PROFESSIONAL-CLOUD-ARCHITECT Practice Test Questions

Topic 4, Dress4Win case study

Company Overview
Dress4win is a web-based company that helps their users organize and manage their personal wardrobe using a
website and mobile application. The company also cultivates an active social network that connects their users
with designers and retailers. They monetize their services through advertising, e-commerce, referrals, and a
freemium app model.
Company Background
Dress4win’s application has grown from a few servers in the founder’s garage to several hundred servers and
appliances in a colocated data center. However, the capacity of their infrastructure is now insufficient for the
application’s rapid growth. Because of this growth and the company’s desire to innovate faster, Dress4win is
committing to a full migration to a public cloud.
Solution Concept
For the first phase of their migration to the cloud, Dress4win is considering moving their development and test
environments. They are also considering building a disaster recovery site, because their current infrastructure
is at a single location. They are not sure which components of their architecture they can migrate as is and
which components they need to change before migrating them.
Existing Technical Environment
The Dress4win application is served out of a single data center location.
Databases:
MySQL - user data, inventory, static data
Redis - metadata, social graph, caching
Application servers:
Tomcat - Java micro-services
Nginx - static content
Apache Beam - Batch processing
Storage appliances:
iSCSI for VM hosts
Fiber channel SAN - MySQL databases
NAS - image storage, logs, backups
Apache Hadoop/Spark servers:
Data analysis
Real-time trending calculations
MQ servers:
Messaging
Social notifications
Events
Miscellaneous servers:
Jenkins, monitoring, bastion hosts, security scanners
Business Requirements
Build a reliable and reproducible environment with scaled parity of production.
Improve security by defining and adhering to a set of security and Identity and Access Management
(IAM) best practices for cloud.
Improve business agility and speed of innovation through rapid provisioning of new resources.
Analyze and optimize architecture for performance in the cloud.
Migrate fully to the cloud if all other requirements are met.
Technical Requirements
Evaluate and choose an automation framework for provisioning resources in cloud.
Support failover of the production environment to cloud during an emergency.
Identify production services that can migrate to cloud to save capacity.
Use managed services whenever possible.
Encrypt data on the wire and at rest.
Support multiple VPN connections between the production data center and cloud environment.
CEO Statement
Our investors are concerned about our ability to scale and contain costs with our current infrastructure. They
are also concerned that a new competitor could use a public cloud platform to offset their up-front investment
and freeing them to focus on developing better features.
CTO Statement
We have invested heavily in the current infrastructure, but much of the equipment is approaching the end of its
useful life. We are consistently waiting weeks for new gear to be racked before we can start new projects. Our
traffic patterns are highest in the mornings and weekend evenings; during other times, 80% of our capacity is
sitting idle.
CFO Statement
Our capital expenditure is now exceeding our quarterly projections. Migrating to the cloud will likely cause an
initial increase in spending, but we expect to fully transition before our next hardware refresh cycle. Our total
cost of ownership (TCO) analysis over the next 5 years puts a cloud strategy between 30 to 50% lower than
our current model.

For this question, refer to the Dress4Win case study.
The Dress4Win security team has disabled external SSH access into production virtual machines (VMs) on Google Cloud Platform (GCP). The operations team needs to remotely manage the VMs, build and push Docker containers, and manage Google Cloud Storage objects. What can they do?

Grant the operations engineers access to use Google Cloud Shell.

Configure a VPN connection to GCP to allow SSH access to the cloud VMs.

Develop a new access request process that grants temporary SSH access to cloud VMs when an
operations engineer needs to perform a task.

Have the development team build an API service that allows the operations team to execute specific
remote procedure calls to accomplish their tasks

Configure a VPN connection to GCP to allow SSH access to the cloud VMs.

The current Dress4win system architecture has high latency to some customers because it is located in one
data center.
As of a future evaluation and optimizing for performance in the cloud, Dresss4win wants to distribute it's
system
architecture to multiple locations when Google cloud platform.
Which approach should they use?

