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

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

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

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.

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

You want to enable your running Google Container Engine cluster to scale as demand for your application changes. What should you do?

A.

Option A

B.

Option B

C.

Option C

D.

Option D

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

The database administration team has asked you to help them improve the performance of their new database
server running on Google Compute Engine. The database is for importing and normalizing their performance
statistics and is built with MySQL running on Debian Linux. They have an n1-standard-8 virtual machine with 80 GB of SSD persistent disk. What should they change to get better performance from this system?

A.

Increase the virtual machine's memory to 64 GB.

B.

Create a new virtual machine running PostgreSQL.

C.

Dynamically resize the SSD persistent disk to 500 GB.

D.

Migrate their performance metrics warehouse to BigQuery.

E.

Modify all of their batch jobs to use bulk inserts into the database.

Your organization requires that metrics from all applications be retained for 5 years for future analysis in
possible legal proceedings. Which approach should you use?

A.

Grant the security team access to the logs in each Project.

B.

Configure Stackdriver Monitoring for all Projects, and export to BigQuery.

C.

Configure Stackdriver Monitoring for all Projects with the default retention policies.

D.

Configure Stackdriver Monitoring for all Projects, and export to Google Cloud Storage.

For this question, refer to the Dress4Win case study. Which of the compute services should be migrated as –is  and would still be an optimized architecture for performance in the cloud?

A.

Web applications deployed using App Engine standard environment

B.

RabbitMQ deployed using an unmanaged instance group

C.

Hadoop/Spark deployed using Cloud Dataproc Regional in High Availability mode

D.

Jenkins, monitoring, bastion hosts, security scanners services deployed on custom machine types