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Google Professional Cloud Professional Cloud Architect

March 21, 2018 by admin

Sample Case Study
During the exam for the Cloud Architect Certification, some of the questions may refer you to a case study that describes a fictitious business and solution concept. These case studies are intended to provide additional context to help you choose your answer(s). Review some sample case studies that may be used in the exam.

JencoMart
Mountkirk Games
Dress4Win
TerramEarth

Job Role Description
A Google Certified Professional – Cloud Architect enables organizations to leverage Google Cloud technologies. Through an understanding of cloud architecture and Google technology, this individual designs, develops, and manages robust, secure, scalable, highly available, and dynamic solutions to drive business objectives. The Cloud Architect should be proficient in all aspects of solution development including implementation details, developing prototypes, and architectural best practices. The Cloud Architect should also be experienced in microservices and multi-tiered distributed applications which span multi-cloud or hybrid environments. Architect 3

Certification Exam Guide
Section 1: Designing and planning a cloud solution architecture

1.1 Designing a solution infrastructure that meets business requirements. Considerations include:
business use cases and product strategy
cost optimization
supporting the application design
integration
movement of data
tradeoffs
build, buy or modify
success measurements (e.g., Key Performance Indicators (KPI), Return on Investment (ROI), metrics)

1.2 Designing a solution infrastructure that meets technical requirements. Considerations include:
high availability and failover design
elasticity of cloud resources
scalability to meet growth requirements

1.3 Designing network, storage, and compute resources. Considerations include:
integration with on premises/multi-cloud environments
identification of data storage needs and mapping to storage systems
data flow diagrams
storage system structure (e.g., Object, File, RDBMS, NoSQL, New SQL)
mapping compute needs to platform products

1.4 Creating a migration plan (i.e., documents and architectural diagrams). Considerations include:
integrating solution with existing systems
migrating systems and data to support the solution
licensing mapping
network and management planning
testing and proof-of-concept

1.5 Envisioning future solution improvements. Considerations include:
cloud and technology improvements
business needs evolution
evangelism and advocacy

Section 2: Managing and provisioning solution Infrastructure

2.1 Configuring network topologies. Considerations include:
extending to on-premises (hybrid networking)
extending to a multi-cloud environment
security
data protection

2.2 Configuring individual storage systems. Considerations include:
data storage allocation
data processing/compute provisioning
security and access management
network configuration for data transfer and latency
data retention and data lifecycle management
data growth management

2.3 Configuring compute systems. Considerations include:
compute system provisioning
compute volatility configuration (preemptible vs. standard)
network configuration for compute nodes
orchestration technology configuration (e.g. Chef/Puppet/Kubernetes)

Section 3: Designing for security and compliance

3.1 Designing for security. Considerations include:
Identity and Access Management (IAM)
data security
penetration testing
Separation of Duties (SoD)
security controls

3.2 Designing for legal compliance. Considerations include:
legislation (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children’s Online Privacy Protection Act (COPPA), etc.)
audits
certification (e.g., Information Technology Infrastructure Library (ITIL) framework)

Section 4: Analyzing and optimizing technical and business processes

4.1 Analyzing and defining technical processes. Considerations include:
Software Development Lifecycle Plan (SDLC)
continuous integration / continuous deployment
troubleshooting / post mortem analysis culture
testing and validation
IT enterprise process (e.g. ITIL)
business continuity and disaster recovery

4.2 Analyzing and defining business processes. Considerations include:
stakeholder management (e.g. Influencing and facilitation)
change management
decision making process
customer success management

4.3 Developing procedures to test resilience of solution in production (e.g., DiRT and Chaos Monkey)

Section 5: Managing implementation

5.1 Advising development/operation team(s) to ensure successful deployment of the solution. Considerations include:
application development
API best practices
testing frameworks (load/unit/integration)
data and system migration tooling

5.2 Reading and writing application development languages. At a minimum, languages include:
Java
Python

Section 6: Ensuring solution and operations reliability
6.1 Monitoring/Logging/Alerting solution
6.2 Deployment and release management
6.3 Supporting operational troubleshooting
6.4 Evaluating quality control measures

QUESTION 1 – (Topic 1)
For this question, refer to the Mountkirk Games case study.
Mountkirk Games’ gaming servers are not automatically scaling properly. Last month, they rolled out a new feature, which suddenly became very popular. A record number of users are trying to use the service, but many of them are getting 503 errors and very slow response times. What should they investigate first?

A. Verify that the database is online.
B. Verify that the project quota hasn’t been exceeded.
C. Verify that the new feature code did not introduce any performance bugs.
D. Verify that the load-testing team is not running their tool against production.

Answer: B

QUESTION 2 – (Topic 1)
For this question, refer to the Mountkirk Games case study. Mountkirk Games has deployed their new backend on Google Cloud Platform (GCP). You want to create a thorough
testing process for new versions of the backend before they are released to the public. You want the testing environment to scale in an economical way.

How should you design the process?
A. Create a scalable environment in GCP for simulating production load.
B. Use the existing infrastructure to test the GCP-based backend at scale.
C. Build stress tests into each component of your application using resources internal to GCP to simulate load.
D. Create a set of static environments in GCP to test different levels of load — for example, high, medium, and low.

Answer: D

QUESTION 3 – (Topic 1)
For this question, refer to the Mountkirk Games case study.
Mountkirk Games wants you to design their new testing strategy. How should the test coverage differ from their existing backends on the other platforms?

A. Tests should scale well beyond the prior approaches.
B. Unit tests are no longer required, only end-to-end tests.
C. Tests should be applied after the release is in the production environment.
D. Tests should include directly testing the Google Cloud Platform (GCP) infrastructure.

Answer: D

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