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

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

Technical requirements considerations

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

Network, Storage, and Compute resources Considerations

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

Creating a migration plan

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

Envisioning future solution improvements

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

2. Managing and provisioning a solution Infrastructure

Configuring network topologies

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

Configuring individual storage systems

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

Configuring compute systems

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

3. Designing for security and compliance

Security considerations

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

compliance Considerations

• 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])
• Audits (including logs)
• Industry certifications (e.g., SOC 2)

4. Analyzing and optimizing technical and business processes

Analyzing and defining technical processes considerations

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

Analyzing and defining business processes. Considerations include:

• Cost optimization / resource optimization (capex / opex)
• Customer success management
• Decision- making process
• Team assessment / skills readiness
• 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

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

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

• Google Cloud Shell
• Local installation

6. Ensuring solution and operations reliability

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

Prerequisites

The recommended industry experience for the potential candidates is at least three years and an additional one year of experience in designing and managing solutions with the use of GCP. You must also understand the content of the corresponding exam before sitting for it. It is also recommended that you have expertise in software development methodologies as well as different approaches such as multi-tiered distributed applications for hybrid and multi-Cloud environments.

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

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