Associate-Cloud-Engineer Questions and Answers

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.

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.

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

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.

Deploy a Cloud SQL database with the SSL mode set to encrypted only, configure SSL/TLS client certificates, and configure a database user and password.

Deploy a Cloud SOL database and configure IAM database authentication. Access the database through the Cloud SQL Auth Proxy.

Deploy a Cloud SQL database with the SSL mode set to encrypted only, configure SSL/TLS client certificates, and configure IAM database authentication.

Deploy a Cloud SQL database and configure a database user and password. Access the database through the Cloud SQL Auth Proxy.

Grant the Project Editor role to the Marketing learn for acme data digest

Create a Project Lien on acme-data digest and then grant the Project Editor role to the Marketing team

Create another protect with the ID acme-marketing-data-digest for the Marketing team and deploy the resources there

Create a new protect named Meeting Data Digest and use the ID acme-data-digest Grant the Project Editor role to the Marketing team.

Set autoscaling to On, set the minimum number of instances to 1, and then set the maximum number of instances to 1.

Set autoscaling to Off, set the minimum number of instances to 1, and then set the maximum number of instances to 1.

Set autoscaling to On, set the minimum number of instances to 1, and then set the maximum number of instances to 2.

Set autoscaling to Off, set the minimum number of instances to 1, and then set the maximum number of instances to 2.

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.

Use a Cloud Scheduler cron job to trigger a Cloud Function that queries Cloud Logging and sends the logs to the SaaS tool.

Create a Cloud Logging sink and configure Pub/Sub as the destination. Configure the SaaS tool to subscribe to the Pub/Sub topic to retrieve the logs.

Create a Cloud Logging sink and configure Cloud Storage as the destination. Configure the SaaS tool to read the Cloud Storage bucket to retrieve the logs.

Create a Cloud Logging sink and configure BigQuery as the destination. Configure the SaaS tool to query BigQuery to retrieve the logs.

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.

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.

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.

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.

Add a bucket lifecycle rule that archives data with newer versions after 30 days to Coldline Storage.

Add a bucket lifecycle rule that archives data with newer versions after 30 days to Nearline Storage.

Add a bucket lifecycle rule that archives data from regional storage after 30 days to Coldline Storage.

Add a bucket lifecycle rule that archives data from regional storage after 30 days to Nearline Storage.

Provision a Standard zonal Google Kubernetes Engine (GKE) cluster.

Provision a fleet of Compute Engine instances and install Kubernetes.

Provision a Google Kubernetes Engine (GKE) Autopilot cluster.

Provision a Standard regional Google Kubernetes Engine (GKE) cluster.

Deploy the application on GKE Autopilot.

Deploy the application on GKE Standard.

Deploy the application on Cloud Functions.

Deploy the application on Cloud Run.

Use the GCP Console to transfer the file instead of gsutil.

Enable parallel composite uploads using gsutil on the file transfer.

Decrease the TCP window size on the machine initiating the transfer.

Change the storage class of the bucket from Nearline to Multi-Regional.

Grant "project owner" for web-applications appropriate roles to crm-databases.

Grant "project owner" role to crm-databases and the web-applications project.

Grant "project owner" role to crm-databases and roles/bigquery.dataViewer role to web-applications.

Grant roles/bigquery.dataViewer role to crm-databases and appropriate roles to web-applications.

Containerize the batch processing jobs and deploy them on Compute Engine.

Use custom machine types on Compute Engine.

Use the M1 machine series on Compute Engine.

Use Spot VMs on Compute Engine.

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.

Store the database password inside the Docker image of the container, not in the YAML file.

Store the database password inside a Secret object. Modify the YAML file to populate the DB_PASSWORD environment variable from the Secret.

Store the database password inside a ConfigMap object. Modify the YAML file to populate the DB_PASSWORD environment variable from the ConfigMap.

Store the database password in a file inside a Kubernetes persistent volume, and use a persistent volume claim to mount the volume to the container.

Deploy the application on a managed instance group and configure autoscaling.

Deploy the application on a Kubernetes Engine cluster and configure node pool autoscaling.

Deploy the application on Cloud Functions and configure the maximum number instances.

Deploy the application on Cloud Run and configure autoscaling.

Use the BigQuery interface to review the nightly Job and look for any errors

Review the Error Reporting page in the Cloud Console to find any errors.

