You are using Cloud SQL as the database backend for a large CRM deployment. You want to scale as usage increases and ensure that you don't run out of storage, maintain 75% CPU usage cores, and keep replication lag below 60 seconds. What are the correct steps to meet your requirements?

1. Enable automatic storage increase for the instance.

Create a Stackdriver alert when CPU usage exceeds 75%, and change the instance type to reduce CPU usage.

Create a Stackdriver alert for replication lag, and shard the database to reduce replication time.

1. Enable automatic storage increase for the instance.

Change the instance type to a 32-core machine type to keep CPU usage below 75%.

Create a Stackdriver alert for replication lag, and deploy memcache to reduce load on the master

1. Create a Stackdriver alert when storage exceeds 75%, and increase the available storage on the instance to create more space.

Deploy memcached to reduce CPU load.

Change the instance type to a 32-core machine type to reduce replication lag.

1. Create a Stackdriver alert when storage exceeds 75%, and increase the available storage on the instance to create more space.

You are tasked with building an online analytical processing (OLAP) marketing analytics and reporting tool. This requires a relational database that can operate on hundreds of terabytes of data. What is the Google-recommended tool for such applications?

BigQuery, because it is designed for large-scale processing of tabular data

Cloud Spanner, because it is globally distributed

Cloud SQL, because it is a fully managed relational database

Cloud Firestore, because it offers real-time synchronization across devices

BigQuery, because it is designed for large-scale processing of tabular data

You have deployed an application to Google Kubernetes Engine (GKE), and are using the Cloud SQL proxy container to make the Cloud SQL database available to the services running on Kubernetes. You are notified that the application is reporting database connection issues. Your company policies require a post-mortem. What should you do?

In the GCP Console, navigate to Stackdriver Logging. Consult logs for (GKE) and Cloud SQL.

Use gcloud sql instances restart.

Validate that the Service Account used by the Cloud SQL proxy container still has the Cloud Build Editor role.

In the GCP Console, navigate to Stackdriver Logging. Consult logs for (GKE) and Cloud SQL.

In the GCP Console, navigate to Cloud SQL. Restore the latest backup. Use kubectl to restart all pods.

Your company pushes batches of sensitive transaction data from its application server VMs to Cloud Pub/Sub for processing and storage. What is the Google-recommended way for your application to authenticate to the required GoogleCloud services?

Ensure that VM service accounts are granted the appropriate Cloud Pub/Sub IAM roles.

Ensure that VM service accounts do not have access to Cloud Pub/Sub, and use VM access scopes to grant the appropriate Cloud Pub/Sub IAM roles.

Generate an OAuth2 access token for accessing Cloud Pub/Sub, encrypt it, and store it in Cloud Storage for access from each VM.

Create a gateway to Cloud Pub/Sub using a Cloud Function, and grant the Cloud Function service account the appropriate Cloud Pub/Sub IAM roles.

You want to establish a Compute Engine application in a single VPC across two regions. The application must communicate over VPN to an on-premises network. How should you deploy the VPN?

Deploy Cloud VPN Gateway in each region. Ensure that each region has at least one VPN tunnel to the on-premises peer gateway.

Use VPC Network Peering between the VPC and the on-premises network.

Expose the VPC to the on-premises network using IAM and VPC Sharing.

Create a global Cloud VPN Gateway with VPN tunnels from each region to the on-premises peer gateway.

Deploy Cloud VPN Gateway in each region. Ensure that each region has at least one VPN tunnel to the on-premises peer gateway.

Your applications will be writing their logs to BigQuery for analysis. Each application should have its own table. Any logs older than 45 days should be removed. You want to optimize storage and follow Google-recommended practices. What should you do?

Make the tables time-partitioned, and configure the partition expiration at 45 days

Configure the expiration time for your tables at 45 days

Make the tables time-partitioned, and configure the partition expiration at 45 days

Rely on BigQuery's default behavior to prune application logs older than 45 days

Create a script that uses the BigQuery command line tool (bq) to remove records older than 45 days

You want your Google Kubernetes Engine cluster to automatically add or remove nodes based on CPUload.What should you do?

Configure a HorizontalPodAutoscaler with a target CPU usage. Enable the Cluster Autoscaler from the GCP Console.

Configure a HorizontalPodAutoscaler with a target CPU usage. Enable autoscaling on the managed instance group for the cluster using the gcloud command.

Create a deployment and set the maxUnavailable and maxSurge properties. Enable the Cluster Autoscaler using the gcloud command.

