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About Google Professional Cloud Architect Exam!

Professional Cloud Architects enable organizations to leverage Google Cloud technologies. With a thorough understanding of cloud architecture and Google Cloud, they design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.

The Professional Cloud Architect certification exam assesses your ability to:

• Design and plan a cloud solution architecture
• Manage and provision the cloud solution infrastructure
• Design for security and compliance
• Analyze and optimize technical and business processes
• Manage implementations of cloud architecture
• Ensure solution and operations reliability

Certification Details

• Length: 2 hours
• Registration fee: $200 (plus tax where applicable)
• Languages: English, Japanese
• Exam format: 50-60 multiple-choice and multiple-select questions
• Case studies:

Each exam includes 2 case studies that describe fictitious business and solution concepts. Case study questions make up 20-30% of the exam and assess your ability to apply your knowledge to a realistic business situation. You can view the case studies on a split screen during the exam. See the Exam Guide for the 4 available case studies.

• Exam delivery method:  

1. Take the online-proctored exam from a remote location
2. Take the onsite-proctored exam at a testing center

• Prerequisites: None
• Recommended experience: 

3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud

Google Professional Cloud Architect Exam Course Content

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, modify, or deprecate
• 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 with respect to quotas and limits
• 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, databases)
• Choosing to 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 solutions with existing systems
• Migrating systems and data to support the solution
• Software license mapping
• Network planning
• Testing and proofs of concept
• Dependency management planning

1.5 Envisioning future solution improvements. Considerations include:

• Cloud and technology improvements
• Evolution of business needs
• Evangelism and advocacy

Section 2: Managing and provisioning a solution infrastructure

2.1 Configuring network topologies. Considerations include:

• Extending to on-premises environments (hybrid networking)
• Extending to a multi cloud environment that may include Google Cloud to Google Cloud communication
• Security protection (e.g. intrusion protection, access control, firewalls)

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 planning

2.3 Configuring compute systems. Considerations include:

• Compute resource provisioning
• Compute volatility configuration (preemptible vs. standard)
• Network configuration for computing resources (Google Compute Engine, Google Kubernetes Engine, server less networking)
• Infrastructure orchestration, resource configuration, and patch management
• Container orchestration

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, secret management)
• Separation of duties (SoD)
• Security controls (e.g., auditing, VPC Service Controls, context-aware access, organization policy)
• Managing customer-managed encryption keys with Cloud Key Management Service
• Remote access

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 technology and business processes

4.1 Analyzing and defining technical processes. Considerations include:

• Software development life cycle (SDLC)
• Continuous integration / continuous deployment
• Troubleshooting/root cause analysis best practices
• Testing and validation of software and infrastructure
• 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 processes
• Customer success management
• Cost optimization/resource optimization (capex / opex)

4.3 Developing procedures to ensure reliability of solutions in production (e.g., chaos engineering, penetration testing)

Section 5: Managing implementation

5.1 Advising development/operation teams to ensure successful deployment of the solution. Considerations include:

• Application development
• API best practices
• Testing frameworks (load/unit/integration)
• Data and system migration and management tooling

5.2 Interacting with Google Cloud programmatically. Considerations include:

• Google Cloud Shell
• Google Cloud SDK (gcloud, gsutil and bq)
• Cloud Emulators (e.g. Cloud Bigtable, Datastore, Spanner, Pub/Sub, Firestore)

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 deployed solutions

6.4 Evaluating quality control measures

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