Certification-Exam-Guide.md

Professional Cloud Architect

Certification Exam Guide

Section 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

  • What does success look like qualitatively

• cost optimization

  • A separate step after business logic criteria are met

• supporting the application design

  • What procedures and processes will be needed?

• integration

  • Working with existing systems in parallel at first? Are there parts that must remain on premises?

• movement of data

  • How and when will the data migrate to the new solutions?

• tradeoffs

  • Priorities. Timing can be critical to value.

• build, buy or modify

  • Control vs. overhead vs. time

• success measurements (e.g., Key Performance Indicators (KPI), Return on Investment (ROI), metrics)

  • What does success look like quantitatively?

• Compliance and observability

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

• high availability and failover design

  • What are the real criteria?

  • What are the measurable goals?

• elasticity of cloud resources

  • How do you want the solution to behave when busy? How will the system behave when under attack? How will it behave when traffic diminishes?

• scalability to meet growth requirements

  • Scaling for growth is different from autoscaling to cover temporary demand non-linearities. When is it time to add a node, upgrade a service, or switch services?

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

• integration with on premises/multi-cloud environments

  • When to use gsutil, gsutil rsync, and Storage Transfer Service

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

  • Understand all the networking services and how to connect for throughput, security, billing, and so forth.

• identification of data processing pipeline
• matching data characteristics to storage systems

  • Velocity(how frequent), Volume(how much), Variety(format, structure), Volatility(how often does it change) -- which services match?

• data flow diagrams

  • Very helpful to know where the data will travel through the solution and to look for bottlenecks and flow monitoring and control

• storage system structure (e.g., Object, File, RDBMS, NoSQL, NewSQL)

  • ACID(Atomicity, Consistency, Isolation, Durability) - What is eventual consistency? BASE(Basically Available, soft state, eventual consistency). Structure requirements?

• mapping compute needs to platform products

  • Scale, capacity, control/overhead?

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

• integrating solution with existing systems

  • Parallel?

• migrating systems and data to support the solution

  • How much, how to synchronize in both directions? Where is the source of data truth?

• licensing mapping

  • Data center license to cloud license -- may have different license or requirements for licensed software.

• network and management planning

  • How will on premises connect to the cloud solution?

• testing and proof-of-concept

  • Different ways to divide a test audience: random, group, phased, test.

1.5 Envisioning future solution improvements. Considerations include:

• cloud and technology improvements

  • When the technology improves, how will the solution embrace the improvements?

• business needs evolution

  • When the business changes, how will the solution change? Most solutions don't just need to work once, they need to become self-sustaining.

• evangelism and advocacy

  • Who are the gatekeepers and what do they need to know to effectively do their jobs?

Section 2: Managing and provisioning solution Infrastructure

2.1 Configuring network topologies. Considerations include:

• extending to on-premise (hybrid networking)

  • VPN. Interconnect.

• extending to a multi-cloud environment which may include GCP to GCP communication

  • Interoperation interface. Stackdriver(GCP + AWS)

• security
• data protection

  • Encryption, access, CSEK, KMS

2.2 Configuring individual storage systems. Considerations include:

• data storage allocation

  • Where will the data be located? Resiliency? Change?

• data processing/compute provisioning

  • Which Platform? What capacity?

• security and access management

  • CSEK and Cloud Storage, for example.

• network configuration for data transfer and latency

  • Location makes a difference in egress charges and round-trip time.

• data retention and data lifecycle management

  • What is the Nearline and Coldline policy? When to delete data?

• data growth management

  • When do you need a different way to organize the data? How much/how big will the current design support?

2.3 Configuring compute systems. Considerations include:

• compute system provisioning

  • Speed, throughput, capacity, burstiness? Turn off when not in use?

• compute volatility configuration (preemptible vs. standard)

  • Stateful vs. Stateless. Tolerance for lost data/state

• network configuration for compute nodes

  • Firewall rules, load balancing, NAT, VPN

• infrastructure provisioning technology configuration (e.g. Chef/Puppet/Ansible/Terraform)

  • Deployment Manager...others. The value of self-documenting and automated orchestration of infrastructure.

• container orchestration (e.g. Kubernetes)

  • The value of container-based development: portability, scalability, fault isolation, platform agnostic deployment, CI/CD development methods

Section 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)
• penetration testing
• Separation of Duties (SoD)
• security controls
• Managing customer-supplied encryption keys with Cloud KMS

3.2 Designing for legal compliance. Considerations include:

• legislation (e.g., Health Insurance Portability and Accountability Act (HIPAA), Children’s Online Privacy Protection Act (COPPA), etc.)
• audits (including logs)
• certification (e.g., Information Technology Infrastructure Library (ITIL) framework)

Section 4: Analyzing and optimizing technical and business processes

4.1 Analyzing and defining technical processes. Considerations include:

• Software Development Lifecycle Plan (SDLC)
• continuous integration / continuous deployment
• troubleshooting / post mortem analysis culture
• testing and validation
• IT enterprise process (e.g. ITIL)
• 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 process
• customer success management
• cost optimization / resource optimization (Capex / Opex)

4.3 Developing procedures to test resilience of solution in production (e.g., DiRT and Simian Army)

Section 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 tooling

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

• local installation
• Google Cloud Shell

Section 6: Ensuring solution and operations reliability

6.1 Monitoring/Logging/Alerting solution

6.2 Deployment and release management

6.3 Supporting operational troubleshooting

6.4 Evaluating quality control measures