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Recommended Experience

Officially, there are no prerequisites to be fulfilled before taking-up the Google Professional Cloud Architect exam. Anyone who wants to polish their knowledge of Google Cloud and aim at an architect role can apply for it.

However, it is recommended to have a minimum of 3+ years of industry experience before anyone enrolls in the test. These should also include 1+ years of experience in designing solutions as well as managing them using GCP. Such a base will make the exam journey a bit more simplified.

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Google Professional Cloud Architect Practice Test Questions, Google Professional Cloud Architect Exam Practice Test Questions

The Google Professional Cloud Architect certification equips the individuals with the ability to leverage Google Cloud technologies for their organizations. It offers the potential candidates an extensive understanding of Google Cloud Platform and Cloud architecture in general. Earning this certificate is a great way to grow your career in the ever-growing Cloud domain.

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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

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

Technical requirements considerations

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

Network, Storage, and Compute resources Considerations

• 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)
• Choosing appropriate storage types (e.g., object, file, RDBMS, NoSQL, NewSQL)
• Mapping compute needs to platform products
• Choosing data processing technologies

Creating a migration plan

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

Envisioning future solution improvements

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

2. Managing and provisioning a solution Infrastructure

Configuring network topologies

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

Configuring individual storage systems

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

Configuring compute systems

• Container orchestration with Kubernetes
• Compute system provisioning
• Compute volatility configuration (preemptible vs. standard)
• 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

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

compliance Considerations

• Legislation (e.g., health record privacy, children's privacy, data privacy, and ownership)
• Industry certifications (e.g., SOC 2)
• Audits (including logs)
• 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

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

Analyzing and defining business processes. Considerations include:

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

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

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

• Local installation
• Google Cloud Shell

6. Ensuring solution and operations reliability

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

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