Use regional managed instance groups and a global load balancer to increase performance because the
regional managed instance group can grow instances in each region separately based on traffic.

Use a global load balancer with a set of virtual machines that forward the requests to a closer group of
virtual machines managed by your operations team.

Use regional managed instance groups and a global load balancer to increase reliability by providing
automatic failover between zones in different regions.

Use a global load balancer with a set of virtual machines that forward the requests to a closer group of
virtual machines as part of a separate managed instance groups

For this question, refer to the Dress4Win case study.
Dress4Win has configured a new uptime check with Google Stackdriver for several of their legacy services.
The Stackdriver dashboard is not reporting the services as healthy. What should they do?

Install the Stackdriver agent on all of the legacy web servers.

In the Cloud Platform Console download the list of the uptime servers' IP addresses and create an
inbound firewall rule

Configure their load balancer to pass through the User-Agent HTTP header when the value matches
GoogleStackdriverMonitoring-UptimeChecks (https://cloud.google.com/monitoring)

Configure their legacy web servers to allow requests that contain user-Agent HTTP header when the
value matches GoogleStackdriverMonitoring— UptimeChecks (https://cloud.google.com/monitoring)

For this question, refer to the Dress4Win case study.
As part of their new application experience, Dress4Wm allows customers to upload images of themselves. The
customer has exclusive control over who may view these images. Customers should be able to upload images
with minimal latency and also be shown their images quickly on the main application page when they log in.
Which configuration should Dress4Win use?

Store image files in a Google Cloud Storage bucket. Use Google Cloud Datastore to maintain metadata
that maps each customer's ID and their image files.

Store image files in a Google Cloud Storage bucket. Add custom metadata to the uploaded images in
Cloud Storage that contains the customer's unique ID.

Use a distributed file system to store customers' images. As storage needs increase, add more persistent
disks and/or nodes. Assign each customer a unique ID, which sets each file's owner attribute, ensuring
privacy of images.

Use a distributed file system to store customers' images. As storage needs increase, add more persistent
disks and/or nodes. Use a Google Cloud SQL database to maintain metadata that maps each customer's
ID to their image files

Store image files in a Google Cloud Storage bucket. Use Google Cloud Datastore to maintain metadata
that maps each customer's ID and their image files.

Dress4win has end to end tests covering 100% of their endpoints.
They want to ensure that the move of cloud does not introduce any new bugs.
Which additional testing methods should the developers employ to prevent an outage?

They should run the end to end tests in the cloud staging environment to determine if the code is
working as intended.

They should enable google stack driver debugger on the application code to show errors in the code

They should add additional unit tests and production scale load tests on their cloud staging environment.

They should add canary tests so developers can measure how much of an impact the new release causes
to latency

They should enable google stack driver debugger on the application code to show errors in the code

For this question, refer to the Dress4Win case study.
As part of Dress4Win's plans to migrate to the cloud, they want to be able to set up a managed logging and
monitoring system so they can handle spikes in their traffic load. They want to ensure that:
• The infrastructure can be notified when it needs to scale up and down to handle the ebb and flow of usage
throughout the day
• Their administrators are notified automatically when their application reports errors.
• They can filter their aggregated logs down in order to debug one piece of the application across many hosts
Which Google StackDriver features should they use?

Logging, Alerts, Insights, Debug

Monitoring, Trace, Debug, Logging

Monitoring, Logging, Alerts, Error Reporting

Monitoring, Logging, Debug, Error Report

Monitoring, Trace, Debug, Logging

For this question, refer to the Dress4Win case study.
At Dress4Win, an operations engineer wants to create a tow-cost solution to remotely archive copies of
database backup files. The database files are compressed tar files stored in their current data center. How
should he proceed?

Create a cron script using gsutil to copy the files to a Coldline Storage bucket.

Create a cron script using gsutil to copy the files to a Regional Storage bucket.

