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

Enable the BigQuery API and ensure that the BigQuery User IAM role is selected. Change the BigQuery dataset to select a data location.

Create a Cloud Billing account. Enable the BigQuery Data Transfer Service API to export pricing data.

Enable Cloud Billing data export to BigQuery when you create a Cloud Billing account.

Enable Cloud Billing on the project and link a Cloud Billing account. Then view the billing data table in the BigQuery dataset.

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.

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

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.

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.

Build the solution by using YAML manifests, and provision the resources.

Build the solution by using Terraform, and provision the resources.

Build the solution by using Python and the cloud SDKs from all providers to provision the resources.

Build the solution by using Config Connector, and provision the resources.

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".

Enable the Cloud Pub/Sub API in the API Library on the GCP Console.

Rely on the automatic enablement of the Cloud Pub/Sub API when the Service Account accesses it.

Use Deployment Manager to deploy your application. Rely on the automatic enablement of all APIs used by the application being deployed.

Grant the App Engine Default service account the role of Cloud Pub/Sub Admin. Have your application enable the API on the first connection to Cloud Pub/Sub.

kubectl get deployments –output=pods

gcloud get pods –selector=”app=prod”

kubectl get pods -I “app=prod”

gcloud list gke-deployments -filter={pod }

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.

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

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

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

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

Create 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.

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.

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

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

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

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

Deploy the 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.

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

Add the group for the finance team to roles/billing user role.

Add the group for the finance team to roles/billing admin role.

Add the group for the finance team to roles/billing viewer role.

Add the group for the finance team to roles/billing project/Manager role.

In the Log Viewer, filter the logs on severity 'Error' and the name of the Service Account.

Create a sink to BigQuery to export all the logs. Create a Data Studio dashboard on the exported logs.

Create a custom log-based metric for the specific error to be used in an Alerting Policy.

Grant Project Owner access to the Service Account.

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

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

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

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

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.

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.

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.

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 IAM & admin page for all resources, and validate the results.

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

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

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

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

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

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

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

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

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

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.

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.

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 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.

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

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

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

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

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.

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.

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.

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:///*

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.

Create Java packages that utilize the Google Cloud Client Libraries for Java to configure Google Cloud products. Store and share the packages in a source code repository.

Create bash scripts that utilize the Google Cloud CLI to configure Google Cloud products. Store and share the bash scripts in a source code repository.

Create Terraform modules that utilize the Google Cloud Terraform Provider to configure Google Cloud products. Store and share the modules in a source code repository.

Use the Google Cloud APIs by using curl to configure Google Cloud products. Store and share the curl commands in a source code repository.

1. Verify that you are assigned the Project Owners IAM role for this project.2. Locate the project in the GCP console, click Shut down and then enter the project ID.

1. Verify that you are assigned the Project Owners IAM role for this project.2. Switch to the project in the GCP console, locate the resources and delete them.

1. Verify that you are assigned the Organizational Administrator IAM role for this project.2. Locate the project in the GCP console, enter the project ID and then click Shut down.

1. Verify that you are assigned the Organizational Administrators IAM role for this project.2. Switch to the project in the GCP console, locate the resources and delete them.

Create a 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.

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.

Manual Scaling with 3 instances.

Basic Scaling with min_instances set to 3.

Basic Scaling with max_instances set to 3.

Automatic Scaling with min_idle_instances set to 3.

Use the gcloud pubsub subscriptions seek email-updates command.

Use the gcloud pubsub topics describe new-orders command.

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

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

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

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

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

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

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.

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

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

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

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

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

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.

Create as few service accounts as possible.

Delete any unused service accounts immediately.

Create single-purpose service accounts.

Manage service accounts as resources.

Use random names for the service accounts.

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.

Run gcloud projects list to get the project ID, and then run gcloud services list --project .

Run gcloud init to set the current project to my-project, and then run gcloud services list --available.

Run gcloud info to view the account value, and then run gcloud services list --account .

Run gcloud projects describe to verify the project value, and then run gcloud services list --available.

Migrate the workload to a Compute Engine Preemptible VM.

Migrate the workload to a Google Kubernetes Engine cluster with Preemptible nodes.

Migrate the workload to a Compute Engine VM. Start and stop the instance as needed.

