Associate-Cloud-Engineer Questions and Answers

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.

Deployment Manager

Cloud Composer

Managed Instance Group

Unmanaged Instance Group

• 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.

Project Editor

Storage Admin

Storage Object Admin

Storage Object Creator

Configure an SSL Proxy load balancer in front of the application servers.

Configure an Internal UDP load balancer in front of the application servers.

Configure an External HTTP(s) load balancer in front of the application servers.

Configure an External Network load balancer in front of the application servers.

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

Create a new project, enable the Compute Engine and Cloud SQL APIs in that project, and replicate the setup you have created in the development environment.

Create a new production subnet in the existing VPC and a new production Cloud SQL instance in your existing project, and deploy your application using those resources.

Create a new project, modify your existing VPC to be a Shared VPC, share that VPC with your new project, and replicate the setup you have in the development environment in that new project, in the Shared VPC.

Ask the security team to grant you the Project Editor role in an existing production project used by another division of your company. Once they grant you that role, replicate the setup you have in the development environment in that project.

– 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 custom role with view-only project permissions. Add the user's account to the custom role.

Create a custom role with view-only service permissions. Add the user's account to the custom role.

Select the built-in IAM project Viewer role. Add the user's account to this role.

Select the built-in IAM service Viewer role. Add the user's account to this role.

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.

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

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

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

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

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.

Assign the auditor the IAM role roles/logging.privateLogViewer. Perform the export of logs to Cloud Storage.

Assign the auditor the IAM role roles/logging.privateLogViewer. Direct the auditor to also review the logs for changes to Cloud IAM policy.

Assign the auditor’s IAM user to a custom role that has logging.privateLogEntries.list

permission. Perform the export of logs to Cloud Storage.

Assign the auditor’s IAM user to a custom role that has logging.privateLogEntries.list

permission. Direct the auditor to also review the logs for changes to Cloud IAM policy.

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.

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.

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.

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.

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.

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.

• Add a step for human approval to the CI/CD pipeline before the execution of the infrastructure

provisioning.

• Use the human approvals IAM account for the provisioning.

• Attach a single service account to the compute instances.

• Add minimal rights to the service account.

• Allow the service account to impersonate a Cloud Identity user with elevated permissions to create, update, or delete resources.

• Attach a single service account to the compute instances.

• Add all required Identity and Access Management (IAM) permissions to this service account to create, update, or delete resources

• Create multiple service accounts, one for each pipeline with the appropriate minimal Identity and

Access Management (IAM) permissions.

• Use a secret manager service to store the key files of the service accounts.

• Allow the CI/CD pipeline to request the appropriate secrets during the execution of the pipeline.

1. Go to the Logs ingestion window in Stackdriver Logging, and disable the log source for the GKE container resource.

1. Go to the Logs ingestion window in Stackdriver Logging, and disable the log source for the GKE Cluster Operations resource.

1. Go to the GKE console, and delete existing clusters.2. Recreate a new cluster.3. Clear the option to enable legacy Stackdriver Logging.

1. Go to the GKE console, and delete existing clusters.2. Recreate a new cluster.3. Clear the option to enable legacy Stackdriver Monitoring.

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

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.

HTTPS Load Balancer

Network Load Balancer

SSL Proxy Load Balancer

Internal TCP/UDP Load Balancer. Add a firewall rule allowing ingress traffic from 0.0.0.0/0 on the target instances.

Create 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 an HTTP load balancer with a backend configuration that references an existing instance group. Set the health check to healthy (HTTP).

Create an HTTP load balancer with a backend configuration that references an existing instance group. Define a balancing mode and set the maximum RPS to 10.

Create a managed instance group. Set the Autohealing health check to healthy (HTTP).

Create a managed instance group. Verify that the autoscaling setting is on.

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

Select the MIG from the Compute Engine console and, in the menu, select Replace VMs.

Use the gcloud compute instance-groups managed recreate-instances command to recreate theVM.

Use the gcloud compute instances update command with a REFRESH action for the VM.

Update and apply the instance template of the MIG.

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

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

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

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

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.

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.

Use the GCP Console to transfer the file instead of gsutil.

Enable parallel composite uploads using gsutil on the file transfer.

Decrease the TCP window size on the machine initiating the transfer.

Change the storage class of the bucket from Nearline to Multi-Regional.

Create a Kubernetes Service of type NodePort for your application, and a Kubernetes Ingress to expose this Service via a Cloud Load Balancer.

