Font size
WorksheetsACE-3
Total questions: 50
Worksheet time: 25mins
Your application is running on Google Cloud in a managed instance group (MIG). Cloud logging for one VM shows errors that one of the processes is not responding. In the MIG. You want to replace this VM in the MIG quickly. What are you supposed to do?
Use the gcloud compute instances update command with a REFRESH action for the VM.
Use the gcloud compute instance-groups managed recreate-instances command to recreate the VM.
Select the MIG from the Compute Engine console and, in the menu, select Replace VMs.
Update and apply the instance template of the MIG.
You want to permanently delete a Pub/Sub topic managed by Config Connector in your Google Cloud project. What are you supposed to be doing?
Use kubectl to create the label deleted-by-cnrm and to change its value to true for the topic resource.
Use kubectl to delete the topic resource.
Use gcloud CLI to delete the topic.
Use gcloud CLI to update the topic label managed-by-cnrm to false.
You are managing your employees' accounts through Google Workspace. In the next two years, expected growth will increase staff numbers from 100 to 1 000. Access to Google Cloud accounts for the majority of your employees will be required. The systems and processes will need to support 10x growth without performance degradation, unnecessary complexity, or security issues. What should you do?
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.
You'd like your video encoding software to be hosted on the Compute Engine. Your user base is growing rapidly and users need to be able to encode their videos at all times without interruption or CPU restrictions. You must ensure that your encoding solution is highly available, and you want to follow Google-recommended practices to automate operations. What should you do?
Deploy your solution on multiple standalone Compute Engine instances, and increase the number of existing instances when 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.
Your managed instance group raised an alert stating that new instance creation has failed to create new instances. The problem of creating an instance needs to be resolved. What are you supposed to be doing?
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.
You've created an application that will be attached to the Docker image. You're going to use Google Kubernetes to deploy the Docker image as a workload. Engine. What are you supposed to do?
Upload the image to Cloud Storage and create a Kubernetes Service referencing the image.
Upload the image to Cloud Storage and create a Kubernetes Deployment referencing the image.
Upload the image to Artifact Registry and create a Kubernetes Service referencing the image.
Upload the image to Artifact Registry and create a Kubernetes Deployment referencing the image.
To view a table from your data warehouse that is compiled with BigQuery, you are using Looker Studio. During the day, data is added to the data warehouse. At night, an overwriting of the table recalculates the day's summaries. You just noticed that the charts in Looker Studio are broken, and you want to analyze the problem. What should you do?
In Cloud Logging, create a filter for your Looker Studio report.
Use the open source CLI tool, Snapshot Debugger, to find out why the data was not refreshed correctly.
Review the Error Reporting page in the Google Cloud console to find any errors.
Use the BigQuery interface to review the nightly job and look for any errors.
In several Google Cloud projects, you've set up a few resources. There are separate billing accounts for all projects. You want a uniform visual representation of all costs arising in order to be more accurate about future charges. You want to include new cost data as soon as possible. What should you do?
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.
Visit the Cost Table page to get a CSV export and visualize it using Looker Studio.
Configure Billing Data Export to BigQuery and visualize the data in Looker Studio.
You've got a batch of tasks that run every night and are using lots of virtual machines. It's capable of fault tolerance, and may allow certain VMs to be shut down. The current cost of VMs is too high. What should you do?
Run a test using simulated maintenance events. If the test is successful, use Spot N2 Standard VMs when running future jobs.
Run a test using simulated maintenance events. If the test is successful, use N2 Standard VMs when running future jobs.
Run a test using a managed instance group. If the test is successful, use N2 Standard VMs in the managed instance group when running future jobs.
Run a test using N1 standard VMs instead of N2. If the test is successful, use N1 Standard VMs when running future jobs.
There is a large amount of unstructured information in different file formats within your company. For the data, you want to perform ETL transformations. You need to make the data accessible on Google Cloud so it can be processed by a Dataflow job. What should you do?
Upload the data to BigQuery using the bq command line tool.
Upload the data to Cloud Storage using the gcloud storage command.
