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Your company’s infrastructure is on-premises, but all machines are running at maximum capacity. You want to burst to Google Cloud. The workloads on Google Cloud must be able to directly communicate to the workloads on-premises using a private IP range. What should you do?

A.

In Google Cloud, configure the VPC as a host for Shared VPC.

B.

In Google Cloud, configure the VPC for VPC Network Peering.

C.

Create bastion hosts both in your on-premises environment and on Google Cloud. Configure both as proxy servers using their public IP addresses.

D.

Set up Cloud VPN between the infrastructure on-premises and Google Cloud.

You have developed a web application that serves traffic for a local event and are expecting unpredictable traffic. You have containerized the application, and you now want to deploy the application on Google Cloud. You also want to minimize costs. What should you do?

A.

Deploy the web application as a Cloud Run service.

B.

Deploy the web application on Google Kubernetes Engine In Standard mode.

C.

Deploy the web application as a Cloud Run job.

D.

Deploy the web application on Google Kubernetes Engine in Autopilot mode.

For analysis purposes, you need to send all the logs from all of your Compute Engine instances to a BigQuery dataset called platform-logs. You have already installed the Stackdriver Logging agent on all the instances. You want to minimize cost. What should you do?

A.

1. Give the BigQuery Data Editor role on the platform-logs dataset to the service accounts used by your instances.2. Update your instances’ metadata to add the following value: logs-destination: bq://platform-logs.

B.

1. In Stackdriver Logging, create a logs export with a Cloud Pub/Sub topic called logs as a sink.2. Create a Cloud Function that is triggered by messages in the logs topic.3. Configure that Cloud Function to drop logs that are not from Compute Engine and to insert Compute Engine logs in the platform-logs dataset.

C.

1. In Stackdriver Logging, create a filter to view only Compute Engine logs.2. Click Create Export.3. Choose BigQuery as Sink Service, and the platform-logs dataset as Sink Destination.

D.

1. Create a Cloud Function that has the BigQuery User role on the platform-logs dataset.2. Configure this Cloud Function to create a BigQuery Job that executes this query:INSERT INTO dataset.platform-logs (timestamp, log)SELECT timestamp, log FROM compute.logsWHERE timestamp > DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY)3. Use Cloud Scheduler to trigger this Cloud Function once a day.

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?

A.

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

B.

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

C.

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.

D.

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

Your team maintains the infrastructure for your organization. The current infrastructure requires changes. You need to share your proposed changes with the rest of the team. You want to follow Google’s recommended best practices. What should you do?

A.

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

B.

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

C.

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

D.

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

You are deploying a large multi-tiered application with more than 1,000 IP addresses in a Google Cloud project that needs to be securely isolated. The application includes the:

    web tier with frontend servers for public traffic

    application tier with servers running core application logic that only need access from the web tier and

    database tier with database servers that only need access from the application tierYou want to minimize cost, complexity, and administrative overhead in the network architecture. What should you do?

    database tier with database servers that only need access from the application tierYou want to minimize cost, complexity, and administrative overhead in the network architecture. What should you do?

A.

Create a /24 Shared VPC with separate subnets for each tier. Use firewall rules that reference network tags to control traffic.

B.

Create one custom mode /16 VPC with three subnets. Place each tier in its own subnet and use firewall rules that reference IP subnets to control traffic.

C.

Deploy each tier into a separate custom mode VPC. Use VPC Network Peering to securely connect each Custom mode VPC. Manage firewall rules individually in each VPC.

D.

Deploy each tier in a /24 VPC by using network tags to identify instances. Implement firewall rules for fine-grained network segmentation.

You are migrating a business critical application from your local data center into Google Cloud. 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 should you do?

A.

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.

B.

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

C.

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.

D.

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

You will have several applications running on different Compute Engine instances in the same project. You want to specify at a more granular level the service account each instance uses when calling Google Cloud APIs. What should you do?

A.

When creating the instances, specify a Service Account for each instance

B.

When creating the instances, assign the name of each Service Account as instance metadata

C.

After starting the instances, use gcloud compute instances update to specify a Service Account for each instance

D.

After starting the instances, use gcloud compute instances update to assign the name of the relevant Service Account as instance metadata

You are deploying an application on Google Cloud that requires a relational database for storage. To satisfy your company's security policies, your application must connect to your database through an encrypted and authenticated connection that requires minimal management and integrates with Identity and Access Management (IAM). What should you do?

A.

Deploy a Cloud SQL database with the SSL mode set to encrypted only, configure SSL/TLS client certificates, and configure a database user and password.

B.

Deploy a Cloud SOL database and configure IAM database authentication. Access the database through the Cloud SQL Auth Proxy.

C.

Deploy a Cloud SQL database with the SSL mode set to encrypted only, configure SSL/TLS client certificates, and configure IAM database authentication.

D.

Deploy a Cloud SQL database and configure a database user and password. Access the database through the Cloud SQL Auth Proxy.

Your company is running a three-tier web application on virtual machines that use a MySQL database. You need to create an estimated total cost of cloud infrastructure to run this application on Google Cloud instances and Cloud SQL. What should you do?

A.

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.

B.

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.

C.

Use the Google Cloud Pricing Calculator and select the Cloud Operations template to define your web application with as much detail as possible.

D.

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.