What It Is to Be Google Professional Cloud Architect Certified?

Earning this certificate allows an individual to gain an expert-like understanding of concepts like building the cloud solution architecture and its end-to-end implementation, managing and provisioning the cloud solution infrastructure, and security & compliance of Google cloud.

Accredited professionals are well-versed in everything related to enterprise cloud strategy, architecture planning, and solution designing. They are known to be proficient in the development of methodologies and best practices that are needed for multiple cloud or hybrid environments.

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.

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

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1. Designing and planning a cloud solution architecture

Business requirements considerations

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

Technical requirements considerations

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

Network, Storage, and Compute resources Considerations

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

Creating a migration plan

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

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

Configuring individual storage systems

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

Configuring compute systems

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

3. Designing for security and compliance

Security considerations

• Managing customer- managed encryption keys with Cloud KMS
• Data security (key management, encryption)
• Identity and access management (IAM)
• Resource hierarchy (organizations, folders, projects)
• Separation of duties (SoD)
• 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)
• 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

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

Analyzing and defining business processes. Considerations include:

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

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

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

• Local installation
• Google Cloud Shell

6. Ensuring solution and operations reliability

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

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