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Google Professional Cloud Architect Prerequisites

There are no official prerequisites for taking the Professional Cloud Architect exam, except passing a single qualifying exam. However, it is recommended that the candidates have about three years of practical experience, including one year of designing and managing solutions with the help of Google Cloud Platform.

Exam Topics

The certification exam covers six domains. Each of them has a list of subtopics that the applicants should understand before taking the test. To develop competence in the content, it is recommended that you spend some time going over the exam guide and taking some practice tests. Below are the details of the subjects covered in the Google Professional Cloud Architect exam:

Designing & Planning Cloud Solution Architectures

• Envision future solutions enhancements: the individuals should understand the technology and Cloud improvements; evangelism and advocacy; business requirements evolution.
• Design network, compute, and storage resources: this covers one’s competence in selecting data processing technologies, relevant storage types, and compute resources; integration with multi-Cloud/on-premises environments; Cloud-native networking; mapping compute requirements for platform products;
• Create a migration plan: the students should be able to integrate the solution with current systems; migrate data and systems to support solutions; license mapping; test and proof concepts; network planning; dependency management strategy;
• Design a solution infrastructure that fulfills the business prerequisites: this covers skills in cost optimization; product strategy and business use cases; integration with the external systems; supporting application designs; build-buy-or-modify; design decision trade-off; data movement; observability and compliance; success measurements;
• Design a solution infrastructure that fulfills the technical prerequisites: the candidates must demonstrate their understanding of Cloud resources elasticity; failover design and high availability; latency and performance; scalability to fulfill growth needs;

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

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

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

Technical requirements considerations

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

Network, Storage, and Compute resources Considerations

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

Creating a migration plan

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

Envisioning future solution improvements

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

2. Managing and provisioning a solution Infrastructure

Configuring network topologies

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

Configuring individual storage systems

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

Configuring compute systems

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

3. Designing for security and compliance

Security considerations

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

compliance Considerations

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

4. Analyzing and optimizing technical and business processes

Analyzing and defining technical processes considerations

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

Analyzing and defining business processes. Considerations include:

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

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
• Application development
• Testing frameworks (load/unit/integration)

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

• Google Cloud Shell
• Local installation

6. Ensuring solution and operations reliability

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

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