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

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.

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.

Use labels to group resources that share common IAM policies

Use folders to group resources that share common IAM policies

Set up a proper billing account structure to group IAM policies

Set up a proper project naming structure to group IAM policies

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.

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

Migrate the web application to App Engine and the backend API to Cloud Run Use Cloud Tasks to run your background job on Compute Engine

Migrate the web application to App Engine and the backend API to Cloud Run. Use Cloud Tasks to run your background job on Cloud Run.

Run the web application on a Cloud Storage bucket and the backend API on Cloud Run Use Cloud Tasks to run your background job on Cloud Run.

Run the web application on a Cloud Storage bucket and the backend API on Cloud Run. Use Cloud Tasks to run your background job on Compute Engine

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

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.

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.

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.

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.

– 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.

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.

Create an instance template that contains valid syntax which will be used by the instance group. Delete any persistent disks with the same name as instance names.

Create an instance template that contains valid syntax that will be used by the instance group. Verify that the instance name and persistent disk name values are not the same in the template.

Verify that the instance template being used by the instance group contains valid syntax. Delete any persistent disks with the same name as instance names. Set the disks.autoDelete property to true in the instance template.

Delete the current instance template and replace it with a new instance template. Verify that the instance name and persistent disk name values are not the same in the template. Set the disks.autoDelete property to true in the instance template.

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.

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.

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.

Add your SREs to roles/iam.roleAdmin role.

Add your SREs to roles/accessapproval approver role.

Add your SREs to a group and then add this group to roles/iam roleAdmin role.

Add your SREs to a group and then add this group to roles/accessapproval approver role.

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

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.

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.

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.

Your zonal capacity is limited, causing all preemptible VM's to be shutdown torecover capacity. Try deploying your group to another zone.

You have hit your instance quota for the region.

Your managed instance group's VM's are toggled to only last 1 minute inpreemptible settings.

Your managed instance group's health check is repeatedly failing, either to amisconfigured health check or misconfigured firewall rules not allowing the healthcheck to access the instance

Sync Identities with Cloud Directory Sync, and then enable SAML for single sign-on

Sync Identities in the Google Admin console, and then enable Oauth for single sign-on

Sync identities with 3rd party LDAP sync, and then copy passwords to allow simplified login with (he same credentials

Sync identities with Cloud Directory Sync, and then copy passwords to allow simplified login with the same credentials.

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.

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 the application lo Cloud. Run. Use gradual rollouts for traffic spelling.

Deploy the application lo Google Kubemetes Engine. Use Anthos Service Mesh for traffic splitting.

Deploy the application to Cloud functions. Saucily the version number in the functions name.

Deploy the application to App Engine. For each new version, create a new service.

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.

Select Cloud SQL (MySQL). Verify that the enable binary logging option is selected.

Select Cloud SQL (MySQL). Select the create failover replicas option.

Select Cloud Spanner. Set up your instance with 2 nodes.

Select Cloud Spanner. Set up your instance as multi-regional.

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 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.

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 the Google Cloud 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 1AM & admin page for all resources, and validate the results.

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

Use the gcloud CLI services enable cloudresourcemanager.googleapis.com command to enable all resources.

Use the gcloud services enable compute.googleapis.com command to enable Compute Engine and the gcloud services enable storage-api.googleapis.com command 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.

Upload the code to Cloud Functions. Use Cloud Scheduler to start the application.

Create a container for the set of binaries. Use Cloud Scheduler to start a Cloud Run job for the container.

Create a container for the set of binaries Deploy the container to Google Kubernetes Engine (GKE) and use the Kubernetes scheduler to start the application.

Lift and shift to a VM on Compute Engine. Use an instance schedule to start and stop the instance.

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.

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.

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.

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.

Grant each individual external consultant the role of BigQuery Editor

Grant each individual external consultant the role of BigQuery Viewer

Create a Google Group that contains the consultants and grant the group the role of BigQuery Editor

Create a Google Group that contains the consultants, and grant the group the role of BigQuery Viewer

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.

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.

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.

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.

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.

.00.0.0/0

10.0.0.0/8

172.16.0.0/12

192.168.0.0/16

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.

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.

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.

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.

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:///***

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 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.

Create a new project and create an App Engine instance in europe-west3

Use the gcloud app region set command and supply the name of the new region.

From the console, under the App Engine page, click edit, and change the region drop-down.

Contact Google Cloud Support and request the change.

Create a file in Cloud Storage per device and append new data to that file.

Create a file in Cloud Filestore per device and append new data to that file.

Ingest the data into Datastore. Store data in an entity group based on the device.

Ingest the data into Cloud Bigtable. Create a row key based on the event timestamp.

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.

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.

Coldline Storage

Nearline Storage

Regional Storage

Multi-Regional Storage

1. Give the BigQuery Data Editor role on the platform-logs dataset to the service accounts used by your instances.2. Update your instances’ metadata to add the following value: logs-destination: bq://platform-logs.

1. In Stackdriver Logging, create a logs export with a Cloud Pub/Sub topic called logs as a sink.2. Create a Cloud Function that is triggered by messages in the logs topic.3. Configure that Cloud Function to drop logs that are not from Compute Engine and to insert Compute Engine logs in the platform-logs dataset.

1. In Stackdriver Logging, create a filter to view only Compute Engine logs.2. Click Create Export.3. Choose BigQuery as Sink Service, and the platform-logs dataset as Sink Destination.

