud SQL for customer data, Cloud Storage (Archive) for historical logs, and Bigtable for sensor data.

Use Firestore for customer data, Cloud Storage (Nearline) for historical logs, and Bigtable for sensor data.

• Navigate to Cloud Mentioning in the Google Cloud console, and create a custom monitoring job for theBigtable instance to track all changes.• Create an alert by using webhook endpoints. with the SIEM endpoint as a receiver

• Navigate to the Audit Logs page in the Google Cloud console, and enable Data Read. Data Write and Admin Read logs for the Bigtable instance• Create a Pub/Sub topic as a Cloud Logging sink destination, and add your SIEM as a subscriber to the topic.

• Install the Ops Agent on the Bigtable instance during configuration. K• Create a service account with read permissions for the Bigtable instance.• Create a custom Dataflow job with this service account to export logs to the company ' s SIEM system.

• Navigate to the Audit Logs page in the Google Cloud console, and enable Admin Write logs for theBiglable instance.• Create a Cloud Functions instance to export logs from Cloud Logging to your SIEM.

.00.0.0/0

10.0.0.0/8

172.16.0.0/12

192.168.0.0/16

Load data in Cloud Datastore and run a SQL query against it.

Create a BigQuery table and load data in BigQuery. Run a SQL query on this table and drop this table after you complete your request.

Create external tables in BigQuery that point to Cloud Storage buckets and run a SQL query on these external tables to complete your request.

Create a Hadoop cluster and copy the AVRO file to NDFS by compressing it. Load the file in a hive table and provide access to your analysts so that they can run SQL queries.

kubectl get deployments –output=pods

gcloud get pods –selector=”app=prod”

kubectl get pods -I “app=prod”

gcloud list gke-deployments -filter={pod }

Create a Cloud Scheduler task to regularly scan your projects and delete mismatched users.

Create a Cloud Scheduler task to regularly scan your resources and delete mismatched users.

Set an organizational policy constraint to limit identities by domain to automatically remove mismatched users.

Set an organizational policy constraint to limit identities by domain, and then retroactively remove the existing mismatched users.

1. Create a subnetwork in the same VPC, in europe-west1.2. Create the new instance in the new subnetwork and use the first instance ' s private address as the endpoint.

1. Create a VPC and a subnetwork in europe-west1.2. Expose the application with an internal load balancer.3. Create the new instance in the new subnetwork and use the load balancer ' s address as the endpoint.

1. Create a subnetwork in the same VPC, in europe-west1.2. Use Cloud VPN to connect the two subnetworks.3. Create the new instance in the new subnetwork and use the first instance ' s private address as the endpoint.

1. Create a VPC and a subnetwork in europe-west1.2. Peer the 2 VPCs.3. Create the new instance in the new subnetwork and use the first instance ' s private address as the endpoint.

Add the user to roles/iam.roleAdmin role.

Add the user to roles/iam.securityAdmin role.

Add the user to roles/iam.serviceAccountUser role.

Add the user to roles/iam.serviceAccountAdmin role.

Configure a Standard multi-zonal GKE cluster.

Configure an Autopilot GKE cluster.

Configure a Standard zonal GKE cluster.

Configure a Standard regional GKE cluster.

Create the instance without a public IP address.

Create the instance with Private Google Access enabled.

Create a deny-all egress firewall rule on the VPC network.

Create a route on the VPC to route all traffic to the instance over the VPN tunnel.

Create a service account per team, and grant the service account the Project Editor role. Ask the teams to provision their infrastructure through the Google Cloud CLI (gcloud CLI), while impersonating their dedicated service account.

Provide training for all engineering teams you work with to understand the company’s required practices. Allow the engineering teams to provision the infrastructure to best meet their needs.

Configure organization policies to enforce your company’s required practices. Ask the teams to provision their infrastructure by using the Google Cloud console.

Write Terraform modules for each component that are compliant with the company’s required practices, and ask teams to implement their infrastructure through these modules.

Create a Billing account, associate a payment method with it, and provide all project creators with permission to associate that billing account with their projects.

