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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

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

Technical requirements considerations

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

Network, Storage, and Compute resources Considerations

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

Creating a migration plan

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

• 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

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

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

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

compliance Considerations

• Commercial (e.g., sensitive data such as credit card information handling, personally identifiable information [PII])
• Industry certifications (e.g., SOC 2)
• Legislation (e.g., health record privacy, children's privacy, data privacy, and ownership)
• Audits (including logs)

4. Analyzing and optimizing technical and business processes

Analyzing and defining technical processes considerations

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

Analyzing and defining business processes. Considerations include:

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

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)
• Data and system migration tooling
• Application development
• API best practices

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

• Local installation
• Google Cloud Shell

6. Ensuring solution and operations reliability

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

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

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Then, candidates can use different books, like the following:

• Google Cloud Certified Professional Cloud Architect (3rd Edition) by Soumen Chatterjee
• The Ultimate Guide for Beginners [Google Cloud Platform] by Adney Ainsley
• Professional Cloud Architect – Google Cloud Certification Guide written by Konrad Clapa & Brian Gerrard

All of them are available on Amazon and throw light on major Google Cloud concepts. They allow one to not just learn all the topics but also understand how to solve real-world tasks related to the implementation of GCP. Various scenarios explained and questions for self-assessment are included too.

To familiarize the applicants with daily issues the professionals face in the workplace, the vendor has provided some detailed case studies to refer to. These relate to Mountkirk Games, Dress4Win, and TerramEarth. Finally, one can join an on-demand webinar “Architecting Hybrid Cloud Infrastructure with Anthos” that provides valuable exam tips.

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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