Create an Instance Template with Preemptible VMs On. Create a Managed Instance Group from the template and adjust Target CPU Utilization. Migrate the workload.

1. Create a Cloud Monitoring Dashboard2. Collect metrics and publish them into the Pub/Sub topics 3. Add CPU and network Charts (or each of (he three projects

1. Create a Cloud Monitoring Dashboard.2. Select the CPU and Network metrics from the three projects.3. Add CPU and network Charts lot each of the three protects.

1 Create a Service Account and apply roles/viewer on the three projects2. Collect metrics and publish them lo the Cloud Monitoring API3. Add CPU and network Charts for each of the three projects.

1. Create a fourth Google Cloud project2 Create a Cloud Workspace from the fourth project and add the other three projects

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.

Split the users from business units to multiple projects.

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

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

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

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

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.

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

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

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

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

Deploy the application on GKE Autopilot.

Deploy the application on GKE Standard.

Deploy the application on Cloud Functions.

Deploy the application on Cloud Run.

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

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

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

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

When creating the VM via the web console, specify the service account under the ‘Identity and API Access’ section.

Download a JSON Private Key for the service account. On the Project Metadata, add that JSON as the value for the key compute-engine-service-account.

Download a JSON Private Key for the service account. On the Custom Metadata of the VM, add that JSON as the value for the key compute-engine-service-account.

Download a JSON Private Key for the service account. After creating the VM, ssh into the VM and save the JSON under ~/.gcloud/compute-engine-service-account.json.

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

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

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

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

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.

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.

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.

Create the instance without a public IP address.

Create the instance with Private Google Access enabled.

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

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

Use kubect1 to delete the topic resource.

Use gcloud CLI to delete the topic.

Use kubect1 to create the label deleted-by-cnrm and to change its value to true for the topic resource.

Use gcloud CLI to update the topic label managed-by-cnrm to false.

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

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

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

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

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.

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.

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.

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.

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.

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.

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.

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.

Give “project owner” for web-applications appropriate roles to crm-databases- proj

Give “project owner” role to crm-databases-proj and the web-applications project.

Give “project owner” role to crm-databases-proj and bigquery.dataViewer role to web-applications.

Give bigquery.dataViewer role to crm-databases-proj and appropriate roles to web-applications.

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.

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

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.

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.listpermission. Perform the export of logs to Cloud Storage.

Assign the auditor’s IAM user to a custom role that has logging.privateLogEntries.listpermission. Direct the auditor to also review the logs for changes to Cloud IAM policy.

Use a Shielded VM.

Use a Preemptible VM.

Use a sole-tenant node.

Enable deletion protection on the instance.

Multi-Regional Storage

Regional Storage

Nearline Storage

Coldline Storage

Option A

Option B

Option C

Option D

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

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

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

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

Navigate to Cloud Logging and view the application logs.

Connect to the instance’s serial console and read the application logs.

Configure a Health Check on the instance and set a Low Healthy Threshold value.

Install and configure the Cloud Logging Agent and view the logs from Cloud Logging.

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

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

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

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

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.

Verify that you are Project Billing Manager for the GCP project. Update the existing project to link it to the existing billing account.

Verify that you are Project Billing Manager for the GCP project. Create a new billing account and link the new billing account to the existing project.

Verify that you are Billing Administrator for the billing account. Create a new project and link the new project to the existing billing account.

Verify that you are Billing Administrator for the billing account. Update the existing project to link it to the existing billing account.

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.

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

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

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

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

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.

Confirm that network firewall rules are not blocking traffic for User A.

Review recent configuration changes that may have caused unintended modifications to permissions.

Verify that User A has the Identity and Access Management (IAM) Project Owner role assigned.

Review the error message that User A received.

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.

Configure the gcloud CLI with Application Default Credentials using your user account. Issue a relevant BigGuery request through the gcloud CLI to test the access.

Grant the service account the BlgQuery Administrator 1AM role to ensure the service account has all required access.

Generate a service account key, and configure the gcloud CLI to use this key. Issue a relevant BlgQuery request through the gcloud CLI to test the access.

Configure the gcloud CLI to use service account impersonation. Issue a relevant BigQuery request through the gcloud CLI to test the access.

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.

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

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.