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

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.

Set the europe-west1-d zone as the default zone using the gcloud config subcommand.

In the Settings page for Compute Engine under Default location, set the zone to europe–west1-d.

In the CLI installation directory, create a file called default.conf containing zone=europe–west1–d.

Create a Metadata entry on the Compute Engine page with key compute/zone and value europe–west1–d.

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.

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.

1. Build an instruction guide to install Cassandra on GCP.2. Make the instruction guide accessible to your developers.

1. Advise your developers to go to Cloud Marketplace.2. Ask the developers to launch a Cassandra image for their development work.

1. Build a Cassandra Compute Engine instance and take a snapshot of it.2. Use the snapshot to create instances for your developers.

1. Build a Cassandra Compute Engine instance and take a snapshot of it.2.Upload the snapshot to Cloud Storage and make it accessible to your developers.3.Build instructions to create a Compute Engine instance from the snapshot so that developers can do it themselves.

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.

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 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.

Use Cloud Bigtable for data storage.

Use Cloud SQL for data storage.

Use Cloud Spanner for data storage.

Use Firestore for data storage.

– 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.

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

Create a Cloud Scheduler task to regularly scan your projects and delete mismatched users.

Create a Cloud Scheduler task to regularly scan your resources and delete mismatched users.

Set an organizational policy constraint to limit identities by domain to automatically remove mismatched users.

Set an organizational policy constraint to limit identities by domain, and then retroactively remove the existing mismatched users.

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.

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

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.

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.

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

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

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

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

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.

Configure an HTTP(S) load balancer.

Configure an internal TCP load balancer.

Configure an external SSL proxy load balancer.

Configure an external TCP proxy load balancer.

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.

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.

Fill in local SSD. Fill in persistent disk storage and snapshot storage.

Fill in local SSD. Add estimated cost for cluster management.

Select Add GPUs. Fill in persistent disk storage and snapshot storage.

Select Add GPUs. Add estimated cost for cluster management.

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

Deploy the container on Cloud Run for Anthos, and set the minimum number of instances to zero

Deploy the container on Cloud Run (fully managed), and set the minimum number of instances to zero.

Deploy the container on App Engine flexible environment with autoscaling. and set the value min_instances to zero in the app yaml

Deploy the container on App Engine flexible environment with manual scaling, and set the value instances to zero in the app yaml

• Create a custom role with Compute Engine, Cloud Functions, and Cloud SQL permissions in one project within the Google Cloud organization.• Copy the role across all projects created within the organization with the gcloud iam roles copy command.• Assign the role to developers in those projects.

• Add all developers to a Google group in Google Groups for Workspace.• Assign the predefined role of Compute Admin to the Google group at the Google Cloud organization level.

• Add all developers to a Google group in Cloud Identity.• Assign predefined roles for Compute Engine, Cloud Functions, and Cloud SQL permissions to the Google group for each project in the Google Cloud organization.

• Add all developers to a Google group in Cloud Identity.• Create a custom role with Compute Engine, Cloud Functions, and Cloud SQL permissions at the Google Cloud organization level.• Assign the custom role to the Google group.

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.

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

Open the Cloud Spanner console to review configurations.

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

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

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

Deployment Manager

Cloud Composer

Managed Instance Group

Unmanaged Instance Group

Expose the application by using an internal passthrough Network Load Balancer.

Expose the application by using an external passthrough Network Load Balancer.

Expose the application by using a global external proxy Network Load Balancer.

Expose the application by using a regional external proxy Network Load Balancer.

Store the application data on a zonal persistent disk. Create a snapshot schedule for the disk. If an outage occurs, create a new disk from the most recent snapshot and attach it to a new VM in another zone.

Store the application data on a zonal persistent disk. If an outage occurs, create an instance in another zone with this disk attached.

Store the application data on a regional persistent disk. Create a snapshot schedule for the disk. If an outage occurs, create a new disk from the most recent snapshot and attach it to a new VM in another zone.

Store the application data on a regional persistent disk If an outage occurs, create an instance in another zone with this disk attached.

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.

Reserve the IP 10.0.3.21 as a static internal IP address using gcloud and assign it to the licensing server.

Reserve the IP 10.0.3.21 as a static public IP address using gcloud and assign it to the licensing server.

Use the IP 10.0.3.21 as a custom ephemeral IP address and assign it to the licensing server.

Start the licensing server with an automatic ephemeral IP address, and then promote it to a static internal IP address.

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 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.

BigQuery

Cloud SQL

Cloud Spanner

Cloud Datastore

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.

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.

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

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

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

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

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.

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.

Use gcloud storage for the video files. Dataflow for the data warehouse data, and Storage Transfer Service for the PNG files.

Use Transfer Appliance for the videos. BigQuery Data Transfer Service for the data warehouse data, and Storage Transfer Service for the PNG files.