Upload the data into Cloud SQL using the import function in the Google Cloud console.
Upload the data into Cloud Spanner using the import function in the Google Cloud console.
You have deployed an application on a single Compute Engine instance. Log files are written to disk by the application. Users are starting to report errors with this application. You want to diagnose the problem. What should you do?
Navigate to Cloud Logging and view the application logs.
Configure a health check on the instance and set a “consecutive successes” Healthy threshold value of 1.
Connect to the instance’s serial console and read the application logs.
Install and configure the Ops agent and view the logs from Cloud Logging.
You recently received a new Google Cloud project with an attached billing account where you will work. In Cloud Storage, you need to set up Instances, configure Firewalls and store data. You want to follow Google-recommended practices. What should you do?
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.
For an application that will be deployed on Google Cloud, your application development team has created a Docker image. The infrastructure associated with this application does not want to be managed by your team. You need to ensure that the application can scale automatically as it gains popularity. What should you do?
Create an instance template with the container image, and deploy a Managed Instance Group with Autoscaling.
Upload Docker images to Artifact Registry, and deploy the application on Google Kubernetes Engine using Standard mode.
Upload Docker images to the Cloud Storage, and deploy the application on Google Kubernetes Engine using Standard mode.
Upload Docker images to Artifact Registry, and deploy the application on Cloud Run.
You'll be moving your business critical application to Google Cloud from a local data center. As part of your high-availability strategy, you want
to ensure that any data used by the application will be immediately available if a zonal failure occurs. What are you supposed to be doing?
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.
Full control of Compute Engine resources in your development project is required by the DevOps group within your organisation. However, they should not have permission to create or update any other resources in the project. You want to follow Google’s recommendations for setting permissions for the DevOps group. What should you do?
Grant the basic role roles/viewer and the predefined role roles/compute.admin to the DevOps group.
Create an IAM policy and grant all compute.instanceAdmin.* permissions to the policy. Attach the policy to the DevOps group.
Create a custom role at the folder level and grant all compute.instanceAdmin.* permissions to the role. Grant the custom role to the DevOps group.
Grant the basic role roles/editor to the DevOps group.
An on premise ecommerce application is being used by your team. The application has a complex set of microservices written in Python, and every microservice runs on Docker containers. Configurations are injected by using environment variables. You need to deploy your current application to a serverless Google Cloud cloud solution. What should you do?
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.
In the Kubernetes Engine cluster, you've got multiple microservices. Images are being rendered by a single microservice. Compared to the memory required, a microservice responsible for rendering images requires an excessive amount of CPU time. The other microservices are workloads that are optimized for n2-standard machine types. You need to optimize your cluster so that all workloads are using resources as efficiently as possible. What should you do?
Assign the pods of the image rendering microservice a higher pod priority than the other 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 the image rendering microservice. Create a node pool 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.
You're working for a team that's developing a new application that needs to be installed on Kubernetes. The production application is critical for the business and needs to be optimised in terms of reliability. You need to provision a Kubernetes cluster and want to follow Google-recommended practices. What should you do?
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.
You're responsible for the Compute Engine Web application. If users experience high latency for at least five minutes, you want your support team to be notified automatically. You need a Google-recommended solution with no development cost. What should you do?
Export Cloud Monitoring metrics to BigQuery and use a Looker Studio dashboard to monitor your web application’s latency.
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.
You've got a set of onpremises data analytics binaries that process data files in memory for about 45 minutes every midnight. These data files range from 1 GB to 16 GB in size. You want to migrate this application to Google Cloud with minimal effort and cost. What should you do?
Create a container for the set of binaries. Use Cloud Scheduler to start a Cloud Run job for the container.
Create a container for the set of binaries. Deploy the container to Google Kubernetes Engine (GKE) and use the Kubernetes scheduler to start the application.
Upload the code to Cloud Functions. Use Cloud Scheduler to start the application.
Lift and shift to a VM on Compute Engine. Use an instance schedule to start and stop the instance.
You used the gcloud container clusters command to create two Google Cloud Kubernetes (GKE) clusters: prod-cluster and dev-cluster.
