A production database virtual machine on Google Compute Engine has an ext4-formatted persistent disk for data files The database is about to run out of storage space How can you remediate the problem with the least amount of downtime?

• A.In the Cloud Platform Console, increase the size of the persistent disk and use the resize2fs command in Linux.
• B.Shut down the virtual machine, use the Cloud Platform Console to increase the persistent disk size, then restart the virtual machine.
• C.In the Cloud Platform Console, increase the size of the persistent disk and verify the new space is ready to use with the fdisk command in Linux.
• D.In the Cloud Platform Console, create a new persistent disk attached to the virtual machine, format and mount it, and configure the database service to move the files to the new disk.
• E.In the Cloud Platform Console, create a snapshot of the persistent disk, restore the snapshot to a new larger disk, unmount the old disk, mount the new disk, and restart the database service.

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Your application needs to process credit card transactions. You want the smallest scope of Payment Card Industry (PCI) compliance without compromising the ability to analyze transactional data and trends relating to which payment methods are used. How should you design your architecture?

• A.Create a tokenizer service and store only tokenized data.
• B.Create separate projects that only process credit card data.
• C.Create separate subnetworks and isolate the components that process credit card data.
• D.Streamline the audit discovery phase by labeling all of the virtual machines (VMs) that process PCI data.
• E.Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the auditor.

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You want to optimize the performance of an accurate, real-time, weather-charting application. The data comes from 50,000 sensors sending 10 readings a second, in the format of a timestamp and sensor reading.
Where should you store the data?

• A.Google BigQuery
• B.Google Cloud SQL
• C.Google Cloud Bigtable
• D.Google Cloud Storage

Correct Answer: C

Explanation/Reference:
Explanation:
Google Cloud Bigtable is a scalable, fully-managed NoSQL wide-column database that is suitable for both real-time access and analytics workloads.
Good for:
Low-latency read/write access

High-throughput analytics

Native time series support

Common workloads:
IoT, finance, adtech

Personalization, recommendations

Monitoring

Geospatial datasets

Graphs

References: https://cloud.google.com/storage-options/

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Your company is using Google Cloud. You have two folders under the Organization: Finance and Shopping.
The members of the development team are in a Google Group. The development team group has been assigned the Project Owner role on the Organization. You want to prevent the development team from creating resources in projects in the Finance folder. What should you do?

• A.Assign the development team group the Project Viewer role on the Finance folder, and assign the development team group the Project Owner role on the Shopping folder.
• B.Assign the development team group only the Project Viewer role on the Finance folder.
• C.Assign the development team group the Project Owner role on the Shopping folder, and remove the development team group Project Owner role from the Organization.
• D.Assign the development team group only the Project Owner role on the Shopping folder.

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For this question, refer to the JencoMart case study.
JencoMart wants to move their User Profiles database to Google Cloud Platform. Which Google Database should they use?

• A.Cloud Spanner
• B.Google BigQuery
• C.Google Cloud SQL
• D.Google Cloud Datastore

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