Grant all engineer’s permission to create their own billing accounts for each new project.

Apply for monthly invoiced billing, and have a single invoice tor the project paid by the finance team.

Create a billing account, associate it with a monthly purchase order (PO), and send the PO to Google Cloud.

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.

gcloud deployment-manager deployments create --config < deployment-config-path >

gcloud deployment-manager deployments update --config < deployment-config-path >

gcloud deployment-manager resources create --config < deployment-config-path >

gcloud deployment-manager resources update --config < deployment-config-path >

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.

Deploy a private autopilot cluster

Deploy a public autopilot cluster.

Deploy a standard public cluster and enable shielded nodes.

Deploy a standard private cluster and enable shielded nodes.

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.

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.

Modify the minimum number of Cloud Run instances.

Set a minimum concurrent requests environment variable for the application.

Modify the maximum number of Cloud Run instances.

Use traffic splitting.

Modify the cluster ' s node pool machine type and choose a machine type with more memory and CPU.

Configure a Horizontal Pod Autoscaler for each microservice.

Configure GKE cluster autoscaling.

Configure a Vertical Pod Autoscaler for each microservice.

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

Perform a rolling-action start-update with maxSurge set to 0 and maxUnavailable set to 1.

Perform a rolling-action start-update with maxSurge set to 1 and maxUnavailable set to 0.

Create a new managed instance group with an updated instance template. Add the group to the backend service for the load balancer. When all instances in the new managed instance group are healthy, delete the old managed instance group.

Create a new instance template with the new application version. Update the existing managed instance group with the new instance template. Delete the instances in the managed instance group to allow the managed instance group to recreate the instance using the new instance template.

Use your existing CI/CD pipeline Use the generated Docker images and deploy them to Cloud Run. Update the configurations and the required endpoints.

Use your existing continuous integration and delivery (CI/CD) pipeline. Use the generated Docker images and deploy them to Cloud Function. Use the same configuration as on-premises.

Use the existing codebase and deploy each service as a separate Cloud Function Update the configurations and the required endpoints.

Use your existing codebase and deploy each service as a separate Cloud Run Use the same configurations as on-premises.

Use Cloud Storage with Object Lifecycle Management to change the object storage class to Standard after six months.

Use Cloud Storage with Object Lifecycle Management to change the object storage class to Coldline after six months.

Store your documents on Filestore, and move the documents to Cloud Storage with object storage class set to Standard after six months.

Store your documents on Filestore, and move the documents to Cloud Storage with object storage class set to Coldline after six months.

Create a service account with just the permissions to access files in the bucket. Create a JSON key for the service account. Execute the command gsutil signurl -m 1h gs:///*.

Create a service account with just the permissions to access files in the bucket. Create a JSON key for the service account. Execute the command gsutil signurl -d 1h gs:///.

Create a service account with just the permissions to access files in the bucket. Create a JSON key for the service account. Execute the command gsutil signurl -p 60m gs:///.

Create a JSON key for the Default Compute Engine Service Account. Execute the command gsutil signurl -t 60m gs:///*

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.

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.

Use the command gcloud config set container/cluster dev.

Use the command gcloud container clusters update dev.

Create a file called gke.default in the ~/.gcloud aname.

Create a file called defaults.json in the ~/.gcloud folder that contains the cluster name.

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 andcompute 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.

Create as few service accounts as possible.

Delete any unused service accounts immediately.

Create single-purpose service accounts.

Manage service accounts as resources.

Use random names for the service accounts.

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.

Create a Kubernetes Service of type NodePort for your application, and a Kubernetes Ingress to expose this Service via a Cloud Load Balancer.

Create a Kubernetes Service of type ClusterIP for your application. Configure the public DNS name of your application using the IP of this Service.

Create a Kubernetes Service of type NodePort to expose the application on port 443 of each node of the Kubernetes cluster. Configure the public DNS name of your application with the IP of every node of the cluster to achieve load-balancing.