1. Create a Cloud Function that has the BigQuery User role on the platform-logs dataset.2. Configure this Cloud Function to create a BigQuery Job that executes this query:INSERT INTO dataset.platform-logs (timestamp, log)SELECT timestamp, log FROM compute.logsWHERE timestamp > DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY)3. Use Cloud Scheduler to trigger this Cloud Function once a day.

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.

Run gcloud auth login, enter your login credentials in the dialog window, and paste the received login token to gcloud CLI.

Create a Google Cloud service account, and download the service account key. Place the key file in a folder on your machine where gcloud CLI can find it.

Download your Cloud Identity user account key. Place the key file in a folder on your machine where gcloud CLI can find it.

Run gcloud config set compute/zone $my_zone to set the default zone for gcloud CLI.

Run gcloud config set project $my_project to set the default project for gcloud CLI.

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.

Use SSL proxy load balancing for the MIG and an A record in your DNS private zone with the load balancer's IP address.

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

Use HTTP(S) load balancing for the MIG and a CNAME record in your DNS private zone with the load balancer's IP address.

Use HTTP(S) load balancing for the MIG and an A record in your DNS public zone with the load balancer's IP address.

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

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

Generate a new SSH key pair. Give the private key to each member of your team. Configure the public key in the metadata of each instance.

Ask each member of the team to generate a new SSH key pair and to send you their public key. Use a configuration management tool to deploy those keys on each instance.

Ask each member of the team to generate a new SSH key pair and to add the public key to their Google account. Grant the “compute.osAdminLogin” role to the Google group corresponding to this team.

Generate a new SSH key pair. Give the private key to each member of your team. Configure the public key as a project-wide public SSH key in your Cloud Platform project and allow project-wide public SSH keys on each instance.

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.

Run gcloud app restore.

On the App Engine page of the GCP Console, select the application that needs to be reverted and click Revert.

On the App Engine Versions page of the GCP Console, route 100% of the traffic to the previous version.

Deploy the original version as a separate application. Then go to App Engine settings and split traffic between applications so that the original version serves 100% of the requests.

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.

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.

Create the instance with the default Compute Engine service account Grant the service account permissions on Cloud Storage.

Create the instance with the default Compute Engine service account Add metadata to the objects on Cloud Storage that matches the metadata on the new instance.

Create a new service account and assig n this service account to the new instance Grant the service account permissions on Cloud Storage.

Create a new service account and assign this service account to the new instance Add metadata to the objects on Cloud Storage that matches the metadata on the new instance.

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.

Create a cluster with a single node-pool by using standard VMs. Label the fault-tolerant Deployments as spot-true.

Create a cluster with a single node-pool by using Spot VMs. Label the critical Deployments as spot-false.

Create a cluster with both a Spot W node pool and a rode pool by using standard VMs Deploy the critical.

deployments on the Spot VM node pool and the fault; tolerant deployments on the node pool by using standard VMs.

Create a cluster with both a Spot VM node pool and by using standard VMs. Deploy the critical deployments on the mode pool by using standard VMs and the fault-tolerant deployments on the Spot VM node pool.

1. Use nslookup to get the IP address for storage.googleapis.com.2. Negotiate with the security team to be able to give a public IP address to the servers.3. Only allow egress traffic from those servers to the IP addresses for storage.googleapis.com.

1. Using Cloud VPN, create a VPN tunnel to a Virtual Private Cloud (VPC) in Google Cloud Platform (GCP).2. In this VPC, create a Compute Engine instance and install the Squid proxy server on this instance.3. Configure your servers to use that instance as a proxy to access Cloud Storage.

1. Use Migrate for Compute Engine (formerly known as Velostrata) to migrate those servers to Compute Engine.2. Create an internal load balancer (ILB) that uses storage.googleapis.com as backend.3. Configure your new instances to use this ILB as proxy.

1. Using Cloud VPN or Interconnect, create a tunnel to a VPC in GCP.2. Use Cloud Router to create a custom route advertisement for 199.36.153.4/30. Announce that network to your on-premises network through the VPN tunnel.3. In your on-premises network, configure your DNS server to resolve *.googleapis.com as a CNAME to restricted.googleapis.com.

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.

Disable the flag “Delete boot disk when instance is deleted.”

Enable delete protection on the instance.

Disable Automatic restart on the instance.

Enable Preemptibility on the instance.

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.

1. In GKE, create a Service of type LoadBalancer that uses the application's Pods as backend.2. Set the service's externalTrafficPolicy to Cluster.3. Configure the Compute Engine instance to use the address of the load balancer that has been created.

1. In GKE, create a Service of type NodePort that uses the application's Pods as backend.2. Create a Compute Engine instance called proxy with 2 network interfaces, one in each VPC.3. Use iptables on this instance to forward traffic from gce-network to the GKE nodes.4. Configure the Compute Engine instance to use the address of proxy in gce-network as endpoint.

1. In GKE, create a Service of type LoadBalancer that uses the application's Pods as backend.2. Add an annotation to this service: cloud.google.com/load-balancer-type: Internal3. Peer the two VPCs together.4. Configure the Compute Engine instance to use the address of the load balancer that has been created.

1. In GKE, create a Service of type LoadBalancer that uses the application's Pods as backend.2. Add a Cloud Armor Security Policy to the load balancer that whitelists the internal IPs of the MIG's instances.3. Configure the Compute Engine instance to use the address of the load balancer that has been created.