Create a deployment and set the maxUnavailable and maxSurge properties. Enable autoscaling on the cluster managed instance group from the GCP Console.

You need to develop procedures to verify resilience of disaster recovery for remote recovery using GCP. Your production environment is hosted on-premises. You need to establish a secure, redundant connection between your on premises network and the GCP network.What should you do?

Verify that Dedicated Interconnect can replicate files to GCP. Verify that Cloud VPN can establish a secure connection between your networks if Dedicated Interconnect fails.

Verify that Dedicated Interconnect can replicate files to GCP. Verify that direct peering can establish a secure connection between your networks if Dedicated Interconnect fails.

Verify that Dedicated Interconnect can replicate files to GCP. Verify that Cloud VPN can establish a secure connection between your networks if Dedicated Interconnect fails.

Verify that the Transfer Appliance can replicate files to GCP. Verify that direct peering can establish a secure connection between your networks if the Transfer Appliance fails.

Verify that the Transfer Appliance can replicate files to GCP. Verify that Cloud VPN can establish a secure connection between your networks if the Transfer Appliance fails.

Your company operates nationally and plans to use GCP for multiple batch workloads, including some that are not time-critical. You also need to use GCP services that are HIPAA-certified and manage service costs.How should you design to meet Google best practices?

Provision preemptible VMs to reduce cost. Disable and then discontinue use of all GCP services and APIs that are not HIPAA-compliant.

Provision preemptible VMs to reduce cost. Discontinue use of all GCP services and APIs that are not HIPAA-compliant.

Provision preemptible VMs to reduce cost. Disable and then discontinue use of all GCP services and APIs that are not HIPAA-compliant.

Provision standard VMs in the same region to reduce cost. Discontinue use of all GCP services and APIs that are not HIPAA-compliant.

Provision standard VMs to the same region to reduce cost. Disable and then discontinue use of all GCP services and APIs that are not HIPAA-compliant.

Your customer wants to do resilience testing of their authentication layer. This consists of a regional managed instance group serving a public REST API that reads from and writes to a Cloud SQL instance.What should you do?

Schedule a disaster simulation exercise during which you can shut off all VMs in a zone to see how your application behaves.

Engage with a security company to run web scrapers that look your for users' authentication data om malicious websites and notify you if any is found.

Deploy intrusion detection software to your virtual machines to detect and log unauthorized access.

Schedule a disaster simulation exercise during which you can shut off all VMs in a zone to see how your application behaves.

Configure a read replica for your Cloud SQL instance in a different zone than the master, and then manually trigger a failover while monitoring KPIs for our REST API.

Your BigQuery project has several users. For audit purposes, you need to see how many queries each user ran in the last month. What should you do?

Use 'bq show' to list all jobs. Per job, use 'bq Is' to list job information and get the required information.

Connect Google Data Studio to BigQuery. Create a dimension for the users and a metric for the amount of queries per user.

In the BigQuery interface, execute a query on the JOBS table to get the required information.

Use 'bq show' to list all jobs. Per job, use 'bq Is' to list job information and get the required information.

Use Cloud Audit Logging to view Cloud Audit Logs, and create a filter on the query operation to get the required information.

You want to automate the creation of a managed instance group. The VMs have many OS package dependencies. You want to minimize the startup time for new VMs in the instance group. What should you do?

Create a custom VM image with all OS package dependencies. Use Deployment Manager to create the managed instance group with the VM image.

Use Terraform to create the managed instance group and a startup script to install the OS package dependencies.

Create a custom VM image with all OS package dependencies. Use Deployment Manager to create the managed instance group with the VM image.

Use Puppet to create the managed instance group and install the OS package dependencies.

Use Deployment Manager to create the managed instance group and Ansible to install the OS package dependencies.

Your company captures all web traffic data in Google Analytics 360 and stores it in BigQuery. Each country has its own dataset. Each dataset has multiple tables. You want analysts from each country to be able to see and query only the data for their respective countries.How should you configure the access rights?

Create a group per country. Add analysts to their respective country-groups. Create a single group 'all_analysts', and add all country-groups as members. Grant the 'all-analysis' group the IAM role of BigQuery jobUser. Share theappropriate dataset with view access with each respective analyst country-group.

Create a group per country. Add analysts to their respective country-groups. Create a single group 'all_analysts', and add all country-groups as members. Grant the 'all-analysis' group the IAM role of BigQuery jobUser. Share theappropriate tables with view access with each respective analyst country-group.