Create a HAProxy pod in the cluster to load-balance the traffic to all the pods of the application. Forward the public traffic to HAProxy with an iptable rule. Configure the DNS name of your application using the public IP of the node HAProxy is running on.

Use gcloud storage for the video files. Dataflow for the data warehouse data, and Storage Transfer Service for the PNG files.

Use Transfer Appliance for the videos. BigQuery Data Transfer Service for the data warehouse data, and Storage Transfer Service for the PNG files.

Use Storage Transfer Service for the video files, BigQuery Data Transfer Service for the data warehouse data, and Storage Transfer Service for the PNG files.

Use Cloud Data Fusion for the video files, Dataflow for the data warehouse data, and Storage Transfer Service for the PNG files.

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.

Store the application data on a zonal persistent disk. Create a snapshot schedule for the disk. If an outage occurs, create a new disk from the most recent snapshot and attach it to a new VM in another zone.

Store the application data on a zonal persistent disk. If an outage occurs, create an instance in another zone with this disk attached.

Store the application data on a regional persistent disk. Create a snapshot schedule for the disk. If an outage occurs, create a new disk from the most recent snapshot and attach it to a new VM in another zone.

Store the application data on a regional persistent disk If an outage occurs, create an instance in another zone with this disk attached.

Create a Service Account in your own project, and grant this Service Account access to BigGuery in your project

Create a Service Account in your own project, and ask the partner to grant this Service Account access to BigQuery in their project

Ask the partner to create a Service Account in their project, and have them give the Service Account access to BigQuery in their project

Ask the partner to create a Service Account in their project, and grant their Service Account access to the BigQuery dataset in your project

Use a proxy Network Load Balancer for the MIG and an A record in your DNS private zone with the load balancer ' s IP address.

Use a proxy Network Load Balancer for the MIG and a CNAME record in your DNS public zone with the load balancer ' s IP address.

Use an Application Load Balancer for the MIG and a CNAME record in your DNS private zone with the load balancer ' s IP address.

Use an Application Load Balancer for the MIG and an A record in your DNS public zone with the load balancer ' s IP address.

Assign appropriate access for Google services to the service account used by the Compute Engine VM.

Create a service account with appropriate access for Google services, and configure the application to use this account.

Store credentials for service accounts with appropriate access for Google services in a config file, and deploy this config file with your application.

Store credentials for your user account with appropriate access for Google services in a config file, and deploy this config file with your application.

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 ' sGoogle 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.

Assign the pods of the image rendering microservice a higher pod priority than the older microservices

Create a node pool with compute-optimized machine type nodes for the image rendering microservice Use the node pool with general-purposemachine type nodes for the other microservices

Use the node pool with general-purpose machine type nodes for lite mage rendering microservice Create a nodepool with compute-optimized machine type nodes for the other microservices

Configure the required amount of CPU and memory in the resource requests specification of the image rendering microservice deployment Keep the resource requests for the other microservices at the default

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.

Enable the Identity Aware Proxy API on the project.

Scan the bucker using the Data Loss Prevention API.

Allow only a single Service Account access to read the data.

Enable Data Access audit logs for the Cloud Storage API.

Go to Data Catalog and search for employee_ssn in the search box.

Write a shell script that uses the bq command line tool to loop through all the projects in your organization.

Write a script that loops through all the projects in your organization and runs a query on INFORMATION_SCHEMA.COLUMNS view to find the employee_ssn column.

Write a Cloud Dataflow job that loops through all the projects in your organization and runs a query on INFORMATION_SCHEMA.COLUMNS view to find employee_ssn column.

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.

Install a RDP client on your desktop. Verify that a firewall rule for port 3389 exists.

Install a RDP client in your desktop. Set a Windows username and password in the GCP Console. Use the credentials to log in to the instance.

Set a Windows password in the GCP Console. Verify that a firewall rule for port 22 exists. Click the RDP button in the GCP Console and supply the credentials to log in.

Set a Windows username and password in the GCP Console. Verify that a firewall rule for port 3389 exists. Click the RDP button in the GCP Console, and supply the credentials to log in.

