Google Associate-Cloud-Engineer Google Cloud Certified - Associate Cloud Engineer Exam Practice Test

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.

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.

Option A

Option B

Option C

Option D

Create a Compute Engine snapshot of your base VM. Create your images from that snapshot.

Create a Compute Engine snapshot of your base VM. Create your instances from that snapshot.

Create a custom Compute Engine image from a snapshot. Create your images from that image.

Create a custom Compute Engine image from a snapshot. Create your instances from that image.

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.

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.

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

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.

Export your bill to a Cloud Storage bucket, and then import into Cloud Bigtable for analysis.

Export your bill to a Cloud Storage bucket, and then import into Google Sheets for analysis.

Export your transactions to a local file, and perform analysis with a desktop tool.

Export your bill to a BigQuery dataset, and then write time window-based SQL queries for analysis.

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.

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.

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.

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.

Rely on live migration to move the workload to a machine with more memory.

Use gcloud to add metadata to the VM. Set the key to required-memory-size and the value to 8 GB.

Stop the VM, change the machine type to n1-standard-8, and start the VM.

Stop the VM, increase the memory to 8 GB, and start the VM.

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.

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 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.

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

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

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

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

gcloud deployment-manager deployments create my-gcp-ace-cluster --config cluster.yaml

gcloud deployment-manager deployments create my-gcp-ace-cluster --type container.v1.cluster --config cluster.yaml

gcloud deployment-manager deployments apply my-gcp-ace-cluster --type container.v1.cluster --config cluster.yaml

gcloud deployment-manager deployments apply my-gcp-ace-cluster --config cluster.yaml

Search errors in Cloud Audit Logs to analyze the issue.

Configure Cloud Trace to analyze the issue.

View errors in Cloud Monitoring to analyze the issue.

Use the information schema views to analyze the underlying issue.

Use BigQuery Bl Engine to analyze the issue.

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.

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.

Deploy the container on Cloud Run.

Deploy the container on Cloud Run on GKE.

Deploy the container on App Engine Flexible.

Deploy the container on Google Kubernetes Engine, with cluster autoscaling and horizontal pod autoscaling enabled.

Deploy me application on App Engine For each update, create a new version of the same service Configure traffic splitting to send a small percentage of traffic to the new version

Deploy the application on App Engine For each update, create a new service Configure traffic splitting to send a small percentage of traffic to the new service.

Deploy the application on Kubernetes Engine For a new release, update the deployment to use the new version

Deploy the application on Kubernetes Engine For a now release, create a new deployment for the new version Update the service e to use the now deployment.

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.

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 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 Cloud Function to create an instance template.

Create a snapshot schedule for the disk using the desired interval.

Create a cron job to create a new disk from the disk using gcloud.

Create a Cloud Task to create an image and export it to Cloud Storage.

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.

Use Cloud SQL database with cross-region replication to store game statistics in the EU, US, and APAC regions.

Use Cloud Spanner to store user data mapped to the game statistics.

Use BigQuery to store game statistics with a Redis on Memorystore instance in the front to provide global consistency.

Store game statistics in a Bigtable database partitioned by username.

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

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

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

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

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.

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.

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

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

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

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

Deploy the application on Cloud Functions.

Deploy the application on Cloud Run.

Deploy the application on GKE Standard.

Deploy the application on GKE Autopilot.

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.

Stream data to Pub/Sub, and use Dataflow to send data to Cloud Storage

Stream data to Pub/Sub. and use Storage Transfer Service to send data to BigQuery.

Stream data to Dataflow, and use Storage Transfer Service to send data to BigQuery.

Stream data to Dataflow, and use Dataprep by Trifacta to send data to Bigtable.

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

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.

Reserve a new static external IP address and assign the new IP address to the VM.

Promote the existing IP address of the VM to become a static external IP address.

Reserve a new static external IPv6 address and assign the new IP address to the VM.

Promote the existing IP address of the VM to become a static internal IP address.

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

Add the network tag allow-udp-636 to the VM instance running the LDAP server.

Create a route called allow-udp-636 and set the next hop to be the VM instance running the LDAP server.

Add a network tag of your choice to the instance. Create a firewall rule to allow ingress on UDP port 636 for that network tag.

