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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