Create a single custom VPC with 2 subnets. Create each subnet in a different region and with a different CIDR range.

Create a single custom VPC with 2 subnets. Create each subnet in the same region and with the same CIDR range.

Create 2 custom VPCs, each with a single subnet. Create each subnet is a different region and with a different CIDR range.

Create 2 custom VPCs, each with a single subnet. Create each subnet in the same region and with the same CIDR range.

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.

Deploy a Dataflow job from the batch template " Datastore lo Cloud Storage " Schedule the batch job on the desired interval

In the Cloud Console, go to Cloud Storage Upload the relevant images to the appropriate bucket

Create a script that uses the gsutil command line interface to synchronize the on-premises storage with Cloud Storage Schedule the script as a cron job

Create a Pub/Sub topic, and enable a Cloud Storage trigger for the Pub/Sub topic. Create an application that sends all medical images to the Pub/Sub lope

Set up Error Reporting to identify stack traces that indicate slowdowns in Dataflow jobs. Set up alerts based on these log entries.

Use the Personalized Service Health dashboard to identify issues with Dataflow jobs across regions.

Update the Dataflow job configurations to send messages to a Pub/Sub topic when there are delays. Configure a backup Dataflow job to process jobs that are delayed. Use Cloud Tasks to trigger an alert when messages are pushed to the Pub/Sub topic.

Set up Cloud Monitoring alerts on the data freshness metric for the Dataflow jobs to receive a notification when a certain threshold is reached.

Use the gcloud pubsub subscriptions seek email-updates command.

Use the gcloud pubsub topics describe new-orders command.

Use the gcloud pubsub subscriptions pull email-updates —auto-ack command.

Use the gcloud pubsub topics list-subscriptions new-orders —1ilter= " email-updates " command.

1. Create a consumer Gmail account.2.Write a script that monitors the CPU usage.3.When the CPU usage exceeds the threshold, have that script send an email using the Gmail account and smtp.gmail.com on port 25 as SMTP server.

1. Create a Stackdriver Workspace, and associate your Google Cloud Platform (GCP) project with it.2.Create an Alerting Policy in Stackdriver that uses the threshold as a trigger condition.3.Configure your email address in the notification channel.

1. Create a Stackdriver Workspace, and associate your GCP project with it.2.Write a script that monitors the CPU usage and sends it as a custom metric to Stackdriver.3.Create an uptime check for the instance in Stackdriver.

1. In Stackdriver Logging, create a logs-based metric to extract the CPU usage by using this regular expression: CPU Usage: ([0-9] {1,3}) %2.In Stackdriver Monitoring, create an Alerting Policy based on this metric.3.Configure your email address in the notification channel.

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.

Enable cluster autoscaling on the GKE cluster.

Configure a Vertical Pod Autoscaler on the Deployment.

Configure a Horizontal Pod Autoscaler on the Deployment.

Enable node auto-provisioning on the GKE cluster.

Use the Google Cloud console to provision and manage Google Cloud resources.

Write shell scripts using gcloud commands to provision and manage Google Cloud resources.

Create Terraform configurations for your Google Cloud resources, and store the state file in a Cloud Storage bucket.

Install Config Connector in a GKE cluster, and define your Google Cloud resources as custom resources in Kubernetes manifests.

1. Create an ingress firewall rule with the following settings:• Targets: all instances• Source filter: IP ranges (with the range set to 10.0.2.0/24)• Protocols: allow all2. Create an ingress firewall rule with the following settings:• Targets: all instances• Source filter: IP ranges (with the range set to 10.0.1.0/24)• Protocols: allow all

1. Create an ingress firewall rule with the following settings:• Targets: all instances with tier #2 service account• Source filter: all instances with tier #1 service account• Protocols: allow TCP:80802. Create an ingress firewall rule with the following settings:• Targets: all instances with tier #3 service account• Source filter: all instances with tier #2 service account• Protocols: allow TCP: 8080