In Cloud Logging create a filter for your Data Studio report

Use the open source CLI tool. Snapshot Debugger, to find out why the data was not refreshed correctly.

Deploy your application to a second Cloud Run service, and ask your customers to use the second Cloud Run service.

Ask your customers to retry access to your service with exponential backoff to mitigate any potential problems after the new revision is deployed.

Gradually roll out the new revision and split customer traffic between the revisions to allow rollback in case a problem occurs.

Send all customer traffic to the new revision, and roll back to a previous revision if you witness any problems in production.

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.

Invite the user to transfer their existing account

Invite the user to use an email alias to resolve the conflict

Tell the user that they must delete their existing account

Tell the user to remove all personal email from the existing account

Create a signed URL with a four-hour expiration and share the URL with the company.

Set object access to ‘public’ and use object lifecycle management to remove the object after four hours.

Configure the storage bucket as a static website and furnish the object’s URL to the company. Delete the object from the storage bucket after four hours.

Create a new Cloud Storage bucket specifically for the external company to access. Copy the object to that bucket. Delete the bucket after four hours have passed.

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.

Deploy an ingress resource on the GKE cluster to expose the API to the internet. Use Cloud Armor to filter for IP addresses that can connect to the API. On the Cloud Run service, configure the application to fetch its public IP address and update the Cloud Armor policy on startup to allow this IP address to call the API on ports 80 and 443.

Create an egress firewall rule on the VPC to allow connections to 0.0.0.0/0 on ports 80 and 443.

Create an ingress firewall rule on the VPC to allow connections from 0.0.0.0/0 on ports 80 and 443.

Deploy an internal Application Load Balancer to expose the API on GKE to the VPC. Configure Cloud DNS with the IP address of the internal Application Load Balancer. Deploy a Serverless VPC Access connector to allow the Cloud Run service to call the API through the FQDN on Cloud DNS.

Develop SQL queries by using Gemini for Google Cloud.

Enable Log Analytics for the log bucket and create a linked dataset in BigQuery.

Create a schema for the storage bucket and run SQL queries for the data in the bucket.

Export logs to a storage bucket and create an external view in BigQuery.

Open the Cloud Spanner console to review configurations.

Open the IAM & admin console to review IAM policies for Cloud Spanner roles.

Go to the Stackdriver Monitoring console and review information for Cloud Spanner.

Go to the Stackdriver Logging console, review admin activity logs, and filter them for Cloud Spanner IAM roles.

Deploy your solution on multiple standalone Compute Engine instances, and increase the number of existing instances wnen CPU utilization on Cloud Monitoring reaches a certain threshold.

Deploy your solution on multiple standalone Compute Engine instances, and replace existing instances with high-CPUinstances when CPU utilization on Cloud Monitoring reaches a certain threshold.

Deploy your solution to an instance group, and increase the number of available instances whenever you see high CPU utilization in Cloud Monitoring.

Deploy your solution to an instance group, and set the autoscaling based on CPU utilization.

Deploy a new version of your application in Google Kubernetes Engine instead of App Engine and then use GCP Console to split traffic.

Deploy a new version of your application in a Compute Engine instance instead of App Engine and then use GCP Console to split traffic.

Deploy a new version as a separate app in App Engine. Then configure App Engine using GCP Console to split traffic between the two apps.

Deploy a new version of your application in App Engine. Then go to App Engine settings in GCP Console and split traffic between the current version and newly deployed versions accordingly.

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.

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.

Use gcloud config configurations describe to review the output.

Use gcloud config configurations activate and gcloud config list to review the output.

Use kubectl config get-contexts to review the output.

Use kubectl config use-context and kubectl config view to review the output.

gcloud deployment-manager deployments create --config

gcloud deployment-manager deployments update --config

gcloud deployment-manager resources create --config

gcloud deployment-manager resources update --config

Configure Firestore. Configure all applications to use Firestore instead of the NFS server.

Deploy a Filestore instance. Replace all NFS mounts with a Filestore mount.

Create a Cloud Storage bucket. Configure all applications to use Cloud Storage client libraries instead of the NFS server.

Create a Compute Engine instance and configure an NFS server on the instance. Point all NFS mounts to the Compute Engine instance.

Use gcloud container clusters upgrade. Deploy the new services.

Create a new Node Pool and specify machine type n2–highmem–16. Deploy the new pods.

