Google : Professional-Cloud-Architect Questions & Answers

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

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

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

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

Creating a migration plan

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

Envisioning future solution improvements

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

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

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

Configuring compute systems

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

3. Designing for security and compliance

Security considerations

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

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)
• Business continuity and disaster recovery
• Continuous integration / continuous deployment
• Service catalog and provisioning
• Testing and validation

Analyzing and defining business processes. Considerations include:

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

• Application development
• API best practices
• Data and system migration tooling
• 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
• Assisting with the support of solutions in operation
• Deployment and release management
• Monitoring/logging/profiling/alerting solution

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

Section #6. Improving and validating the reliability of processes and solutions

The final exam domain is compact and throws light on concepts like deployment & release management, evaluations of quality control measures, monitoring and logging solutions, and helping users through deployed aids for the same.

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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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