1. Create an ingress firewall rule with the following settings:• Targets: all instances with tier #2 service account• Source filter: all instances with tier #1 service account• Protocols: allow all2. Create an ingress firewall rule with the following settings:• Targets: all instances with tier #3 service account• Source filter: all instances with tier #2 service account• Protocols: allow all

1. Create an egress firewall rule with the following settings:• Targets: all instances• Source filter: IP ranges (with the range set to 10.0.2.0/24)• Protocols: allow TCP: 80802. Create an egress firewall rule with the following settings:• Targets: all instances• Source filter: IP ranges (with the range set to 10.0.1.0/24)• Protocols: allow TCP: 8080

Extract your access token by using the gcloud auth print-access-token command, and store it with the application.

Grant the relevant IAM roles to the service account used as your agent identity.

Create a secret in Secret Manager to store your personal credentials, and configure the application ' s authentication code to use this secret.

Generate a JSON private key for the service account, and upload the key as Vertex AI 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.

Use your personal user credentials to authenticate the application, ensuring your account has the necessary permissions.

Create a new project, generate a service account key in the new project, and grant the service account the required IAM roles in the application project.

Override the organization policy in the project, and create a long-lived service account key in the GKE cluster.

Configure Workload Identity Federation to allow the application to impersonate a service account.

Create a single module for each resource type, and place all modules in the same directory.

Put the Terraform configuration resources for each application in its own root directory.

Create a single module for each application, and place all modules in the same directory.

Put resources of the same type in their own root directory.

Deployment Manager

Cloud Composer

Managed Instance Group

Unmanaged Instance Group

Verify that you are the project billing administrator. Select the associated billing account and create a budget and alert for the appropriate project.

Verify that you are the project billing administrator. Select the associated billing account and create a budget and a custom alert.

Verify that you are the project administrator. Select the associated billing account and create a budget for the appropriate project.

Verify that you are project administrator. Select the associated billing account and create a budget and a custom alert.

Create a custom role, and add all the required compute.disks.list and compute, images.list permissions as includedPermissions. Grant the custom role to the user at the project level.

Create a custom role based on the Compute Image User role Add the compute.disks, list to theincludedPermissions field Grant the custom role to the user at the project level

Grant the Compute Storage Admin role at the project level.

Create a custom role based on the Compute Storage Admin role. Exclude unnecessary permissions from the custom role. Grant the custom role to the user at the project level.

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.

Create an instance template. Set the disk type to be an SSD Persistent Disk. Launch the instance template as part of a stateful managed instance group.

Create an instance template. Set the disk type to be an SSD Persistent Disk. Launch the instance template as part of a stateless managed instance group.

Create an instance template. Set the disk type to be Hyperdisk Extreme. Launch the instance template as part of a stateful managed instance group.

Create an instance template. Set the disk type to be Hyperdisk Extreme. Launch the instance template as part of a stateless managed instance group.

Configure Billing Data Export to BigQuery and visualize the data in Data Studio.

Visit the Cost Table page to get a CSV export and visualize it using Data Studio.

Fill all resources in the Pricing Calculator to get an estimate of the monthly cost.

Use the Reports view in the Cloud Billing Console to view the desired cost information.

Configure your GKE cluster with one node, and set the node to have a static external IP address. Ensure that the GKE cluster autoscaler is off. Send the external IP address of the node to the vendor to be added to the allowlist.

Configure your GKE cluster with private nodes. Configure a Cloud NAT instance with static IP addresses. Provide these IP addresses to the vendor to be added to the allowlist.

Configure your GKE cluster with public nodes. Write a Cloud Function that pulls the public IP addresses of each node in the cluster. Trigger the function to run every day with Cloud Scheduler. Send the list to the vendor by email every day.

Configure your GKE cluster with private nodes. Configure a Cloud NAT instance with dynamic IP addresses. Provide these IP addresses to the vendor to be added to the allowlist.

Update your web application to use the protocol HTTP/2 instead of HTTP/1.1

Set the concurrency number to 1 for your Cloud Run service.

Set the maximum number of instances for your Cloud Run service to 100.

