#2. Google Professional Cloud Architect (GCP) Certification

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700+ Q&A with explanation based on Google Professional Cloud Architect (GCP) Certification. Review yourself before Exam.

#2. Google Professional Cloud Architect (GCP) Certification

700+ Q&A with explanation based on Google Professional Cloud Architect (GCP) Certification. Review yourself before Exam..

This is the 2nd Practice set about Google Professional Cloud Architect (GCP).

Professional Cloud Architect

     A Professional Cloud Architect enables organizations to     leverage Google Cloud technologies. With a thorough     understanding of cloud architecture and Google Cloud Platform,     this individual can design, develop, and manage robust, secure, scalable, highly available, and     dynamic solutions to drive business objectives.   

About this certification exam

• Length: 2 hours     

• Registration fee: $200       (plus tax where applicable)     

• Languages: English, Japanese.     

1. Designing and planning a cloud solution architecture

•    

       1.1 Designing a solution infrastructure that meets business requirements. Considerations     include:   

  •        Business use cases and product strategy     

  •        Cost optimization     

  •        Supporting the application design     

  •        Integration with external systems     

  •        Movement of data     

  •        Design decision trade-offs     

  •        Build, buy, modify, or deprecate     

  •        Success measurements (e.g., key performance indicators [KPI], return on investment [ROI],       metrics)     

  •        Compliance and observability     

  1.2 Designing a solution infrastructure that meets technical requirements. Considerations     include:

  •        High availability and failover design     

  •        Elasticity of cloud resources with respect to quotas and limits     

  •        Scalability to meet growth requirements     

  •        Performance and latency     

  1.3 Designing network, storage, and compute resources. Considerations include:

  •        Integration with on-premises/multi-cloud environments     

  •        Cloud-native networking (VPC, peering, firewalls, container networking)     

  •        Choosing data processing technologies     

  •        Choosing appropriate storage types (e.g., object, file, databases)     

  •        Choosing compute resources (e.g., preemptible, custom machine type, specialized workload)     

  •        Mapping compute needs to platform products     

  1.4 Creating a migration plan (i.e., documents and architectural diagrams). Considerations     include:

  •        Integrating solutions with existing systems     

  •        Migrating systems and data to support the solution     

  •        Software license mapping     

  •        Network planning     

  •        Testing and proofs of concept     

  •        Dependency management planning     

  1.5 Envisioning future solution improvements. Considerations include:

  •        Cloud and technology improvements     

  •        Evolution of business needs     

  •        Evangelism and advocacy     

2. Managing and provisioning a solution infrastructure

•    

  2.1 Configuring network topologies. Considerations include:

  •        Extending to on-premises environments (hybrid networking)     

  •        Extending to a multi-cloud environment that may include Google Cloud  to Google Cloud       communication     

  •        Security protection (e.g. intrusion protection, access control, firewalls)     

  2.2 Configuring individual storage systems. Considerations include:

  •        Data storage allocation     

  •        Data processing/compute provisioning     

  •        Security and access management     

  •        Network configuration for data transfer and latency     

  •        Data retention and data life cycle management     

  •        Data growth planning     

  2.3 Configuring compute systems. Considerations include:

  •        Compute resource provisioning     

  •        Compute volatility configuration (preemptible vs. standard)     

  •        Network configuration for compute resources (Google Compute Engine, Google Kubernetes Engine,       serverless networking)     

  •        Infrastructure orchestration, resource configuration, and patch management     

  •        Container orchestration     

3. Designing for security and compliance

•    

  3.1 Designing for security. Considerations include:

  •        Identity and access management (IAM)     

  •        Resource hierarchy (organizations, folders, projects)     

  •        Data security (key management, encryption, secret management)     

  •        Separation of duties (SoD)     

  •        Security controls (e.g., auditing, VPC Service Controls, context aware access, organization       policy)     

  •        Managing customer-managed encryption keys with Cloud Key Management Service     

  •        Remote access     

  3.2 Designing for compliance. Considerations include:

  •        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)     

  •        Audits (including logs)     

4. Analyzing and optimizing technical and business processes

•    

  4.1 Analyzing and defining technical processes. Considerations include:

  •        Software development life cycle (SDLC)     

  •        Continuous integration / continuous deployment

  •        Troubleshooting / root cause analysis best practices

  •        Testing and validation of software and infrastructure     

  •        Service catalog and provisioning     

  •        Business continuity and disaster recovery     

  4.2 Analyzing and defining business processes. Considerations include:

  •        Stakeholder management (e.g. influencing and facilitation)     

  •        Change management     

  •        Team assessment / skills readiness     

  •        Decision-making processes     

  •        Customer success management     

  •        Cost optimization / resource optimization (capex / opex)     

  4.3 Developing procedures to ensure reliability of solutions in production (e.g., chaos     engineering, penetration testing)

5. Managing implementation

•    

  5.1 Advising development/operation team(s) to ensure successful deployment of the solution.     Considerations include:

  •        Application development     

  •        API best practices     

  •        Testing frameworks (load/unit/integration)     

  •        Data and system migration and management tooling     

  5.2 Interacting with Google Cloud programmatically. Considerations include:

  •        Google Cloud Shell     

  •        Google Cloud SDK (gcloud, gsutil and bq)     

  •        Cloud Emulators (e.g. Cloud Bigtable, Datastore, Spanner, Pub/Sub, Firestore)     

6. Ensuring solution and operations reliability

6.1 Monitoring/logging/profiling/alerting solution

6.2 Deployment and release management

6.3 Assisting with the support of deployed solutions

6.4 Evaluating quality control measures

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