• prod-cluster is a standard cluster.
• dev-cluster is an auto-pilot cluster.
When you run the kubectl get nodes command, you only see the nodes from prod-cluster. Which commands should you run to check the node status for dev-cluster?
gcloud container clusters get-credentials dev-cluster
kubectl get nodes
gcloud container clusters update -generate-password dev-cluster kubectl get nodes
kubectl config set-context dev-cluster
kubectl cluster-info
kubectl config set-credentials dev-cluster
kubectl cluster-info
In your development process, you've recently discovered that many service account keys are being used by your developers. While you work on a long term improvement, you need to quickly implement a process to enforce short-lived service account credentials in your company. You have the following requirements:
• All service accounts that require a key should be created in a centralized project called pj-sa.
• Service account keys should only be valid for one day.
You need a Google-recommended solution that minimizes cost. What should you do?
Implement a Cloud Run job to rotate all service account keys periodically in pj-sa. Enforce an org policy to deny service account key creation with an exception to pj-sa.
Implement a Kubernetes CronJob to rotate all service account keys periodically. Disable attachment of service accounts to resources in all projects with an exception to pj-sa.
Enforce an org policy constraint allowing the lifetime of service account keys to be 24 hours. Enforce an org policy constraint denying service account key creation with an exception on pj-sa.
Enforce a DENY org policy constraint over the lifetime of service account keys for 24 hours. Disable attachment of service accounts to resources in all projects with an exception to pj-sa.
A three-tier web application using the MySQL database is being used by your company on a VM. To use this application on Google Cloud Instances and SQL Server, you will need to generate an estimate of the total infrastructure cost for these services. What are you going to do?
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 the Google Cloud Pricing Calculator and select the Cloud Operations template to define your web application with as much detail as possible.
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 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.
You've got a Bigtable instance which consists of three nodes that are storing Personally Identifiable Information,PII. In your company's security information and event management, you must record all reading or writing operations that include any metadata or configuration read of this database table. (SIEM) system. What are you supposed to do?
• Navigate to Cloud Monitoring 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 Admin Write logs for the Bigtable instance.
• Create a Cloud Functions instance to export logs from Cloud Logging to your SIEM.
• 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.
• 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.
You'd like to create a Google Kubernetes Engine cluster. The cluster must have verifiable node identity and integrity, and the nodes cannot be accessed from the Internet. You want to reduce the operational cost of managing your cluster, and you want to follow Google-recommended practices. What should you do?
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.
Your company wants to migrate their on-premises workloads to Google Cloud. The current on-premises workloads consist of:
• A Flask web application
• A backend API
• A scheduled long-running background job for ETL and reporting
You need to keep operational costs low. You want to follow Google-recommended practices to migrate these workloads to serverless solutions on Google Cloud. What should you do?
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.
Your company is moving its continuous integration and delivery (CI/CD) pipeline to Compute Engine instances. All cloud infrastructure will be managed by this pipeline in code. How can you ensure that the pipeline has appropriate permissions while your system is following security best practices?
• 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.
• 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 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.
By using the standard storage class, your application stores files in cloud storage. Only files generated in the past 30 days need to be accessed by this application. You want to automatically save costs on files that are no longer accessed by the application. What should you do?
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.
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.
You are being asked by your manager to set up a workload for the Kubernetes cluster. You're not sure about the workload's resources requirements or how to handle them. Depending on the use patterns, external dependencies or any number of factors, requirements may differ. You need a solution that makes cost-effective
recommendations regarding CPU and memory requirements, and allows the workload to function consistently in any situation. You want to follow
Google-recommended practices. What should you do?
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.
You need to migrate invoice documents stored on-premises to Cloud Storage. The documents have the following storage requirements:
• Documents must be kept for five years.
• Up to five revisions of the same invoice document must be stored, to allow for corrections.
• Documents older than 365 days should be moved to lower cost storage tiers.
You want to follow Google-recommended practices to minimize your operational and development costs. What should you do?