Create a Kubernetes Service of type ClusterIP for your application. Configure the public DNS name of your application using the IP of this Service.

Create a Kubernetes Service of type NodePort to expose the application on port 443 of each node of the Kubernetes cluster. Configure the public DNS name of your application with the IP of every node of the cluster to achieve load-balancing.

Create a HAProxy pod in the cluster to load-balance the traffic to all the pods of the application. Forward the public traffic to HAProxy with an iptable rule. Configure the DNS name of your application using the public IP of the node HAProxy is running on.

Cloud SQL

Cloud Spanner

Cloud Firestore

Cloud Datastore

Create a GKE Autopilot cluster. Enroll the cluster in the rapid release channel.

Create a GKE Autopilot cluster. Enroll the cluster in the stable release channel.

Create a zonal GKE standard cluster. Enroll the cluster in the stable release channel.

Create a regional GKE standard cluster. Enroll the cluster in the rapid release channel.

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.

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.

.00.0.0/0

10.0.0.0/8

172.16.0.0/12

192.168.0.0/16

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.

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.

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

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.

Create a service account with an access scope. Use the access scope ‘https://www.googleapis.com/auth/devstorage.write_only’.

Create a service account with an access scope. Use the access scope ‘https://www.googleapis.com/auth/cloud-platform’.

Create a service account and add it to the IAM role ‘storage.objectCreator’ for that bucket.

Create a service account and add it to the IAM role ‘storage.objectAdmin’ for that bucket.

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.

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.

Use kubectl app deploy .

Use gcloud app deploy .

Create a docker image from the Dockerfile and upload it to Container Registry. Create a Deployment YAML file to point to that image. Use kubectl to create the deployment with that file.

Create a docker image from the Dockerfile and upload it to Cloud Storage. Create a Deployment YAML file to point to that image. Use kubectl to create the deployment with that file.

Update your web application to use the protocol HTTP/2 instead of HTTP/1.1

Set the concurrency number to 1 for your Cloud Run service.

Set the maximum number of instances for your Cloud Run service to 100.

Set the minimum number of instances for your Cloud Run service to 3.

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.

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.

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.

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.

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.

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.

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

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

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

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.

kubectl delete deployment nginx

kubectl delete –deployment=nginx

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

kubectl delete inginx

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.

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.

Run gcloud app restore.

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

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

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

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".

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.

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.

Deploy Jenkins through the Google Cloud Marketplace.

Create a new Compute Engine instance. Run the Jenkins executable.

Create a new Kubernetes Engine cluster. Create a deployment for the Jenkins image.

Create an instance template with the Jenkins executable. Create a managed instance group with this template.

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

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

Open the Google Cloud console and enable all Google Cloud APIs from the API dashboard.

Open the Google Cloud console and run gcloud init --project in a Cloud Shell.

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.

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.

Run gcloud configurations list followed by gcloud configurations activate .

Run gcloud config list followed by gcloud config activate.

Run gcloud config configurations list followed by gcloud config configurations activate.

Re-authenticate with the gcloud auth login command and select the correct configurations on login.

Navigate to Stackdriver Logging and select resource.labels.project_id="*"

Create a Stackdriver Logging Export with a Sink destination to a BigQuery dataset. Configure the table expiration to 60 days.

Create a Stackdriver Logging Export with a Sink destination to Cloud Storage. Create a lifecycle rule to delete objects after 60 days.

Configure a Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery. Configure the table expiration to 60 days.

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.

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.

Use Shared VPC to connect all projects, and link Stackdriver to one of the projects.

For each project, create a Stackdriver account. In each project, create a service account for that project and grant it the role of Stackdriver Account Editor in all other projects.

Configure a single Stackdriver account, and link all projects to the same account.

Configure a single Stackdriver account for one of the projects. In Stackdriver, create a Group and add the other project names as criteria for that Group.

Modify the existing subnet range to 172.16.20.0/24.

Create a new Secondary IP Range in the VPC and configure the VMs to use that range.

Create a new VPC network for the VMs. Enable VPC Peering between the VMs’ VPC network and the Dataproc cluster VPC network.

Create a new VPC network for the VMs with a subnet of 172.32.0.0/16. Enable VPC network Peering between the Dataproc VPC network and the VMs VPC network. Configure a custom Route exchange.

kubectl get deployments –output=pods

gcloud get pods –selector=”app=prod”

kubectl get pods -I “app=prod”

gcloud list gke-deployments -filter={pod }