Create a group per country. Add analysts to their respective country-groups. Create a single group 'all_analysts', and add all country-groups as members. Grant the 'all-analysis' group the IAM role of BigQuery dataViewer. Share theappropriate dataset with view access with each respective analyst country-group.

Create a group per country. Add analysts to their respective country-groups. Create a single group 'all_analysts', and add all country-groups as members. Grant the 'all-analysis' group the IAM role of BigQuery dataViewer. Share theappropriate table with view access with each respective analyst country-group.

You have been engaged by your client to lead the migration of their application infrastructure to GCP. One of their current problems is that the on-premises high performance SAN is requiring frequent and expensive upgrades to keep up with the variety of workloads that are identified as follows: 20TB of log archives retained for legal reasons; 500 GB of VM boot/data volumes and templates; 500 GB of image thumbnails; 200 GB of customer session state data that allows customers to restart sessions even if off-line for several days.Which of the following best reflects your recommendations for a cost-effective storage allocation?

Memcache backed by Persistent Disk SSD storage for customer session state data. Assorted local SSD-backed instances for VM boot/data volumes. Cloud Storage for log archives and thumbnails.

Local SSD for customer session state data. Lifecycle-managed Cloud Storage for log archives, thumbnails, and VM boot/data volumes.

Memcache backed by Cloud Datastore for the customer session state data. Lifecycle- managed Cloud Storage for log archives, thumbnails, and VM boot/data volumes.

Memcache backed by Cloud SQL for customer session state data. Assorted local SSD-backed instances for VM boot/data volumes. Cloud Storage for log archives and thumbnails.

Memcache backed by Persistent Disk SSD storage for customer session state data. Assorted local SSD-backed instances for VM boot/data volumes. Cloud Storage for log archives and thumbnails.

Your web application uses Google Kubernetes Engine to manage several workloads. One workload requires a consistent set of hostnames even after pod scaling and relaunches.Which feature of Kubernetes should you use to accomplish this?

Container environment variables

You are using Cloud CDN to deliver static HTTP(S) website content hosted on a Compute Engine instance group. You want to improve the cache hit ratio.What should you do?

Customize the cache keys to omit the protocol from the key.

Shorten the expiration time of the cached objects.

Make sure the HTTP(S) header "Cache-Region" points to the closest region of your users.

Replicate the static content in a Cloud Storage bucket. Point CloudCDN toward a load balancer on that bucket.

Your architecture calls for the centralized collection of all admin activity and VM system logs within your project.How should you collect these logs from both VMs and services?

Stackdriver automatically collects admin activity logs for most services. The Stackdriver Logging agent must be installed on each instance to collect system logs.

All admin and VM system logs are automatically collected by Stackdriver.

Stackdriver automatically collects admin activity logs for most services. The Stackdriver Logging agent must be installed on each instance to collect system logs.

Launch a custom syslogd compute instance and configure your GCP project and VMs to forward all logs to it.

Install the Stackdriver Logging agent on a single compute instance and let it collect all audit and access logs for your environment.

You have an App Engine application that needs to be updated. You want to test the update with production traffic before replacing the current application version.What should you do?

Deploy the update as a new version in the App Engine application, and split traffic between the new and current versions.

Deploy the update using the Instance Group Updater to create a partial rollout, which allows for canary testing.

Deploy the update as a new version in the App Engine application, and split traffic between the new and current versions.

Deploy the update in a new VPC, and use Google's global HTTP load balancing to split traffic between the update and current applications.

Deploy the update as a new App Engine application, and use Google's global HTTP load balancing to split traffic between the new and current applications.

All compute Engine instances in your VPC should be able to connect to an Active Directory server on specific ports. Any other traffic emerging from your instances is not allowed. You want to enforce this using VPC firewall rules.How should you configure the firewall rules?

Create an egress rule with priority 1000 to deny all traffic for all instances. Create another egress rule with priority 100 to allow the Active Directory traffic for all instances.

Create an egress rule with priority 100 to deny all traffic for all instances. Create another egress rule with priority 1000 to allow the Active Directory traffic for all instances.

Create an egress rule with priority 1000 to allow the Active Directory traffic. Rely on the implied deny egress rule with priority 100 to block all traffic for all instances.

Create an egress rule with priority 100 to allow the Active Directory traffic. Rely on the implied deny egress rule with priority 1000 to block all traffic for all instances.