Add a network tag of your choice to the instance running the LDAP server. Create a firewall rule to allow egress on UDP port 636 for that network tag.

Grant all members of the DevOps team the role of Project Editor on the organization level.

Grant all members of the DevOps team the role of Project Editor on the production project.

Create a custom role that combines the required permissions. Grant the DevOps team the custom role on the production project.

Create a custom role that combines the required permissions. Grant the DevOps team the custom role on the organization level.

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.

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.

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.

Cloud Pub/Sub, Cloud Dataflow, Cloud Datastore, BigQuery

Firebase Messages, Cloud Pub/Sub, Cloud Spanner, BigQuery

Cloud Pub/Sub, Cloud Storage, BigQuery, Cloud Bigtable

Cloud Pub/Sub, Cloud Dataflow, Cloud Bigtable, BigQuery

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-CPU

instances 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.

Enable node auto-provisioning on the GKE cluster.

Create a VerticalPodAutscaler for those workloads.

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

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

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.

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.

Enable retention policies on the bucket, and use Cloud Scheduler to invoke a Cloud Function to move or delete your documents based on their metadata.

Enable retention policies on the bucket, use lifecycle rules to change the storage classes of the objects, set the number of versions, and delete old files.

Enable object versioning on the bucket, and use Cloud Scheduler to invoke a Cloud Functions instance to move or delete your documents based on their metadata.

Enable object versioning on the bucket, use lifecycle conditions to change the storage class of the objects, set the number of versions, and delete old files.

Configure regional storage for the region closest to the users Configure a Nearline storage class

Configure regional storage for the region closest to the users Configure a Standard storage class

Configure dual-regional storage for the dual region closest to the users Configure a Nearline storage class

Configure dual-regional storage for the dual region closest to the users Configure a Standard storage class

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.

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 a Shielded VM.

Use a Preemptible VM.

Use a sole-tenant node.

Enable deletion protection on the instance.

Set up a budget alert on the project with an amount of 100 dollars, a threshold of 100%, and notification type of “email.”

Set up a budget alert on the billing account with an amount of 100 dollars, a threshold of 100%, and notification type of “email.”

Export the billing data to BigQuery. Create a Cloud Function that uses BigQuery to sum the egress network costs of the exported billing data for the Apache web server for the current month and sends an email if it is over 100 dollars. Schedule the Cloud Function using Cloud Scheduler to run hourly.

Use the Stackdriver Logging Agent to export the Apache web server logs to Stackdriver Logging. Create a Cloud Function that uses BigQuery to parse the HTTP response log data in Stackdriver for the current month and sends an email if the size of all HTTP responses, multiplied by current GCP egress prices, totals over 100 dollars. Schedule the Cloud Function using Cloud Scheduler to run hourly.

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.

Save the incoming votes to Firestore. Use Cloud Scheduler to trigger a Cloud Functions instance to periodically process the votes.

Use a dedicated instance to process the incoming votes. Send the votes directly to this instance.

Save the incoming votes to a JSON file on Cloud Storage. Process the votes in a batch at the end of the day.

Save the incoming votes to Pub/Sub. Use the Pub/Sub topic to trigger a Cloud Functions instance to process the votes.

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.

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.

* Create service accounts sa-app and sa-db.

• Associate service account: sa-app with the application servers and the service account sa-db with the database servers.

• Create an ingress firewall rule to allow network traffic from source service account sa-app to target service account sa-db.

• Create network tags app-server and db-server.

• Add the app-server lag lo the application servers and the db-server lag to the database servers.

• Create an egress firewall rule to allow network traffic from source network tag app-server to target network tag db-server.

* Create a service account sa-app and a network tag db-server.

* Associate the service account sa-app with the application servers and the network tag db-server with

the database servers.

• Create an ingress firewall rule to allow network traffic from source VPC IP addresses and target the subnet-a IP addresses.

• Create a network lag app-server and service account sa-db.

• Add the tag to the application servers and associate the service account with the database servers.

• Create an egress firewall rule to allow network traffic from source network tag app-server to target service account sa-db.

