You have been asked to select the storage system for the click-data of your company's large portfolio of websites. This data is streamed in from a custom website analytics package at a typical rate of 6,000 clicks per minute, with bursts of up to 8,500 clicks per second. It must been stored for future analysis by your data science and user experience teams. Which storage infrastructure should you choose?

• A.Google Cloud SQL
• B.Google Cloud Bigtable
• C.Google Cloud Storage
• D.Google cloud Datastore

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For this question, refer to the EHR Healthcare case study. You need to define the technical architecture for securely deploying workloads to Google Cloud. You also need to ensure that only verified containers are deployed using Google Cloud services. What should you do? (Choose two.)

• A.Enable Binary Authorization on GKE, and sign containers as part of a CI/CD pipeline.
• B.Configure Jenkins to utilize Kritis to cryptographically sign a container as part of a CI/CD pipeline.
• C.Configure Container Registry to only allow trusted service accounts to create and deploy containers from the registry.
• D.Configure Container Registry to use vulnerability scanning to confirm that there are no vulnerabilities before deploying the workload.

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Your company has decided to make a major revision of their API in order to create better experiences for their developers. They need to keep the old version of the API available and deployable, while allowing new customers and testers to try out the new API. They want to keep the same SSL and DNS records in place to serve both APIs. What should they do?

• A.Configure a new load balancer for the new version of the API.
• B.Reconfigure old clients to use a new endpoint for the new API.
• C.Have the old API forward traffic to the new API based on the path.
• D.Use separate backend pools for each API path behind the load balancer.

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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?

• A.Cloud Spanner, because it is globally distributed
• B.Cloud SQL, because it is a fully managed relational database
• C.Cloud Firestore, because it offers real-time synchronization across devices
• D.BigQuery, because it is designed for large-scale processing of tabular data

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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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