Set the minimum number of instances for your Cloud Run service to 3.

After the VM has been created, use your Google Account credentials to log in into the VM.

After the VM has been created, use gcloud compute reset-windows-password to retrieve the login credentials for the VM.

When creating the VM, add metadata to the instance using ‘windows-password’ as the key and a password as the value.

After the VM has been created, download the JSON private key for the default Compute Engine service account. Use the credentials in the JSON file to log in to the VM.

Create a retention policy on the storage bucket of 30 days, and lock the bucket by using a retention policy lock.

Enable object versioning on the storage bucket and add lifecycle rules to expire non-current versions after 30 days

Create an object lifecycle on the storage bucket to change the storage class to Archive Storage for objects with an age over 30 days.

Create a cron job in Cloud Scheduler to call a Cloud Functions instance every day to delete files older than 30 days.

Fill in local SSD. Fill in persistent disk storage and snapshot storage.

Fill in local SSD. Add estimated cost for cluster management.

Select Add GPUs. Fill in persistent disk storage and snapshot storage.

Select Add GPUs. Add estimated cost for cluster management.

Grant yourself the IAM role of Cloud Spanner Admin

Create a new VPC network with subnetworks in all desired regions

Configure your Cloud Spanner instance to be multi-regional

Enable the Cloud Spanner API

Enable Cloud CDN on the website frontend.

Enable ‘Share publicly’ on the PDF file objects.

Set Content-Type metadata to application/pdf on the PDF file objects.

Add a label to the storage bucket with a key of Content-Type and value of application/pdf.

Create an export to the sink that saves logs from Cloud Audit to BigQuery.

Create an export to the sink that saves logs from Cloud Audit to a Coldline Storage bucket.

Write a custom script that uses logging API to copy the logs from Stackdriver logs to BigQuery.

Export these logs to Cloud Pub/Sub and write a Cloud Dataflow pipeline to store logs to Cloud SQL.

Create a folder to contain all the dev projects Create an organization policy to limit resources in US locations.

Create an organization to contain all the dev projects. Create an Identity and Access Management (IAM) policy to limit the resources in US regions.

Create an Identity and Access Management < IAM) policy to restrict the resources locations in the US. Apply the policy to all dev projects.

Create an Identity and Access Management (IAM)policy to restrict the resources locations in all dev projects. Apply the policy to all dev roles.

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.

Deploy the web application as a Cloud Run service.

Deploy the web application on Google Kubernetes Engine In Standard mode.

Deploy the web application as a Cloud Run job.

Deploy the web application on Google Kubernetes Engine in Autopilot mode.

Create an instance template for the instances. Set the ‘Automatic Restart’ to on. Set the ‘On-host maintenance’ to Migrate VM instance. Add the instance template to an instance group.

Create an instance template for the instances. Set ‘Automatic Restart’ to off. Set ‘On-host maintenance’ to Terminate VM instances. Add the instance template to an instance group.

Create an instance group for the instances. Set the ‘Autohealing’ health check to healthy (HTTP).

Create an instance group for the instance. Verify that the ‘Advanced creation options’ setting for ‘do not retry machine creation’ is set to off.

Create a new Cloud Billing account, and associate the project with it to prevent new spending from affecting your project ' s budget.

Create a Pub/Sub topic, and connect it to the budget. Create a Cloud Run function that subscribes to the Pub/Sub topic and executes code to stop the VM.

Use the Cloud Billing dashboard to identify the forecasted spend of your project, and then update the budget and alert to match the forecasted spend.

Rely on the budget ' s configuration to automatically disable billable resources when the spend reaches 100%.

Add users to roles/bigquery user role only, instead of roles/bigquery dataOwner.

Add users to roles/bigquery dataEditor role only, instead of roles/bigquery dataOwner.

Create a custom role by removing delete permissions, and add users to that role only.

Create a custom role by removing delete permissions. Add users to the group, and then add the group to the custom role.

Create an alert in Cloud Monitoring to alert when the percentage of high priority CPU utilization reaches 45% If you exceed this threshold, add nodes lo your instance.

