GCP Professional Cloud Architect — Exam Guide Mapping to Prep links

Irrespective of what ever amount of preparation, a final check on whether we are good with respect to all exam guide points is something important to be ticked. Hence sharing this Cert Prep Map to Exam guide. In case you are looking at my complete- all in one guide for GCP PCA preparation, I got you already covered too here!

Hope this helps you connect the dots backwards and get even more confident to face the exam!

Professional Cloud Architect Certification Exam Guide | Google Cloud Certified

Module 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: Best practices for enterprise organizations, Implementing policies for customer use cases

· Cost optimization: Performance and cost optimization

· Supporting the application design: Google Cloud system design considerations

· Integration with external systems: Using APIs from an External Network

· Movement of data: Data lifecycle

· Build, buy, or modify, Success measurements (e.g., key performance indicators [KPI], return on investment [ROI], metrics):KPIs for APIs: How Metrics Change Over Time

· Compliance and observability: Security, privacy, and compliance

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

· High availability and failover design :Overview of the high availability configuration

· Elasticity of cloud resources with respect to quotas and limits: Working with quotas

· Scalability to meet growth requirements: Reliability

· Performance and latency: Performance and cost optimization

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

· Integration with on-premises/multi-cloud environments : Hybrid and multi-cloud architecture patterns

· Cloud-native networking (VPC, peering, firewalls, container networking): VPC network overview)

· Then, Selecting data processing technologies: Data processing, Dataflow, Dataproc

· Selecting appropriate storage types (e.g., object, file, RDBMS, NoSQL, NewSQL) : Google Cloud Databases

· Choosing to compute resources (e.g., preemptible, custom machine type, specialized workload): Compute, Creating a VM Instance with a custom machine type

· Mapping compute needs to platform products: Google Cloud products

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

• Integrating solution with existing systems : Migration to Google Cloud: Getting started
• Migrating systems and data to support the solution
• Licensing mapping : Bringing your own licenses
• Network planning : Best practices and reference architectures for VPC design, VPC network overview
• Testing and proof of concept : Running a hybrid render farm proof of concept
• Dependency management planning : Specifying Dependencies

1.5 Envisioning future solution improvements. Considerations include:

• Cloud and technology improvements : Google Cloud Improvements
• Then, Business needs evolution : Best practices for enterprise organizations, Google Cloud Improvements
• Evangelism and advocacy : API Team Best Practices: Developers, Evangelists, and Champions

Module 2. Managing and provisioning a solution Infrastructure

2.1 Configuring network topologies. Considerations include:

• Extending to on-premises (hybrid networking) : Extending On-Premises Network-Attached Storage to Cloud Storage with Komprise, Google Cloud Hybrid Connectivity
• Extending to a multi-cloud environment that may include GCP to GCP communication : Hybrid and multi-cloud architecture patterns
• Security and data protection : Data Protection

2.2 Configuring individual storage systems. Considerations include:

• Data storage allocation : Best practices for Cloud Storage
• Data processing/compute provisioning : Provisioning VMs on sole-tenant nodes, Data processing, Dataflow, Dataproc
• Security and access management : Identity and Access Management
• Network configuration for data transfer and latency : GCP network performance, Performance, and cost optimization
• Data retention and data life cycle management : Data lifecycle, Retention policies and retention policy locks
• Data growth management : Data lifecycle, Cloud storage growth

2.3 Configuring compute systems. Considerations include:

• Compute system provisioning : Provisioning VMs on sole-tenant nodes, Compute Engine
• Compute volatility configuration (preemptible vs. standard) : Preemptible VM instances, Creating and starting a preemptible VM instance
• Network configuration for compute resources /nodes (Google Compute Engine, Google Kubernetes Engine, serverless networking) : Sole-tenant nodes, Serverless NEGs
• Infrastructure orchestration, resource configuration, and patch management (e.g. Chef/Puppet/Ansible/Terraform/Deployment Manager) : Infrastructure as code
• Container orchestration with Kubernetes : Google Kubernetes Engine

Module 3. Designing for security and compliance

3.1 Designing for security. Considerations include:

• Identity and access management (IAM) : Identity and Access Management
• Resource hierarchy (organizations, folders, projects) : Resource hierarchy, Using resource hierarchy for access control
• Data security (key management, encryption) : Encryption at rest in Google Cloud
• Penetration testing : MPAA Compliance
• Separation of duties (SoD) : Separation of duties
• Security controls e.g., auditing, VPC Service Controls, context aware access, organization policy) : Overview of VPC Service Controls
• Managing customer-managed encryption keys with Cloud KMS : Customer-managed encryption keys (CMEK)

3.2 Designing for compliance. Considerations include:

• Legislation (e.g., health record privacy, children’s privacy, data privacy, and ownership) : Compliance resource center)
• Commercial (e.g., sensitive data such as credit card information handling, personally identifiable information [PII]) : Scan for sensitive data in just a few clicks, Take charge of your sensitive data with the Cloud Data Loss Prevention (DLP) API
• Industry certifications (e.g., SOC 2) : SOC 2
• Audits (including logs) : Cloud Audit Logs

Module 4: Analyzing and optimizing technology and business processes

4.1 Analyzing and defining technical processes. Considerations include:

• Software development life cycle plan (SDLC) , Continuous integration / continuous deployment : Setting up a CI/CD pipeline
• Troubleshooting/post mortem analysis culture : Postmortem Culture: Learning from Failure, Fearless shared postmortem
• Testing and validation : Validate Your Data, Testing Overview
• Service catalogue and provisioning : Provisioning Overview
• Business continuity and disaster recovery : Disaster recovery planning guide, Solving for business continuity

4.2 Analyzing and defining business processes. Considerations include:

• Stakeholder management (e.g. influencing and facilitation)
• Change management : Opening doors, embracing change with cloud data warehouses
• Team assessment/skills readiness : Migration to Google Cloud: Assessing and discovering your workloads
• Decision-making process
• Customer success management
• Cost optimization / resource optimization (Capex / Opex) : Cloud cost optimization, Cost Management

4.3 Developing procedures to ensure the resilience of solution in production (e.g., chaos engineering, penetration testing) : Patterns for scalable and resilient apps

Module 5: Managing implementation

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

• Application development : Application modernization, Application Development
• API best practices : API Key Best Practices
• Testing frameworks (load/unit/integration) : Testing Overview, test — Run gsutil unit/integration tests (for developers)
• Data and system migration tooling : Data center migration

5.2 Interacting with Google Cloud using GCP SDK (gcloud, gsutil, and bq). Considerations include:

• Local installation : Installing Google Cloud SDK)
• Google Cloud Shell : Google Cloud Shell documentation)
• Cloud Emulators (e.g. Cloud Bigtable, Datastore, Spanner, Pub/Sub, Firestore) : BT Emulator, Spanner Emulator , Datastore Emulator, PubSub Emulator

Module 6. Ensuring solution and operations reliability

· Monitoring/logging/profiling/alerting solution : Introduction to alerting, Alerting behavior

· Deployment and release management : Google Cloud Deployment Manager

· Assisting with the support of solutions in operation : Cloud Monitoring, Operations

· Evaluating quality control measures : Google security whitepaper

All details related to Booking/scheduling your exam, System Pre checks, Certification — Testing time, Extra tips, Post exam Certified notices etc. are already covered in my first blog of GCP — ACE. Do check out for all tips and tricks for GCP Exams!

Be sure to take a few minutes to explore these resources, and when you have time, dig deeper into a product that you’ve been wanting to learn more about.

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