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
You've installed Google Cloud CLI on your workstation and configured the proxy settings. However, you're afraid that the gcloud CLI logs will contain your proxy credentials. You're trying to prevent your proxy credentials from being logged in. What are you supposed to do?
Configure username and password by using gcloud config set proxy/username and gcloud config set proxy/password commands.
ncode username and password in sha256 encoding, and save in to a text file. Use filename as a value in the gcloud config set
core/custom_ca_certs_file command.
Provide values for CLOUDSDK_PROXY_USERNAME and CLOUDSDK_PROXY_PASSWORD in the gcloud CLI tool configuration file.
Set the CLOUDSDK_PROXY_USERNAME and CLOUDSDK_PROXY_PASSWORD properties by using environment variables in your command
line tool.
Your company developed an application to deploy on Google Kubernetes Engine. Certain parts of the application are not fault-tolerant and are
allowed to have downtime. There is a critical need for other parts of the application to be available, which must always be accessible. Google Kubernetes needs to be configured. Engine cluster while optimizing for cost. What are you supposed to do?
Create a cluster with a single node-pool by using standard VMs. Label he 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 VM node pool and a node 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 a nods pool by using standard VMs. Deploy the critical deployments on the node pool
by using standard VMs and the fault-tolerant deployments on the Spot VM node pool.
Using serverless technology, you need to install an application on Google Cloud. With a modest percentage of production traffic, you want to test the new version of your application. What are you supposed to do?
Deploy the application to Cloud Run. Use gradual rollouts for traffic splitting.
Deploy the application to Google Kubernetes Engine. Use Anthos Service Mash for traffic splitting.
Deploy the application to Cloud Functions. Specify the version number in the functions name.
Deploy the application to App Engine. For each new version, create a new service.
Your company's security vulnerability management policy requires that a member of the safety team have visibility into vulnerabilities as well as any additional operating system Metadata for an instance of the Compute Engine. This Compute Engine instance hosts a critical application in your Google Cloud project. You
need to implement your company's security vulnerability management policy. What should you do?
• 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 the Compute Engine instance.
• Provide the security team member roles/osconfig.inventoryViewer permission.
• Ensure that the OS Config agent is installed on the Compute Engine instance.
• Provide the security team member roles/osconfig.vulnerabilityReportViewer permission.
• Ensure that the OS Config agent is installed on the Compute Engine instance.
• Create a log sink to BigQuery dataset.
• Provide the security team member with access to this dataset.
You'd like to enable your development team to take advantage of an existing Cloud Run service in production by deploying new features. To minimize the risk associated with it With a new revision, you want to reduce the number of customers that may be affected by an interruption without introducing any changes or development Operational costs for your customers. You want to follow Google-recommended practices for managing revisions to a service. What should you do?
Ask your customers to retry access to your service with exponential backoff to mitigate any potential problems after the new revision is
deployed
Gradually roll out the new revision and split customer traffic between the revisions to allow rollback in case a problem occurs.
Send all customer traffic to the new revision, and roll back to a previous revision if you witness any problems in production.
Deploy your application to a second Cloud Run service, and ask your customers to use the second Cloud Run service.
You have deployed an application on a Compute Engine instance. Access to a Linux based instance is requested by an outside consultant. The consultant is connected to your company's network by a VPN connection, but he has no Google account. What are you supposed to do?
Instruct the external consultant to use the gcloud compute ssh command line tool by using Identity-Aware Proxy to access the instance
Instruct the external consultant to use the gcloud compute ssh command line tool by using the public IP address of the instance to access
it.
Instruct the external consultant to generate an SSH key pair, and request the public key from the consultant. Add the public key to the
instance yourself, and have the consultant access the instance through SSH with their private key
Instruct the external consultant to generate an SSH key pair, and request the private key from the consultant. Add the private key to the
instance yourself, and have the consultant access the instance through SSH with their public key.
Your startup company is looking for more information on what's going on in the Google Cloud environment after last week's security incident. You need to
monitor unexpected firewall changes and instance creation. Your company prefers simple solutions. What should you do?