Create a new cluster with n2–highmem–16 nodes. Redeploy the pods and delete the old cluster.

Create a new cluster with both n1–standard–2 and n2–highmem–16 nodes. Redeploy the pods and delete the old cluster.

Configure an HTTP(S) load balancer.

Configure an internal TCP load balancer.

Configure an external SSL proxy load balancer.

Configure an external TCP proxy load balancer.

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.

Use the gcloud CLI services enablecloudresourcemanager.googleapis.comcommand to enable all resources.

Use the gcloud services enablecompute.googleapis.comcommand to enable Compute Engineand thegcloud services enablestorage-api.googleapis.comcommand to enable the Cloud Storage APIs.

Open the Google Cloud console and enable all Google Cloud APIs from the API dashboard.

Open the Google Cloud console and run gcloud init --project in a Cloud Shell.

1. Verify that you ace assigned the Billing Administrator IAM role tor your organization's Google Cloud Project for the Marketing department2. Link the new project to a Marketing Billing Account

1. Verify that you are assigned the Billing Administrator IAM role for your organization's Google Cloud account2. Create a new Google Cloud Project for the Marketing department3. Set the default key-value project labels to department marketing for all services in this project

1. Verify that you are assigned the Organization Administrator IAM role for your organization's Google Cloud account2. Create a new Google Cloud Project for the Marketing department 3. Link the new project to a Marketing Billing Account.

1. Verity that you are assigned the Organization Administrator IAM role for your organization's Google Cloud account2. Create a new Google Cloud Project for the Marketing department3. Set the default key value project labels to department marketing for all services in this protect

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

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.

Coldline Storage

Nearline Storage

Regional Storage

Multi-Regional Storage

Create one CNAME record to point mydomain.com to the load balancer, and create two A records to point WWW and HOME lo mydomain.com respectively.

Create one CNAME record to point mydomain.com to the load balancer, and create two AAAA records to point WWW and HOME to mydomain.com respectively.

Create one A record to point mydomain.com to the load balancer, and create two CNAME records to point WWW and HOME to mydomain.com respectively.

Create one A record to point mydomain.com lo the load balancer, and create two NS records to point WWW and HOME to mydomain.com respectively.

In the console, validate which SSH keys have been stored as project-wide keys.

Navigate to Identity-Aware Proxy and check the permissions for these resources.

Enable Audit Logs on the IAM & admin page for all resources, and validate the results.

Use the command gcloud projects get–iam–policy to view the current role assignments.

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.

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.

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.

1. Create a single VPC with a subnet for the DMZ and a subnet for the LAN. 2. Set up firewall rules to open up relevant traffic between the DMZ and the LAN subnets, and another firewall rule to allow public ingress traffic for the DMZ.

1. Create a single VPC with a subnet for the DMZ and a subnet for the LAN. 2. Set up firewall rules to open up relevant traffic between the DMZ and the LAN subnets, and another firewall rule to allow public egress traffic for the DMZ.

1. Create a VPC with a subnet for the DMZ and another VPC with a subnet for the LAN. 2. Set up firewall rules to open up relevant traffic between the DMZ and the LAN subnets, and another firewall rule to allow public ingress traffic for the DMZ.

1. Create a VPC with a subnet for the DMZ and another VPC with a subnet for the LAN. 2. Set up firewall rules to open up relevant traffic between the DMZ and the LAN subnets, and another firewall rule to allow public egress traffic for the DMZ.

Run a Kubernetes job to scan the bucket regularly for incoming files, and call the Speech-to-Text API for each unprocessed file.

Create an App Engine standard environment triggered by Cloud Storage bucket events to submit the file URI to the Google Speech-to-Text API.

Run a Python script by using a Linux cron job in Compute Engine to scan the bucket regularly for incoming files, and call the Speech-to-Text API for each unprocessed file.

Create a Cloud Function triggered by Cloud Storage bucket events to submit the file URI to the Google Speech-to-Text API.

Download and deploy the Jenkins Java WAR to App Engine Standard.

Create a new Compute Engine instance and install Jenkins through the command line interface.

Create a Kubernetes cluster on Compute Engine and create a deployment with the Jenkins Docker image.

Use GCP Marketplace to launch the Jenkins solution.

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

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

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

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

Create a single budget for all projects and configure budget alerts on this budget.

