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

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.

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.

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.

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.

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.

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

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

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

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

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.

Set the maximum number of instances to 1.

Decrease the maximum number of instances to 3.

Use a TCP health check instead of an HTTP health check.

Increase the initial delay of the HTTP health check to 200 seconds.

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

kubectl delete deployment nginx

kubectl delete –deployment=nginx

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

kubectl delete inginx

Use granular logging statements within a Deployment Manager template authored in Python.

Monitor activity of the Deployment Manager execution on the Stackdriver Logging page of the GCP Console.

Execute the Deployment Manager template against a separate project with the same configuration, and monitor for failures.

Execute the Deployment Manager template using the –-preview option in the same project, and observe the state of interdependent resources.

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.

Google Compute Engine

Google App Engine

Cloud Functions

Google Kubernetes Engine

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.

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

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

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

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

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

Create a 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.

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

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

machine type nodes for the other microservices

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

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

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.

Coldline Storage

Nearline Storage

Regional Storage

Multi-Regional Storage

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.

Arrange to switch to Flat-Rate pricing for this query, then move back to on-demand.

Use the command line to run a dry run query to estimate the number of bytes read. Then convert that bytes estimate to dollars using the Pricing Calculator.

Use the command line to run a dry run query to estimate the number of bytes returned. Then convert that bytes estimate to dollars using the Pricing Calculator.

Run a select count (*) to get an idea of how many records your query will look through. Then convert that number of rows to dollars using the Pricing Calculator.

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.

• 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.

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.

BigQuery

Cloud SQL

Cloud Spanner

Cloud Datastore

Use Binary Authorization and whitelist only the container images used by your customers’ Pods.

Use the Container Analysis API to detect vulnerabilities in the containers used by your customers’ Pods.

Create a GKE node pool with a sandbox type configured to gvisor. Add the parameter runtimeClassName: gvisor to the specification of your customers’ Pods.

Use the cos_containerd image for your GKE nodes. Add a nodeSelector with the value cloud.google.com/gke-os-distribution: cos_containerd to the specification of your customers’ Pods.

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.

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.

Using the GCP Console, filter the Activity log to view the information.

Using the GCP Console, filter the Stackdriver log to view the information.

View the bucket in the Storage section of the GCP Console.

Create a trace in Stackdriver to view the information.

Deployment Manager

Cloud Composer

Managed Instance Group

Unmanaged Instance Group

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

• Navigate to Cloud Mentioning in the Google Cloud console, and create a custom monitoring job for the

Bigtable 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 the

Biglable instance.

• Create a Cloud Functions instance to export logs from Cloud Logging to your SIEM.

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

Create a custom role based on the Compute Image User role Add the compute.disks, list to the

includedPermissions field Grant the custom role to the user at the project level

Grant the Compute Storage Admin role at the project level.

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

Enable Audit Logs for all APIs that are related to data storage.

Review the IAM permissions for any role that allows for data access.

Review the Identity-Aware Proxy settings for each resource.

Create a Data Loss Prevention job.

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.

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.

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.

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.

Enable the Identity Aware Proxy API on the project.

Scan the bucker using the Data Loss Prevention API.

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

Enable Data Access audit logs for the Cloud Storage API.

Create and deploy a Custom Resource Definition per microservice.

Create and deploy a Docker Compose File.

Create and deploy a Job per microservice.

Create and deploy a Deployment per microservice.

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.

Save file automatic first-of-the- month backup for three years Store the backup file in an Archive class Cloud Storage bucket

Convert the automatic first-of-the-month backup to an export file Write the export file to a Coldline class Cloud Storage bucket

Set up an export job for the first of the month Write the export file to an Archive class Cloud Storage bucket

Set up an on-demand backup tor the first of the month Write the backup to an Archive class Cloud Storage bucket

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.

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.

1. Update your instances’ metadata to add the following value: snapshot–schedule: 0 1 * * *

2. Update your instances’ metadata to add the following value: snapshot–retention: 30

1. In the Cloud Console, go to the Compute Engine Disks page and select your instance’s disk.

2. In the Snapshot Schedule section, select Create Schedule and configure the following parameters:

–Schedule frequency: Daily

–Start time: 1:00 AM – 2:00 AM

–Autodelete snapshots after 30 days

1. Create a Cloud Function that creates a snapshot of your instance’s disk.

2.Create a Cloud Function that deletes snapshots that are older than 30 days.

3.Use Cloud Scheduler to trigger both Cloud Functions daily at 1:00 AM.

1. Create a bash script in the instance that copies the content of the disk to Cloud Storage.

2.Create a bash script in the instance that deletes data older than 30 days in the backup Cloud Storage bucket.

3.Configure the instance’s crontab to execute these scripts daily at 1:00 AM.

Ask the auditor for their Google account, and give them the Viewer role on the project.

Ask the auditor for their Google account, and give them the Security Reviewer role on the project.

Create a temporary account for the auditor in Cloud Identity, and give that account the Viewer role on the project.

Create a temporary account for the auditor in Cloud Identity, and give that account the Security Reviewer role on the project.

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.

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

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

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

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

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

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.

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.

Select Multi-Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Coldline Storage.

Select Multi-Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Nearline Storage.

Select Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Nearline Storage.

Select Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Coldline Storage.

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.

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.

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.

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 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.

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.

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.

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 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

Review the Compute Engine activity logs Select and review the Admin Event logs

Review the Compute Engine activity logs Select and review the System Event logs

Install the Cloud Logging Agent In Cloud Logging review the Compute Engine syslog logs

Install the Cloud Logging Agent In Cloud Logging, review the Compute Engine operation logs

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.

.00.0.0/0

10.0.0.0/8

172.16.0.0/12

192.168.0.0/16

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

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

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

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

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.

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.

1. Create a Cloud Monitoring Dashboard

2. 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 projects

2. Collect metrics and publish them lo the Cloud Monitoring API

3. Add CPU and network Charts for each of the three projects.

1. Create a fourth Google Cloud project

2 Create a Cloud Workspace from the fourth project and add the other three projects

– 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.

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

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

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

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

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

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

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

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

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.

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.

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.

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.

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.