Use Storage Transfer Service for the video files, BigQuery Data Transfer Service for the data warehouse data, and Storage Transfer Service for the PNG files.

Use Cloud Data Fusion for the video files, Dataflow for the data warehouse data, and Storage Transfer Service for the PNG files.

Configure your GKE cluster with one node, and set the node to have a static external IP address. Ensure that the GKE cluster autoscaler is off. Send the external IP address of the node to the vendor to be added to the allowlist.

Configure your GKE cluster with private nodes. Configure a Cloud NAT instance with static IP addresses. Provide these IP addresses to the vendor to be added to the allowlist.

Configure your GKE cluster with public nodes. Write a Cloud Function that pulls the public IP addresses of each node in the cluster. Trigger the function to run every day with Cloud Scheduler. Send the list to the vendor by email every day.

Configure your GKE cluster with private nodes. Configure a Cloud NAT instance with dynamic IP addresses. Provide these IP addresses to the vendor to be added to the allowlist.

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.

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.

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.

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

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

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

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

Deploy 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.

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.

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.

Use a proxy Network Load Balancer for the MIG and an A record in your DNS private zone with the load balancer's IP address.

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

Use an Application Load Balancer for the MIG and a CNAME record in your DNS private zone with the load balancer's IP address.

Use an Application Load Balancer for the MIG and an A record in your DNS public zone with the load balancer's IP address.

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.

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 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.

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

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

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

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

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

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

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

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

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

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.

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

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.

Create a health check on port 443 and use that when creating the Managed Instance Group.

Select Multi-Zone instead of Single-Zone when creating the Managed Instance Group.

In the Instance Template, add the label ‘health-check’.

In the Instance Template, add a startup script that sends a heartbeat to the metadata server.

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

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

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

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

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 Deployment Manager templates to describe the proposed changes and store them in a Cloud Storage bucket.

Use Deployment Manager templates to describe the proposed changes and store them in Cloud Source Repositories.

Apply the change in a development environment, run gcloud compute instances list, and then save the output in a shared Storage bucket.

Apply the change in a development environment, run gcloud compute instances list, and then save the output in Cloud Source Repositories.

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.

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.

The pending Pod's resource requests are too large to fit on a single node of the cluster.

Too many Pods are already running in the cluster, and there are not enough resources left to schedule the pending Pod.

The node pool is configured with a service account that does not have permission to pull the container image used by the pending Pod.

The pending Pod was originally scheduled on a node that has been preempted between the creation of the Deployment and your verification of the Pods’ status. It is currently being rescheduled on a new node.

Create a new subnet in the same region as the subnet being used.

Add an alias IP range to the subnet used by the GKE clusters.

Create a new VPC, and set up VPC peering with the existing VPC.

Expand the CIDR range of the relevant subnet for the cluster.

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

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

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

Use GCP Marketplace to launch the Jenkins solution.

Create an instance template. Set the disk type to be an SSD Persistent Disk. Launch the instance template as part of a stateful managed instance group.

Create an instance template. Set the disk type to be an SSD Persistent Disk. Launch the instance template as part of a stateless managed instance group.

Create an instance template. Set the disk type to be Hyperdisk Extreme. Launch the instance template as part of a stateful managed instance group.

Create an instance template. Set the disk type to be Hyperdisk Extreme. Launch the instance template as part of a stateless managed instance group.

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".

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.

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.

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.

Install Kafka on VM instances to acknowledge incoming transactions. Use Cloud Run to process transactions.

Install Kafka on VM Instances to acknowledge incoming transactions. Use VM Instances to process transactions.

Use Pub/Sub to acknowledge incoming transactions. Use VM instances to process transactions.

Use Pub/Sub to acknowledge incoming transactions. Use Cloud Run to process transactions.

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

Use gcloud to create the new project, and then deploy your application to the new project.

Use gcloud to create the new project and to copy the deployed application to the new project.

Create a Deployment Manager configuration file that copies the current App Engine deployment into a new project.

Deploy your application again using gcloud and specify the project parameter with the new project name to create the new project.

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 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

Select Google Kubernetes Engine. Use a single-node cluster with a small instance type.

Select Google Kubernetes Engine. Use a three-node cluster with micro instance types.

Select Compute Engine. Use preemptible VM instances of the appropriate standard machine type.

Select Compute Engine. Use VM instance types that support micro bursting.

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

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

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

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

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

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

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

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

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

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.

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.

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

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

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

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

• 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.

Use the command gcloud config set container/cluster dev.

Use the command gcloud container clusters update dev.

Create a file called gke.default in the ~/.gcloud aname.

Create a file called defaults.json in the ~/.gcloud folder that contains the cluster name.

Migrate your data to AlloyDB.

Migrate your data to Spanner.

Migrate your data to Firebase.

Migrate your data to Bigtable.

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.

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.

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.