Your customer runs a web service used by e-commerce sites to offer product recommendations to users. the company has begun experimenting with a machine learning model on Google Cloud Platform to improve the quality of results.What should the customer do to improve their model's results over time?

Save a history of recommendations and results of the recommendations in BigQuery, to be used as training data.

Export Cloud Machine Learning Engine performance metrics from Stackdriver to BigQuery, to be used to analyze the efficiency of the model.

Build a roadmap to move the machine learning model training from Cloud GPUs to Cloud TPUs, which offer better results.

Monitor Compute Engine announcements for availability of newer CPU architectures, and deploy the model to them as soon as they are available for additional performance.

Save a history of recommendations and results of the recommendations in BigQuery, to be used as training data.

A development team at your company has created a dockerized HTTPS web application. You need to deploy the application on Google Kubernetes Engine (GKE) and make sure that the application scales automatically.How should you deploy to GKE?

Use the Horizontal Pod Autoscaler and enable cluster autoscaling. Use an Ingress resource to load-balance the HTTPS traffic.

Use the Horizontal Pod Autoscaler and enable cluster autoscaling on the Kubernetes cluster. Use a Service resource of type LoadBalancer to load-balance the HTTPS traffic.

Enable autoscaling on the Compute Engine instance group. Use an Ingress resource to load balance the HTTPS traffic.

Enable autoscaling on the Compute Engine instance group. Use a Service resource of type LoadBalancer to load-balance the HTTPS traffic.

You need to design a solution for global load balancing based on the URL path being requested. You need to ensure operations reliability and end-to-end in-transit encryption based on Google best practices.What should you do?

Create an HTTPS load balancer with URL maps.

Create a cross-region load balancer with URL Maps.

Create an HTTPS load balancer with URL maps.

Create appropriate instance groups and instances. Configure SSL proxy load balancing.

Create a global forwarding rule. Configure SSL proxy load balancing.

You have an application that makes HTTP requests to Cloud Storage. Occasionally the requests fail with HTTP status codes of 5xx and 429.How should you handle these types of errors?

Implement retry logic using a truncated exponential backoff strategy.

Use gRPC instead of HTTP for better performance.

Implement retry logic using a truncated exponential backoff strategy.

Make sure the Cloud Storage bucket is multi-regional for geo-redundancy.

Monitor https://status.cloud.google.com/feed.atom and only make requests if Cloud Storage is not reporting an incident.

You need to develop procedures to test a disaster plan for a mission-critical application. You want to use Google-recommended practices and native capabilities within GCP.What should you do?

Use Deployment Manager to automate provisioning. Use Stackdriver to monitor and debug your tests.

Use Deployment Manager to automate service provisioning. Use Activity Logs to monitor and debug your tests.

Use Deployment Manager to automate provisioning. Use Stackdriver to monitor and debug your tests.

Use gcloud scripts to automate service provisioning. Use Activity Logs to monitor and debug your tests.

Use gcloud scripts to automate service provisioning. Use Stackdriver to monitor and debug your tests.

Your company creates rendering software which users can download from the company website. Your company has customers all over the world. You want to minimize latency for all your customers. You want to followGooglerecommended practices.How should you store the files?

Save the files in a Multi-Regional Cloud Storage bucket.

Save the files in a Regional Cloud Storage bucket, one bucket per zone of the region.

Save the files in multiple Regional Cloud Storage buckets, one bucket per zone per region.

Save the files in multiple Multi-Regional Cloud Storage buckets, one bucket per multi-region.

Your company acquired a healthcare startup and must retain its customers' medical information for up to 4 more years, depending on when it was created. Your corporate policy is to securely retain this data, and then delete it as soon as regulations allow.Which approach should you take?

Store the data in Cloud Storage and use lifecycle management to delete files when they expire.

Store the data in Google Drive and manually delete records as they expire.

Anonymize the data using the Cloud Data Loss Prevention API and store it indefinitely.

Store the data in Cloud Storage and use lifecycle management to delete files when they expire.

Store the data in Cloud Storage and run a nightly batch script that deletes all expired data.

You are deploying a PHP App Engine Standard service with Cloud SQL as the backend. You want to minimize the number of queries to the database.What should you do?

Set the memcache service level to dedicated. Create a key from the hash of the query, and return database values from memcache before issuing a query to Cloud SQL.

Set the memcache service level to dedicated. Create a cron task that runs every minute to populate the cache with keys containing query results.

Set the memcache service level to shared. Create a cron task that runs every minute to save all expected queries to a key called "cached-queries".