Create a Cloud Storage Transfer Service Job to copy the files to a Coldline Storage bucket.

Create a Cloud Storage Transfer Service job to copy the files to a Regional Storage bucket.

Create a cron script using gsutil to copy the files to a Coldline Storage bucket.

Follow these rules of thumb when deciding whether to use gsutil or Storage Transfer Service:
When transferring data from an on-premises location, use gsutil.
When transferring data from another cloud storage provider, use Storage Transfer Service.
Otherwise, evaluate both tools with respect to your specific scenario.
Use this guidance as a starting point. The specific details of your transfer scenario will also help you determine
which tool is more appropriate

For this question, refer to the Dress4Win case study.
Dress4Win has asked you to recommend machine types they should deploy their application servers to. How
should you proceed?

Perform a mapping of the on-premises physical hardware cores and RAM to the nearest machine types
in the cloud.

Recommend that Dress4Win deploy application servers to machine types that offer the highest RAM to
CPU ratio available.

Recommend that Dress4Win deploy into production with the smallest instances available, monitor them
over time, and scale the machine type up until the desired performance is reached.

Identify the number of virtual cores and RAM associated with the application server virtual machines
align them to a custom machine type in the cloud, monitor performance, and scale the machine types up
until the desired performance is reached.

Perform a mapping of the on-premises physical hardware cores and RAM to the nearest machine types
in the cloud.

For this question, refer to the Dress4Win case study.
You want to ensure Dress4Win's sales and tax records remain available for infrequent viewing by auditors for at least 10 years. Cost optimization is your top priority. Which cloud services should you choose?

Google Cloud Storage Coldline to store the data, and gsutil to access the data.

Google Cloud Storage Nearline to store the data, and gsutil to access the data.

Google Bigtabte with US or EU as location to store the data, and gcloud to access the data.

BigQuery to store the data, and a web server cluster in a managed instance group to access the data.
Google Cloud SQL mirrored across two distinct regions to store the data, and a Redis cluster in a
managed instance group to access the data.

Google Cloud Storage Coldline to store the data, and gsutil to access the data.

References: https://cloud.google.com/storage/docs/storage-classes

For this question, refer to the Dress4Win case study.
Dress4Win has end-to-end tests covering 100% of their endpoints. They want to ensure that the move to the cloud does not introduce any new bugs. Which additional testing methods should the developers employ to prevent an outage?

They should enable Google Stackdriver Debugger on the application code to show errors in the code.

They should add additional unit tests and production scale load tests on their cloud staging environment.

They should run the end-to-end tests in the cloud staging environment to determine if the code is
working as intended.

They should add canary tests so developers can measure how much of an impact the new release causes
to latency.

They should add additional unit tests and production scale load tests on their cloud staging environment.

For this question, refer to the Dress4Win case study.
Dress4Win would like to become familiar with deploying applications to the cloud by successfully deploying some applications quickly, as is. They have asked for your recommendation. What should you advise?

Identify self-contained applications with external dependencies as a first move to the cloud.

Identify enterprise applications with internal dependencies and recommend these as a first move to the
cloud.

Suggest moving their in-house databases to the cloud and continue serving requests to on-premise
applications.

Recommend moving their message queuing servers to the cloud and continue handling requests to
on-premise applications.

Suggest moving their in-house databases to the cloud and continue serving requests to on-premise
applications.

You need to reduce the number of unplanned rollbacks of erroneous production deployments in your
company's web hosting platform. Improvement to the QA/Test processes accomplished an 80% reduction. Which additional two approaches can you take to further reduce the rollbacks? Choose 2 answers

Introduce a green-blue deployment model.

Replace the QA environment with canary releases.

Fragment the monolithic platform into microservices.

Reduce the platform's dependency on relational database systems.

Replace the platform's relational database systems with a NoSQL database

Introduce a green-blue deployment model.

Fragment the monolithic platform into microservices.

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