CLOUD ARCHITECT

Certification Exam Guide

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.

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.

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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

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