Set the memcache service level to shared. Create a key called "cached-queries", and return database values from the key before using a query to Cloud SQL.

You need to ensure reliability for your application and operations by supporting reliable task scheduling for compute on GCP. Leveraging Google best practices, what should you do?

Using the Cron service provided by App Engine, publish messages to a Cloud Pub/Sub topic. Subscribe to that topic using a message-processing utility service running on Compute Engine instances.

Using the Cron service provided by App Engine, publish messages directly to a message-processing utility service running on Compute Engine instances.

Using the Cron service provided by App Engine, publish messages to a Cloud Pub/Sub topic. Subscribe to that topic using a message-processing utility service running on Compute Engine instances.

Using the Cron service provided by Google Kubernetes Engine (GKE), publish messages directly to a message-processing utility service running on Compute Engine instances.

Using the Cron service provided by GKE, publish messages to a Cloud Pub/Sub topic. Subscribe to that topic using a message-processing utility service running on Compute Engine instances.

Your company is building a new architecture to support its data-centric business focus. You are responsible for setting up the network. Your company's mobile and web-facing applications will be deployed on-premises, and all data analysis will be conducted in GCP. The plan is to process and load 7 years of archived .csv files totaling 900 TB of data and then continue loading 10 TB of data daily. You currently have an existing 100-MB internet connection.What actions will meet your company's needs?

Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a connection with Google using a Dedicated Interconnect or Direct Peering connection and use it to upload files daily.

Compress and upload both archieved files and files uploaded daily using the gsutil -m option.

Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a connection with Google using a Dedicated Interconnect or Direct Peering connection and use it to upload files daily.

Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish one Cloud VPN Tunnel to VPC networks over the public internet, and compress and upload files daily using the gsutil –m option.

Lease a Transfer Appliance, upload archived files to it, and send it to Google to transfer archived data to Cloud Storage. Establish a Cloud VPN Tunnel to VPC networks over the public internet, and compress and upload files daily.

You are developing a globally scaled frontend for a legacy streaming backend data API. This API expects events in strict chronological order with no repeat data for proper processing.Which products should you deploy to ensure guaranteed-once FIFO (first-in, first-out) delivery of data?

Cloud Pub/Sub to Cloud Dataflow

Your company is planning to perform a lift and shift migration of their Linux RHEL 6.5+ virtual machines. The virtual machines are running in an on-premises VMware environment. You want to migrate them to Compute Engine followingGoogle-recommended practices. What should you do?

1. Perform an assessment of virtual machines running in the current VMware environment.

1. Define a migration plan based on the list of the applications and their dependencies.

Migrate all virtual machines into Compute Engine individually with Migrate for Compute Engine.

1. Perform an assessment of virtual machines running in the current VMware environment.

Create images of all disks. Import disks on Compute Engine.

Create standard virtual machines where the boot disks are the ones you have imported.

1. Perform an assessment of virtual machines running in the current VMware environment.

Define a migration plan, prepare a Migrate for Compute Engine migration RunBook, and execute the migration.

1. Perform an assessment of virtual machines running in the current VMware environment.

Install a third-party agent on all selected virtual machines.

Migrate all virtual machines into Compute Engine.

You need to deploy an application to Google Cloud. The application receives traffic via TCP and reads and writes data to the filesystem. The application does not support horizontal scaling. The application process requires full control over the data on the file system because concurrent access causes corruption. The business is willing to accept a downtime when an incident occurs, but the application must be available 24/7 to support their business operations. You need to design the architecture of this application on Google Cloud. What should you do?

Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use a network load balancer in front of the instances.

Use a managed instance group with instances in multiple zones, use Cloud Filestore, and use an HTTP load balancer in front of the instances.

Use a managed instance group with instances in multiple zones, use Cloud Filestore, and use a network load balancer in front of the instances.

Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use an HTTP load balancer in front of the instances.

Use an unmanaged instance group with an active and standby instance in different zones, use a regional persistent disk, and use a network load balancer in front of the instances.

Your company has an application running on multiple Compute Engine instances. You need to ensure that the application can communicate with an on-premises service that requires high throughput via internal IPs, while minimizing latency. What should you do?

Use Cloud VPN to configure a VPN tunnel between the on-premises environment and Google Cloud.

Use OpenVPN to configure a VPN tunnel between the on-premises environment and Google Cloud.

Configure a direct peering connection between the on-premises environment and Google Cloud.

