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Professional-Cloud-Architect Practice Questions

Question # 1

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



Question # 2

You are developing an application using different microservices that should remain internal to the cluster. You want to be able to configure each microservice with a specific number of replicas. You also want to be able to address a specific microservice from any other microservice in a uniform way, regardless of the number of replicas the microservice scales to. You need to implement this solution on Google Kubernetes Engine. What should you do?

A.

Deploy each microservice as a Deployment. Expose the Deployment in the cluster using a Service, and use the Service DNS name to address it from other microservices within the cluster.

B.

Deploy each microservice as a Deployment. Expose the Deployment in the cluster using an Ingress, and use the Ingress IP address to address the Deployment from other microservices within the cluster.

C.

Deploy each microservice as a Pod. Expose the Pod in the cluster using a Service, and use the Service DNS name to address the microservice from other microservices within the cluster.

D.

Deploy each microservice as a Pod. Expose the Pod in the cluster using an Ingress, and use the Ingress IP address name to address the Pod from other microservices within the cluster.



A.

Deploy each microservice as a Deployment. Expose the Deployment in the cluster using a Service, and use the Service DNS name to address it from other microservices within the cluster.


Explanation: https://kubernetes.io/docs/concepts/services-networking/ingress/



Question # 3

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?

A.

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

B.

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

C.

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

D.

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



C.

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




Question # 4

For this question, refer to the Mountkirk Games case study. You need to analyze and define the technical
architecture for the database workloads for your company, Mountkirk Games. Considering the business and technical requirements, what should you do?

A.

Use Cloud SQL for time series data, and use Cloud Bigtable for historical data queries.

B.

Use Cloud SQL to replace MySQL, and use Cloud Spanner for historical data queries.

C.

Use Cloud Bigtable to replace MySQL, and use BigQuery for historical data queries.

D.

Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery
for historical data queries.



D.

Use Cloud Bigtable for time series data, use Cloud Spanner for transactional data, and use BigQuery
for historical data queries.




Question # 5

You are implementing a single Cloud SQL MySQL second-generation database that contains business-critical transaction data. You want to ensure that the minimum amount of data is lost in case of catastrophic failure. Which two features should you implement? (Choose two.)

A.

Sharding

B.

Read replicas

C.

Binary logging

D.

Automated backups

E.

Semisynchronous replication



C.

Binary logging


D.

Automated backups


Explanation:
Backups help you restore lost data to your Cloud SQL instance. Additionally, if an instance
is having a problem, you can restore it to a previous state by using the backup to overwrite
it. Enable automated backups for any instance that contains necessary data. Backups
protect your data from loss or damage.
Enabling automated backups, along with binary logging, is also required for some
operations, such as clone and replica creation.
Reference: https://cloud.google.com/sql/docs/mysql/backup-recovery/backups



Question # 6

Your organization has a 3-tier web application deployed in the same network on Google Cloud Platform. Each
tier (web, API, and database) scales independently of the others Network traffic should flow through the web
to the API tier and then on to the database tier. Traffic should not flow between the web and the database tier.
How should you configure the network?

A.

Add each tier to a different subnetwork.

B.

Set up software based firewalls on individual VMs.

C.

Add tags to each tier and set up routes to allow the desired traffic flow.

D.

Add tags to each tier and set up firewall rules to allow the desired traffic flow.



D.

Add tags to each tier and set up firewall rules to allow the desired traffic flow.


https://aws.amazon.com/blogs/aws/building-three-tier-architectures-with-security-groups/



Question # 7

For this question, refer to the Dress4Win case study. Dress4Win is expected to grow to 10 times its size in 1 year with a corresponding growth in data and traffic that mirrors the existing patterns of usage. The CIO has set the target of migrating production infrastructure to the cloud within the next 6 months. How will you
configure the solution to scale for this growth without making major application changes and still maximize
the ROI?

A.

Migrate the web application layer to App Engine, and MySQL to Cloud Datastore, and NAS to Cloud
Storage. Deploy RabbitMQ, and deploy Hadoop servers using Deployment Manager.

B.

Migrate RabbitMQ to Cloud Pub/Sub, Hadoop to BigQuery, and NAS to Compute Engine with
Persistent Disk storage. Deploy Tomcat, and deploy Nginx using Deployment Manager.
ge

C.

Implement managed instance groups for Tomcat and Nginx. Migrate MySQL to Cloud SQL, RabbitMQ
to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Compute Engine with Persistent Disk
storage.

D.

Implement managed instance groups for the Tomcat and Nginx. Migrate MySQL to Cloud SQL,
RabbitMQ to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Cloud Stora



C.

Implement managed instance groups for Tomcat and Nginx. Migrate MySQL to Cloud SQL, RabbitMQ
to Cloud Pub/Sub, Hadoop to Cloud Dataproc, and NAS to Compute Engine with Persistent Disk
storage.




Question # 8

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?

A.

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

B.

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

C.

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

D.

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



B.

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




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