Create an alert in Cloud Monitoring to alert when the percentage to high priority CPU utilization reaches 45% Use database query statistics to identify queries that result in high CPU usage, and then rewrite those queries to optimize their resource usage

Create an alert in Cloud Monitoring to alert when the percentage of high priority CPU utilization reaches 65% If you exceed this threshold, add nodes to your instance

Create an alert in Cloud Monitoring to alert when the percentage of high priority CPU utilization reaches 65%. Use database query statistics to identity queries that result in high CPU usage, and then rewrite those queries to optimize their resource usage.

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 " .

Use Dataflow as a platform to run the fine-tuning jobs.

Use a Compute Engine managed instance group as a platform to deploy Jupyter Notebooks and run fine-tuning jobs.

Use Google Kubernetes Engine (GKE) and hardware accelerators as a platform to run the fine-tuning jobs.

Use Cloud Run and GPU as a platform to run the fine-tuning jobs.

Set up a policy that uses Nearline storage for 30 days and then moves to Archive storage for three years.

Set up a policy that uses Standard storage for 30 days and then moves to Archive storage for three years.

Set up a policy that uses Nearline storage for 30 days, then moves the Coldline for one year, and then moves to Archive storage for two years.

Set up a policy that uses Standard storage for 30 days, then moves to Coldline for one year, and then moves to Archive storage for two years.

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

Use kubectl app deploy < dockerfilename > .

Use gcloud app deploy < dockerfilename > .

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.

In Cloud Monitoring, create a custom metric that tracks the creation of Cloud Run instances, and display the metric on a dashboard.

Log each new database connection in the application. In Cloud Monitoring, create a custom metric for these logs, and display the metric on a dashboard.

In the Google Cloud console, navigate to the Cloud SQL instance, and review the instance logs.

In Cloud Trace, enable trace storage for your project, and use a filter to check for new database connections.

• Ensure that the Ops Agent Is Installed on the Compute Engine instance.• Create a custom metric in the Cloud Monitoring dashboard.• Provide the security team member with access to this dashboard.

• Ensure that the Ops Agent is installed on tie Compute Engine instance.• Provide the security team member roles/configure.inventoryViewer permission.

• Ensure that the OS Config agent Is Installed on the Compute Engine instance.• Provide the security team member roles/configure.vulnerabilityViewer permission.

• Ensure that the OS Config agent is installed on the Compute Engine instance• Create a log sink Co a BigQuery dataset.• Provide the security team member with access to this dataset.

Enable Object Versioning on the bucket, and create an Object Lifecycle Management rule that sets the daysSinceNoncurrentTime condition to 90 days, transitioning noncurrent versions to Archive storage.

Create an Object Lifecycle Management rule on the bucket that specifies an age condition of 90 days and uses the SetStorageClass action to transition the objects to Archive storage.

Create a nightly scheduled Cloud Run function that uses the Cloud Storage API to change the storage class of all objects older than 90 days to Archive storage.

Create an Object Lifecycle Management rule on the bucket that specifies the createdBefore condition set to 90 days ago and uses the Delete action to remove the objects.

kubectl delete deployment nginx

kubectl delete –deployment=nginx

kubectl delete pod nginx-84748895c4-k6bzl –no-restart 2

kubectl delete inginx

Grant the roles/bigquery.dataViewer role to the domain:terramearth.com principal on the dataset ' s IAM policy.

Grant the roles/bigquery.dataViewer role to the allUsers principal on the dataset ' s IAM policy.

Grant the roles/bigquery.dataViewer role to a new service account on the dataset ' s IAM policy.

Grant the roles/bigquery.dataViewer role to the allAuthenticatedUsers principal on the dataset ' s IAM policy.

Configure a Cloud Router in vpc-a and another Cloud Router in vpc-b.

Configure a Cloud Interconnect connection between vpc-a and vpc-b.

Create VPC Network Peering between vpc-a and vpc-b.

Create an OpenVPN connection between vpc-a and vpc-b.