Use Cloud VPN to configure a VPN tunnel between the on-premises environment and Google Cloud.

Configure a Cloud Dedicated Interconnect connection between the on-premises environment and Google Cloud.

You are managing an application deployed on Cloud Run for Anthos, and you need to define a strategy for deploying new versions of the application. You want to evaluate the new code with a subset of production traffic to decide whether to proceed with the rollout. What should you do?

In the Google Cloud Console page for Cloud Run, set up continuous deployment using Cloud Build for the development branch. As part of the Cloud Build trigger, configure the substitution variable TRAFFIC_PERCENTAGE with thepercentage of traffic you want directed to a new version.

Deploy a new revision to Cloud Run with the new version. Configure traffic percentage between revisions.

Deploy a new service to Cloud Run with the new version. Add a Cloud Load Balancing instance in front of both services.

In the Google Cloud Console page for Cloud Run, set up continuous deployment using Cloud Build for the development branch. As part of the Cloud Build trigger, configure the substitution variable TRAFFIC_PERCENTAGE with thepercentage of traffic you want directed to a new version.

In the Google Cloud Console, configure Traffic Director with a new Service that points to the new version of the application on Cloud Run. Configure Traffic Director to send a small percentage of traffic to the new version of theapplication.

You are monitoring Google Kubernetes Engine (GKE) clusters in a Cloud Monitoring workspace. As a Site Reliability Engineer (SRE), you need to triage incidents quickly. What should you do?

Create a custom dashboard in the Cloud Monitoring workspace for each incident, and then add metrics and create alert policies.

Navigate the predefined dashboards in the Cloud Monitoring workspace, and then add metrics and create alert policies.

Navigate the predefined dashboards in the Cloud Monitoring workspace, create custom metrics, and install alerting software on a Compute Engine instance.

Write a shell script that gathers metrics from GKE nodes, publish these metrics to a Pub/Sub topic, export the data to BigQuery, and make a Data Studio dashboard.

Create a custom dashboard in the Cloud Monitoring workspace for each incident, and then add metrics and create alert policies.

You are working at a sports association whose members range in age from 8 to 30. The association collects a large amount of health data, such as sustained injuries. You are storing this data in BigQuery. Current legislation requires you to delete such information upon request of the subject. You want to design a solution that can accommodate such a request. What should you do?

When ingesting new data in BigQuery, run the data through the Data Loss Prevention (DLP) API to identify any personal information. As part of the DLP scan, save the result to Data Catalog. Upon a deletion request, query DataCatalogto find the column with personal information.

Use a unique identifier for each individual. Upon a deletion request, delete all rows from BigQuery with this identifier.

When ingesting new data in BigQuery, run the data through the Data Loss Prevention (DLP) API to identify any personal information. As part of the DLP scan, save the result to Data Catalog. Upon a deletion request, query DataCatalogto find the column with personal information.

Create a BigQuery view over the table that contains all data. Upon a deletion request, exclude the rows that affect the subject's data from this view. Use this view instead of the source table for all analysis tasks.

Use a unique identifier for each individual. Upon a deletion request, overwrite the column with the unique identifier with a salted SHA256 of its value.

Your company is running its application workloads on Compute Engine. The applications have been deployed in production, acceptance, and development environments. The production environment is business-critical and is used 24/7, while the acceptance and development environments are only critical during office hours. Your CFO has asked you to optimize these environments to achieve cost savings during idle times. What should you do?

Use regular Compute Engine instances for the production environment, and use preemptible VMs for the acceptance and development environments.

Create a shell script that uses the gcloud command to change the machine type of the development and acceptance instances to a smaller machine type outside of office hours. Schedule the shell script on one of the production instancesto automate the task.

Use Cloud Scheduler to trigger a Cloud Function that will stop the development and acceptance environments after office hours and start them just before office hours.

Deploy the development and acceptance applications on a managed instance group and enable autoscaling.

Use regular Compute Engine instances for the production environment, and use preemptible VMs for the acceptance and development environments.

Google Professional Cloud Architect Practice Test 4 - Free Online Exam Prep & Questions

Your web application has several VM instances running within a VPC. You want to restrict communications between instances to only the paths and ports you authorize, but you don't want to rely on static IP addresses or subnets because the app can autoscale. How should you restrict communications?

Become a Premium Member for full access

Unlock Premium Member

Google Professional Cloud Architect Practice Test 4

Question

Google Professional Cloud Architect Practice Tests

Practice Tests