Create a log sink to forward Cloud Audit Logs filtered for firewalls and compute instances to Cloud Storage. Use BigQuery to periodically
analyze log events in the storage bucket.
Use Cloud Logging filters to create log-based metrics for firewall and instance actions. Monitor the changes and set up reasonable alerts.
Install Kibana on a compute instance. Create a log sink to forward Cloud Audit Logs filtered for firewalls and compute instances to
Pub/Sub. Target the Pub/Sub topic to push messages to the Kibana instance. Analyze the logs on Kibana in real time.
Turn on Google Cloud firewall rules logging, and set up alerts for any insert, update, or delete events.
For an application that is part of more than one project, you need to configure service accounts. Virtual machinesVMs running on the Web Applications project need access to BigQuery datasets in the crmdatabases project. You want to follow Google-recommended practices to grant access to the
service account in the web-applications project. What should you do?
Grant "project owner" for web-applications appropriate roles to crm-databases.
Grant "project owner" role to crm-databases and the web-applications project.
Grant "project owner" role to crm-databases and roles/bigquery.dataViewer role to web-applications.
Grant roles/bigquery.dataViewer role to crm-databases and appropriate roles to web-applications.
Your Dataproc cluster runs in a single Virtual Private Cloud (VPC) network in a single subnetwork with range 172.16.20.128/25. There are no Private IP addresses in the sub network are available. You want to add new VMs to communicate with your cluster using the minimum number of
steps. What should you do?
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.
You are building a backend service for an ecommerce platform that will persist transaction data from mobile and web clients. After the platform is launched, you expect a large volume of global transactions. Your business team wants to run SQL queries to analyze the data. You need to build a highly available and scalable data store for the platform. What should you do?
Create a multi-region Cloud Spanner instance with an optimized schema.
Create a multi-region Firestore database with aggregation query enabled.
Create a multi-region Cloud SQL for PostgreSQL database with optimized indexes.
Create a multi-region BigQuery dataset with optimized tables.
Provisioning access for all Google Cloud users in your organization is the responsibility of you. A startup company that has its own Google Cloud business was recently acquired by your firm. You need to ensure that your Site Reliability Engineers (SREs) have the same project permissions in the
startup company's organization as in your own organization. What should you do?
In the Google Cloud console for your organization, select Create role from selection, and choose destination as the startup company's
organization.
In the Google Cloud console for the startup company, select Create role from selection and choose source as the startup company's Google
Cloud organization.
Use the gcloud iam roles copy command, and provide the Organization ID of the startup company's Google Cloud Organization as the
destination.
Use the gcloud iam roles copy command, and provide the project IDs of all projects in the startup company's organization as the
destination.
Using the SpeechtoText API, you must extract text from audio files. The audio files are pushed to a Cloud Storage bucket. A fully managed, serverless computing solution that requires authentication and is compatible with Googlerecommended practices needs to be implemented. You want to
automate the call to the API by submitting each file to the API as the audio file arrives in the bucket. What should you do?
Create an App Engine standard environment triggered by Cloud Storage bucket events to submit the file URI to the Google Speech-to-TextAPI.
Run a Kubernetes job to scan the bucket regularly for incoming files, and call the Speech-to-Text API for each unprocessed file.
Run a Python script by using a Linux cron job in Compute Engine to scan the bucket regularly for incoming files, and call the Speech-to-Text
API for each unprocessed file.
Create a Cloud Function triggered by Cloud Storage bucket events to submit the file URI to the Google Speech-to-Text API.
You are requested by your customer to create a secure website with autoscaling based on the CPU load of the compute instance. By storing static content in cloud storage, you want to increase performance. Which resources are needed to distribute the user traffic?
An external HTTP(S) load balancer with a managed SSL certificate to distribute the load and a URL map to target the requests for the static
content to the Cloud Storage backend.
An external network load balancer pointing to the backend instances to distribute the load evenly. The web servers will forward the request
to the Cloud Storage as needed.
An internal HTTP(S) load balancer together with Identity-Aware Proxy to allow only HTTPS traffic.
