Google Cloud - Professional Cloud Architect

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 with external systems
• Movement of data
• Design decision trade-offs
• Build, buy, or modify
• Success measurements (e.g., key performance indicators [KPI], return on investment [ROI], metrics)
• Compliance and observability

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
• Performance and latency

1.3 Designing network, storage, and compute resources. Considerations include:

• Integration with on-premises/multi-cloud environments
• Cloud-native networking (VPC, peering, firewalls, container networking)
• Choosing data processing technologies
• Choosing appropriate storage types (e.g., object, file, RDBMS, NoSQL, NewSQL)
• Choosing compute resources (e.g., preemptible, custom machine type, specialized workload)
• 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 planning
• Testing and proof of concept
• Dependency management planning

1.5 Envisioning future solution improvements. Considerations include:

• Cloud and technology improvements
• Business needs evolution
• Evangelism and advocacy

Section 2: Managing and provisioning a solution Infrastructure

2.1 Configuring network topologies. Considerations include:

• Extending to on-premises (hybrid networking)
• Extending to a multi-cloud environment that may include GCP to GCP communication
• Security and 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 life cycle 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
• Infrastructure provisioning technology configuration (e.g. Chef/Puppet/Ansible/Terraform/Deployment Manager)
• Container orchestration with Kubernetes

Section 3: Designing for security and compliance

3.1 Designing for security. Considerations include:

• Identity and access management (IAM)
• Resource hierarchy (organizations, folders, projects)
• Data security (key management, encryption)
• Penetration testing
• Separation of duties (SoD)
• Security controls (e.g., auditing, VPC Service Controls, organization policy)
• Managing customer-managed encryption keys with Cloud KMS

3.2 Designing for compliance. Considerations include:

• Legislation (e.g., health record privacy, children’s privacy, data privacy, and ownership)
• Commercial (e.g., sensitive data such as credit card information handling, personally identifiable information [PII])
• Industry certifications (e.g., SOC 2)
• Audits (including logs)

Section 4: Analyzing and optimizing technical and business processes

4.1 Analyzing and defining technical processes. Considerations include:

• Software development life cycle plan (SDLC)
• Continuous integration / continuous deployment
• Troubleshooting / post mortem analysis culture
• Testing and validation
• Service catalog and provisioning
• Business continuity and disaster recovery

4.2 Analyzing and defining business processes. Considerations include:

• Stakeholder management (e.g. influencing and facilitation)
• Change management
• Team assessment / skills readiness
• Decision-making process
• Customer success management
• Cost optimization / resource optimization (capex / opex)

4.3 Developing procedures to ensure resilience of solution in production (e.g., chaos engineering)

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 Interacting with Google Cloud using GCP SDK (gcloud, gsutil, and bq). Considerations include:

• Local installation
• Google Cloud Shell

Section 6: Ensuring solution and operations reliability

6.1 Monitoring/logging/profiling/alerting solution

6.2 Deployment and release management

6.3 Assisting with the support of solutions in operation

6.4 Evaluating quality control measures

• Pricing: $200 USD (In India $120; for other countries it may vary.)
• Time: 2 hours
• Question types: There are three types of questions on the examination
  • Multiple choice: Has one correct response and three incorrect responses
  • Multiple select: Has two or more correct responses out of given options
  • Sample Case Studies: Case studies with single choice or multi choice questions
• Available at: remotely (@home or office) or in person at Kryterion Testing Centers.