Create a separate billing account per sandbox project and enable BigQuery billing exports. Create a Data Studio dashboard to plot the spending per billing account.

Create a budget per project and configure budget alerts on all of these budgets.

Create a single billing account for all sandbox projects and enable BigQuery billing exports. Create a Data Studio dashboard to plot the spending per project.

Ask your ML team to add the “accelerator: gpu” annotation to their pod specification.

Recreate all the nodes of the GKE cluster to enable GPUs on all of them.

Create your own Kubernetes cluster on top of Compute Engine with nodes that have GPUs. Dedicate this cluster to your ML team.

Add a new, GPU-enabled, node pool to the GKE cluster. Ask your ML team to add the cloud.google.com/gke -accelerator: nvidia-tesla-p100 nodeSelector to their pod specification.

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.

Move your website to Google Kubemetes Engine (GKE). and move your background job to Cloud Functions

Move both your website and background job to Compute Engine

CMove both your website and background job to Cloud Run.

Move your website to Google Kubemetes Engine (GKE), and move your background job to Compute Engine

Create a cron job that runs on a scheduled basis to review stackdriver monitoring metrics, and then resize the Spanner instance accordingly.

Create a Stackdriver alerting policy to send an alert to oncall SRE emails when Cloud Spanner CPU exceeds the threshold. SREs would scale resources up or down accordingly.

Create a Stackdriver alerting policy to send an alert to Google Cloud Support email when Cloud Spanner CPU exceeds your threshold. Google support would scale resources up or down accordingly.

Create a Stackdriver alerting policy to send an alert to webhook when Cloud Spanner CPU is over or under your threshold. Create a Cloud Function that listens to HTTP and resizes Spanner resources accordingly.

Enable Cloud IAP for the Compute Engine instances, and add the operations partner as a Cloud IAP Tunnel User.

Tag all the instances with the same network tag. Create a firewall rule in the VPC to grant TCP access on port 22 for traffic from the operations partner to instances with the network tag.

Set up Cloud VPN between your Google Cloud VPC and the internal network of the operations partner.

Ask the operations partner to generate SSH key pairs, and add the public keys to the VM instances.

Review details of the myapp-service Service object and check for error messages.

Review details of the myapp-deployment Deployment object and check for error messages.

Review details of myapp-deployment-58ddbbb995-lp86m Pod and check for warning messages.

View logs of the container in myapp-deployment-58ddbbb995-lp86m pod and check for warning messages.

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.

Use the projects. move method to move the project to your organization. Update the billing account of the project to that of your organization.

Ensure that you have an Organization Administrator Identity and Access Management (IAM) role assigned to you in both organizations. Navigate to the Resource Manager in the startup's Google Cloud organization, and drag the project to your company's organization.

Create a Private Catalog tor the Google Cloud Marketplace, and upload the resources of the startup’s production project to the Catalog. Share the Catalog with your organization, and deploy the resources in your company’s project.

Create an infrastructure-as-code template tor all resources in the project by using Terraform. and deploy that template to a new project in your organization. Delete the protect from the startup's Google Cloud organization.

Create a bash script that contains all requirement steps as gcloud commands

Develop templates for the environment using Cloud Deployment Manager

Use curl in a terminal to send a REST request to the relevant Google API for each individual resource.

Use the Cloud Console interface to provision and manage all related resources

Assign the appropriate permissions, and then use Cloud Monitoring to review metrics

Use the export logs API to provide the Admin Activity Audit Logs in the format they want

Turn on Data Access Logs for the buckets they want to audit, and Then build a query in the log viewer that filters on Cloud Storage

Assign the appropriate permissions, and then create a Data Studio report on Admin Activity Audit Logs

Create a Cloud Memorystore for Redis instance with 32-GB capacity.

Run it on Compute Engine, and choose a custom instance type with 6 vCPUs and 32 GB of memory.

Package it in a container image, and run it on Kubernetes Engine, using n1-standard-32 instances as nodes.

Run it on Compute Engine, choose the instance type n1-standard-1, and add an SSD persistent disk of 32 GB.

BigQuery

Cloud SQL

Cloud Spanner

Cloud Datastore

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

Change the default region property setting in the existing GCP project to asia-northeast1.

Change the region property setting in the existing App Engine application from us-central to asia-northeast1.

Create a second App Engine application in the existing GCP project and specify asia-northeast1 as the region to serve your application.