An external HTTP(S) load balancer to distribute the load and a URL map to target the requests for the static content to the Cloud Storage
backend. Install the HTTPS certificates on the instance.
Rental of construction equipment at large scale is a key business for your company. Multiple sensors have been set up in all the equipment rented to transmit event data every few seconds. These signals can be different from the engine's status, distance travelled, fuel level and more. Customers are billed based on the consumption monitored by these sensors. You expect high throughput – up to thousands of events per hour per device – and need to retrieve consistent data based on the time of the event. Storing and retrieving individual signals should be atomic. What should you do?
Create files in Cloud Storage as data comes in.
Create a file in Filestore per device, and append new data to that file
Ingest the data into Cloud SQL. Use multiple read replicas to match the throughput.
Ingest the data into Bigtable. Create a row key based on the event timestamp
Your new corporate laptop has just been installed with Google Cloud CLI. In Google Cloud, you must list the current instances of your company. Before running the gcloud compute instances list command, what are you supposed to do? (Choose two.)
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.
You are planning to migrate your on-premises data to Google Cloud. The data includes:
• 200 TB of video files in SAN storage
• Data warehouse data stored on Amazon Redshift
• 20 GB of PNG files stored on an S3 bucket
You need to load the video files into a Cloud Storage bucket, transfer the data warehouse data into BigQuery, and load the PNG files into a second
Cloud Storage bucket. You want to follow Google-recommended practices and avoid writing any code for the migration. What should you do?
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.
In the same project, several applications will be running on different Compute Engine instances. When calling Google Cloud APIs, you want to specify the service account used by each instance at a more granular level. What are you supposed to do?
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.
You're creating an application that runs on Google Kubernetes Engine. You've chosen MongoDB as the most suitable database system for your application, and you want to deploy a managed MongoDB environment that provides support for the Service Level Agreement. What are you supposed to do?
Create a Cloud Bigtable cluster, and use the HBase API.
Deploy MongoDB Atlas from the Google Cloud Marketplace.
Download a MongoDB installation package, and run it on Compute Engine instances.
Download a MongoDB installation package, and run it on a Managed Instance Group.
You're in charge of a project in your company's BI department. Data is streamed to BigQuery via a data pipeline. You'd like users of the BI department to be able to run custom SQL query on BigQuery data that is most recent. What should you do?
Create a Data Studio dashboard that uses the related BigQuery tables as a source and give the BI team view access to the Data Studio
dashboard.
Create a Service Account for the BI team and distribute a new private key to each member of the BI team.
Use Cloud Scheduler to schedule a batch Dataflow job to copy the data from BigQuery to the BI team's internal data warehouse.
Assign the IAM role of BigQuery User to a Google Group that contains the members of the BI team.
Your company is moving its entire workload to Compute Engine. You should be able to access certain servers via the Internet, and other servers must only be available on your internal network. Any server should be able to talk about specific ports and protocols with one another. The current on-premises network relies on a demilitarized zone (DMZ) for the public servers and a Local Area Network (LAN) for the private servers. You need to design the networking infrastructure on
Google Cloud to match these requirements. What should you do?
1. Create a single VPC with a subnet for the DMZ and a subnet for the LAN. 2. Set up firewall rules to open up relevant traffic between the
DMZ and the LAN subnets, and another firewall rule to allow public ingress traffic for the DMZ.
1. Create a single VPC with a subnet for the DMZ and a subnet for the LAN. 2. Set up firewall rules to open up relevant traffic between the
DMZ and the LAN subnets, and another firewall rule to allow public egress traffic for the DMZ.
1. Create a VPC with a subnet for the DMZ and another VPC with a subnet for the LAN. 2. Set up firewall rules to open up relevant traffic
between the DMZ and the LAN subnets, and another firewall rule to allow public ingress traffic for the DMZ.
1. Create a VPC with a subnet for the DMZ and another VPC with a subnet for the LAN. 2. Set up firewall rules to open up relevant traffic
between the DMZ and the LAN subnets, and another firewall rule to allow public egress traffic for the DMZ.