1. Create an IAM entry for each data scientist's user account.2. Assign the BigQuery jobUser role to the group.

1. Create an IAM entry for each data scientist's user account.2. Assign the BigQuery dataViewer user role to the group.

1. Create a dedicated Google group in Cloud Identity.2. Add each data scientist's user account to the group.3. Assign the BigQuery jobUser role to the group.

1. Create a dedicated Google group in Cloud Identity.2. Add each data scientist's user account to the group.3. Assign the BigQuery dataViewer user role to the group.

Add the users to roles/browser role.

Add the users to roles/iam.roleViewer role.

Add the users to a group, and add this group to roles/browser role.

Add the users to a group, and add this group to roles/iam.roleViewer role.

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

Use the Google Cloud Pricing Calculator to determine the cost of every Google Cloud resource you expect to use. Use similar size instances for the web server, and use your current on-premises machines as a comparison for Cloud SQL.

Implement a similar architecture on Google Cloud, and run a reasonable load test on a smaller scale. Check the billing information, and calculate the estimated costs based on the real load your system usually handles.

Use the Google Cloud Pricing Calculator and select the Cloud Operations template to define your web application with as much detail as possible.

Create a Google spreadsheet with multiple Google Cloud resource combinations. On a separate sheet, import the current Google Cloud prices and use these prices for the calculations within formulas.

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.

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.

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.

1. Create a Cloud Function that uses a Cloud Pub/Sub trigger on that topic.2. Call your application on Cloud Run from the Cloud Function for every message.

1. Grant the Pub/Sub Subscriber role to the service account used by Cloud Run.2. Create a Cloud Pub/Sub subscription for that topic.3. Make your application pull messages from that subscription.

1. Create a service account.2. Give the Cloud Run Invoker role to that service account for your Cloud Run application.3. Create a Cloud Pub/Sub subscription that uses that service account and uses your Cloud Run application as the push endpoint.

1. Deploy your application on Cloud Run on GKE with the connectivity set to Internal.2. Create a Cloud Pub/Sub subscription for that topic.3. In the same Google Kubernetes Engine cluster as your application, deploy a container that takes the messages and sends them to your application.

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.

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

• 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.

An internal HTTP(S) load balancer together with Identity-Aware Proxy to allow only HTTPS traffic.

An external HTTP(S) load balancer to distribute the load and a URL map to target the requests for the static content to the Cloud Storage backend. Install the HTTPS certificates on the instance.

An external HTTP(S) load balancer with a managed SSL certificate to distribute the load and a URL map to target the requests for the static content to the Cloud Storage backend.

An external network load balancer pointing to the backend instances to distribute the load evenly. The web servers will forward the request to the Cloud Storage as needed.

Create two configurations using gcloud config configurations create [NAME]. Run gcloud config configurations activate [NAME] to switch between accounts when running the commands to start the Compute Engine instances.

Create two configurations using gcloud config configurations create [NAME]. Run gcloud configurations list to start the Compute Engine instances.

Activate two configurations using gcloud configurations activate [NAME]. Run gcloud config list to start the Compute Engine instances.

Activate two configurations using gcloud configurations activate [NAME]. Run gcloud configurations list to start the Compute Engine instances.

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:///***

Project Editor

Storage Admin

Storage Object Admin

Storage Object Creator

Use permissions in your role that use the ‘supported’ support level for role permissions. Set the role stage to ALPHA while testing the role permissions.

Use permissions in your role that use the ‘supported’ support level for role permissions. Set the role stage to BETA while testing the role permissions.

Use permissions in your role that use the ‘testing’ support level for role permissions. Set the role stage to ALPHA while testing the role permissions.

Use permissions in your role that use the ‘testing’ support level for role permissions. Set the role stage to BETA while testing the role permissions.

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

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

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

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

Use App Engine and configure Cloud Scheduler to trigger the application using Pub/Sub.

Use Cloud Functions and configure the bucket as a trigger resource.

Use Google Kubernetes Engine and configure a CronJob to trigger the application using Pub/Sub.

Use Dataflow as a batch job, and configure the bucket as a data source.

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 a Deployment Manager script to automate creating storage buckets in an appropriate region

Use a local SSD to improve performance of the VM for the targeted workload

Use the gsutii command to create a storage bucket in the same region as the VM

Use a Persistent Disk SSD in the same zone as the VM to improve performance of the VM

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.

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

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

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

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

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