A multinational retail company has approached you to help design its systems. They have millions of transactions at their point of sale systems across the world that need to be captured, stored, and analyzed. They are seeing more growth and expect to expand into even more geographies. Which database would be appropriate for them?
A. Cloud Datastore
B. Cloud Storage
C. Cloud Spanner
D. Cloud SQL
Which of the following NIST Cloud characteristics uses the business model of shared re-sources in a cloud environment?
A. Elasticity
B. Availability
C. Broad Network Access
D. Multi-Tenancy
Your organization needs to analyze data in order to gather insights into its daily operations. You only want to pay for the data you store and the queries you perform. Which Google Cloud product should your organization choose for its data analytics warehouse?
A. Cloud SQL
B. Dataproc
C. Cloud Spanner
D. BigQuery
A prospect wants to be able to store and analyze data. Their analysts already know SQL, but are not familiar with other technologies. Which of these databases can the analysts use without addi-tional training?
A. Cloud SQL, BigQuery, Datastore
B. Spanner, Cloud SQL, BigQuery
C. Cloud SQL, Firestore, Datastore
D. Cloud SQL, Bigtable, BigQuery
Your organization is developing and deploying an application on Google Cloud. Tracking your Google Cloud spending needs to stay as simple as possible.
What should you do to ensure that workloads in the development environment are fully isolated from production workloads?
A. Apply a unique tag to development resources
B. Associate the development resources with their own network
C. Associate the development resources with their own billing account
D. Put the development resources in their own project
Your organization needs to plan its cloud infrastructure expenditures.
Which should your organization do?
A. Review cloud resource costs frequently, because costs change often based on use
B. Review cloud resource costs annually as part of planning your organization's overall budget
C. If your organization uses only cloud resources, infrastructure costs are no longer part of your overall budget
D. Involve fewer people in cloud resource planning than your organization did for on-premises resource planning
Your company is running the majority of its workloads in a co-located data center. The workloads are running on virtual machines (VMs) on top of a hypervisor and use either Linux or Windows server editions. As part of your company's transformation strategy, you need to modernize workloads as much as possible by adopting cloud-native technologies. You need to migrate the workloads into Google Cloud.
What should you do?
A. Export the VMs into VMDK format, and import them into Compute Engine
B. Export the VMs into VMDK format, and import them into Google Cloud VMware Engine
C. Migrate the workloads using Migrate for Compute Engine
D. Migrate the workloads using Migrate for Anthos
Which Google Cloud product provides a consistent platform for multi-cloud application deployments and extends other Google Cloud services to your organization's environment?
A. Google Kubernetes Engine
B. Virtual Public Cloud
C. Compute Engine
D. Anthos
A Multiple projects within your organization have long-term VM usage. Based on current demand, they are able to project into the future and estimate how many VM hours they will use every year. Going in for a committed use contract seems sensible. How can you configure committed use easily across all the projects?
A. Enable committed use with discount sharing for the projects
B. Review the usage of resources by each project on a daily basis. Enable committed use for the following day based on that number, so that it gives maximum granularity without wastage.
C. Take a report of each project's use in the last year. Enable committed use on a per-project basis based on the previous year's numbers.
D. Share a Google Sheet and request each project team to send in their estimate. Enable committed use accordingly on a per-project basis.
A customer has new applications to build that has to handle both batch data and streaming data. Which product should they choose?
A. Dataprep
B. Dataflow
C. Dataproc
D. Data Fusion
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