Create a new GCP project and create an App Engine application inside this new project. Specify asia-northeast1 as the region to serve your application.

Grant the basic role roles/viewer and the predefined role roles/compute.admin to the DevOps group.

Create an IAM policy and grant all compute. instanceAdmln." permissions to the policy Attach the policy to the DevOps group.

Create a custom role at the folder level and grant all compute. instanceAdmln. * permissions to the role Grant the custom role to the DevOps group.

Grant the basic role roles/editor to the DevOps group.

Run your database as a StatefulSet. Configure cluster autoscaling to handle changes in the demands of your workloads.

Run your database as a single Pod. Run the resize command when you notice changes in the demands of your workloads.

Run your database as a Deployment. Configure cluster autoscaling to handle changes in the demands of your workloads.

Run your database as a DaemonSet. Run the resize command when you notice changes in the demands of your workloads.

Set metadata to enable-oslogin=true for the instance. Grant the dev1 group the compute.osLogin role. Direct them to use the Cloud Shell to ssh to that instance.

Set metadata to enable-oslogin=true for the instance. Set the service account to no service account for that instance. Direct them to use the Cloud Shell to ssh to that instance.

Enable block project wide keys for the instance. Generate an SSH key for each user in the dev1 group. Distribute the keys to dev1 users and direct them to use their third-party tools to connect.

Enable block project wide keys for the instance. Generate an SSH key and associate the key with that instance. Distribute the key to dev1 users and direct them to use their third-party tools to connect.

Open the Google Cloud console, and run a query to determine which resources this service account can access.

Open the Google Cloud console, and run a query of the audit logs to find permission denied errors for this service account.

Open the Google Cloud console, and check the organization policies.

Open the Google Cloud console, and check the Identity and Access Management (IAM) roles assigned to the service account at the project or inherited from the folder or organization levels.

Configure an SSL Proxy load balancer in front of the application servers.

Configure an Internal UDP load balancer in front of the application servers.

Configure an External HTTP(s) load balancer in front of the application servers.

Configure an External Network load balancer in front of the application servers.

Use Google Cloud Directory Sync (GCDS) to synchronize users into Cloud Identity.

Use the cloud Identity APIs and write a script to synchronize users to Cloud Identity.

Export users from Active Directory as a CSV and import them to Cloud Identity via the Admin Console.

Ask each employee to create a Google account using self signup. Require that each employee use their company email address and password.

Use Shared VPC to connect all projects, and link Stackdriver to one of the projects.

For each project, create a Stackdriver account. In each project, create a service account for that project and grant it the role of Stackdriver Account Editor in all other projects.

Configure a single Stackdriver account, and link all projects to the same account.

Configure a single Stackdriver account for one of the projects. In Stackdriver, create a Group and add the other project names as criteria for that Group.

Modify the existing subnet range to 172.16.20.0/24.

Create a new Secondary IP Range in the VPC and configure the VMs to use that range.

Create a new VPC network for the VMs. Enable VPC Peering between the VMs’ VPC network and the Dataproc cluster VPC network.

Create a new VPC network for the VMs with a subnet of 172.32.0.0/16. Enable VPC network Peering between the Dataproc VPC network and the VMs VPC network. Configure a custom Route exchange.

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.

Meet with the cloud enablement team to discuss load balancer options.

Redesign the application to use a distributed user session service that does not rely on WebSockets and HTTP sessions.

Review the encryption requirements for WebSocket connections with the security team.

Convert the WebSocket code to use HTTP streaming.

Use a Shielded VM.

Use a Preemptible VM.

Use a sole-tenant node.

Enable deletion protection on the instance.

Run gcloud configurations list followed by gcloud configurations activate .

Run gcloud config list followed by gcloud config activate.

Run gcloud config configurations list followed by gcloud config configurations activate.

Re-authenticate with the gcloud auth login command and select the correct configurations on login.

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.

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.

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.

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.

Project Editor

Storage Admin

Storage Object Admin

Storage Object Creator

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

Contact cloud-billing@google.com with your bank account details and request a corporate billing account for your company.

Create a ticket with Google Support and wait for their call to share your credit card details over the phone.

In the Google Platform Console, go to the Resource Manage and move all projects to the root Organization.

In the Google Cloud Platform Console, create a new billing account and set up a payment method.