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

Technical requirements considerations

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

Network, Storage, and Compute resources Considerations

• Choosing data processing technologies
• Integration with on- premises/multi- cloud environments
• Choosing compute resources (e.g., preemptible, custom machine type, specialized workload)
• 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

Creating a migration plan

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

Envisioning future solution improvements

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

2. Managing and provisioning a solution Infrastructure

Configuring network topologies

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

Configuring individual storage systems

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

Configuring compute systems

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

3. Designing for security and compliance

Security considerations

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

compliance Considerations

• Audits (including logs)
• 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)

4. Analyzing and optimizing technical and business processes

Analyzing and defining technical processes considerations

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

Analyzing and defining business processes. Considerations include:

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

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

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

Exam Domains Overview

The entire syllabus is based on six domains and each tries to educate the learner about various Google Cloud technologies. They are disclosed below in detail:

Section #1. Designing and strategy-making for the Cloud Solution Architecture

Designing a Google Cloud solution as per business and technical needs, handling the cost optimization, data movement, observability, and compliance are some of the most talked-about topics under this module.

The applicants should also demonstrate their expertise regarding the concepts like architecting the storage, network, and compute solutions or resources, multi-cloud or on-premises integration, and fulfilling & monitoring the compute needs of the platform products, picking-up right data processing and related technologies.

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

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