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Professional-Cloud-Architect Practice Test


Page 17 out of 51 Pages

Topic 5, Misc Questions

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





C.
  

Google Cloud Storage



https://cloud.google.com/solutions/data-analytics-partner-ecosystem
https://zulily-tech.com/2015/08/10/leveraging-google-cloud-dataflow-for-clickstream-processing/

Auditors visit your teams every 12 months and ask to review all the Google Cloud Identity and Access
Management (Cloud IAM) policy changes in the previous 12 months. You want to streamline and expedite the analysis and audit process. What should you do?


A.

Create custom Google Stackdriver alerts and send them to the auditor.


B.

Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the
auditor.


C.

Use cloud functions to transfer log entries to Google Cloud SQL and use ACLS and views to limit an
auditor's view.


D.

Enable Google Cloud Storage (GCS) log export to audit logs Into a GCS bucket and delegate access to
the bucket





D.
  

Enable Google Cloud Storage (GCS) log export to audit logs Into a GCS bucket and delegate access to
the bucket



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





E.
  

Enable Logging export to Google BigQuery and use ACLs and views to scope the data shared with the
auditor



The proper model for exporting credit card processing data is to forward from a squid proxy to Stackdriver
Logging, and export from Stackdriver Logging into BigQuery
https://cloud.google.com/solutions/pci-dss

Your company places a high value on being responsive and meeting customer needs quickly. Their primary
business objectives are release speed and agility. You want to reduce the chance of security errors being
accidentally introduced. Which two actions can you take? Choose 2 answers


A.

Ensure every code check-in is peer reviewed by a security SME.


B.

Use source code security analyzers as part of the CI/CD pipeline.


C.

Ensure you have stubs to unit test all interfaces between components.


D.

Enable code signing and a trusted binary repository integrated with your CI/CD pipeline.


E.

Run a vulnerability security scanner as part of your continuous-integration /continuous-delivery (CI/CD)
pipeline.





B.
  

Use source code security analyzers as part of the CI/CD pipeline.



E.
  

Run a vulnerability security scanner as part of your continuous-integration /continuous-delivery (CI/CD)
pipeline.



https://docs.microsoft.com/en-us/vsts/articles/security-validation-cicd-pipeline?view=vsts

Your company's test suite is a custom C++ application that runs tests throughout each day on Linux virtual
machines. The full test suite takes several hours to complete, running on a limited number of on premises
servers reserved for testing. Your company wants to move the testing infrastructure to the cloud, to reduce the
amount of time it takes to fully test a change to the system, while changing the tests as little as possible. Which cloud infrastructure should you recommend?


A.

Google Compute Engine unmanaged instance groups and Network Load Balancer


B.

Google Compute Engine managed instance groups with auto-scaling


C.

Google Cloud Dataproc to run Apache Hadoop jobs to process each test


D.

Google App Engine with Google Stackdriver for logging





B.
  

Google Compute Engine managed instance groups with auto-scaling



https://cloud.google.com/compute/docs/instance-groups/


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