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Topics of Google Professional Cloud Architect Exam

Candidates must know the exam topics before they start of preparation. because it will really help them in hitting the core. Our Google Professional Cloud Architect Dumps will include the following topics:

1. Designing and planning a cloud solution architecture

Business requirements considerations

• Compliance and observability
• Success measurements (e.g., key performance indicators [KPI], return on investment [ROI], metrics)
• Movement of data
• Integration with external systems
• Design decision trade-offs
• Build, buy or modify
• Supporting the application design
• Cost optimization
• Business use cases and product strategy

Technical requirements considerations

• High availability and failover design
• Performance and latency
• Scalability to meet growth requirements
• Elasticity of cloud resources

Network, Storage, and Compute resources Considerations

• Choosing appropriate storage types (e.g., object, file, RDBMS, NoSQL, NewSQL)
• Mapping compute needs to platform products
• Choosing data processing technologies
• Choosing compute resources (e.g., preemptible, custom machine type, specialized workload)
• Integration with on- premises/multi- cloud environments
• Cloud-native networking (VPC, peering, firewalls, container networking)

Creating a migration plan

• Dependency management planning
• Testing and proof of concept
• Licensing mapping
• Integrating solution with existing systems
• Network planning
• Migrating systems and data to support the solution

Envisioning future solution improvements

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

2. Managing and provisioning a solution Infrastructure

Configuring network topologies

• Extending to on-premises (hybrid networking)
• Extending to a multi-cloud environment that may include GCP to GCP communication
• Security and data protection

Configuring individual storage systems

• Data storage allocation
• Network configuration for data transfer and latency
• Data growth management
• Security and access management
• Data retention and data life cycle management
• Data processing/compute provisioning

Configuring compute systems

• Infrastructure provisioning technology configuration (e.g. Chef/Puppet/Ansible/Terraform/Deployment Manager)
• Compute system provisioning
• Compute volatility configuration (preemptible vs. standard)
• Container orchestration with Kubernetes
• Network configuration for compute nodes

3. Designing for security and compliance

Security considerations

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

compliance Considerations

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

4. Analyzing and optimizing technical and business processes

Analyzing and defining technical processes considerations

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

Analyzing and defining business processes. Considerations include:

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

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

5. Managing implementation

Advising development/operation team(s) to ensure successful deployment of the solution. considerations

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

Interacting with Google Cloud using GCP SDK (gcloud, gsutil, and bq) considerations

• Local installation
• Google Cloud Shell

6. Ensuring solution and operations reliability

• Assisting with the support of solutions in operation
• Monitoring/logging/profiling/alerting solution
• Deployment and release management
• Evaluating quality control measures

Reference: https://cloud.google.com/certification/cloud-architect

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