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Exam Information
Official specifications published by Google
Exam Format
120 min
50-60
Not disclosed (pass/fail only; estimated ~70%)
Professional
Registration
$200 USD
Kryterion or online proctoring
English, Japanese
Validity
2 years
Take the renewal exam (1 hour, $100, starting 60 days before expiration); Retake the full standard exam
GCP-PCA Exam Topics and Domains
GCP-PCA is organized into 6 weighted domains. Expect to work with GKE, Cloud Build, Cloud Run, Cloud Storage, and more.
1
Designing and Planning a Cloud Solution Architecture
25%
Designing a solution infrastructure that meets business requirements
Business use cases and product strategyIdentifying functional and non-functional requirementsBusiness continuity planCost optimizationSupporting the application designIntegration patterns with external systemsMovement of dataDesign decision trade-offsWorkload disposition strategiesSuccess measurementsSecurity and complianceObservability
- Design cloud solution infrastructures that align with business use cases and product strategy
- Identify and balance functional and non-functional requirements
- Create business continuity plans with appropriate RPO/RTO targets
- Optimize costs while meeting business requirements
- Design integration patterns for external system connectivity
- Plan data movement strategies based on volume, velocity, and latency needs
- Evaluate design decision trade-offs and justify architectural choices
- Define success measurements using KPIs, ROI, and other metrics
Designing a solution infrastructure that meets technical requirements
Google Cloud Well-Architected FrameworkHigh availability and fail-over designFlexibility of cloud resourcesScalability to meet growth requirementsPerformance and latencyGemini Cloud AssistBackup and recovery
- Apply the Google Cloud Well-Architected Framework to solution design
- Design high-availability and failover architectures
- Plan for scalability and performance optimization
- Implement backup and recovery strategies
Designing network, storage, and compute resources
Integration with on-premises/multicloud environmentsGoogle Cloud AI and machine learning solutionsCloud-native networkingChoosing data processing solutionsChoosing appropriate storage typesMapping compute needs to platform productsChoosing compute resources
- Design hybrid and multicloud network architectures
- Select appropriate AI/ML services including Gemini and Vertex AI
- Design cloud-native network topologies using VPC, load balancers, and Private Service Connect
- Choose data processing, storage, and compute resources for specific use cases
Creating a migration plan
Integrating solutions with existing systemsAssessing and migrating systems and dataMigration methodologies and planningSoftware license implications and financial impact
- Create comprehensive migration plans with architectural diagrams
- Use Migration Center to assess and plan migrations
- Apply migration methodologies appropriate to workload types
- Evaluate software licensing and financial implications
Envisioning future solution improvements
Cloud and technology improvementsEvolution of business needsCloud-first design approach
- Design solutions that accommodate future technology and business evolution
- Apply cloud-first design principles
2
Managing and Provisioning a Solution Infrastructure
18%
Configuring network topologies
Extending to on-premises environments (hybrid networking)Extending to a multicloud environmentSecurity protectionVPC design and load balancing
- Configure hybrid networking solutions using Cloud Interconnect and VPN
- Design multicloud network architectures
- Implement network security with firewalls, Cloud Armor, and access controls
- Design VPC topologies and configure load balancing
Configuring individual storage systems
Data storage allocationData processing and compute provisioningSecurity and access management for storageConfiguration for data transfer and latencyData retention and data lifecycle managementData growth planningData protection
- Configure storage systems with appropriate classes and lifecycle policies
- Secure storage resources with IAM and encryption
- Plan for data growth and implement retention policies
- Configure data protection with backups and replication
Configuring compute systems
Compute resource provisioningCompute volatility configuration (spot vs. standard)Cloud-native network configuration for compute resourcesInfrastructure orchestration, resource configuration, and patch managementContainer orchestrationServerless computing
- Provision and configure compute resources on Compute Engine, GKE, and Cloud Run
- Configure networking for compute resources
- Manage infrastructure with IaC and automated patching
- Design container orchestration with GKE
Leveraging Vertex AI for end-to-end ML workflows
Using Vertex AI Pipelines to automate and orchestrate the ML lifecyclePreparing for Vertex AI data integrationUsing AI Hypercomputer
- Design end-to-end ML workflows using Vertex AI Pipelines
- Prepare data for ML using Vertex AI data integration tools
- Leverage AI Hypercomputer with GPUs and TPUs for large-scale AI workloads
Configuring prebuilt solutions or APIs with Vertex AI
Differentiating between Google AI APIsIntegrating Gemini Enterprise featuresIntegrating AI models from Model Garden
- Differentiate and select appropriate Google AI APIs
- Integrate Gemini Enterprise features including AI Agents and NotebookLM
- Deploy and integrate AI models from Model Garden
3
Designing for Security and Compliance
17%
Designing for security
Identity and Access Management (IAM)Resource hierarchyData securitySeparation of dutiesSecurity controlsManaging customer-managed encryption keys with Cloud KMSSecure remote accessSecuring software supply chainSecuring AI
- Design IAM policies following the principle of least privilege
- Implement data security with encryption and key management
- Configure security controls including VPC Service Controls and organization policies
- Implement secure remote access using IAP and Zero Trust principles
- Secure software supply chains and AI deployments
Designing for compliance
Legislation and regulationCommercial complianceIndustry certificationsAudits
- Design solutions that comply with relevant legislation and regulations
- Implement controls for handling sensitive commercial data
- Configure audit logging for compliance and governance
4
Analyzing and Optimizing Technical and Business Processes
15%
Analyzing and defining technical processes
Software development lifecycle (SDLC)Continuous integration / continuous deploymentTroubleshooting / root cause analysis best practicesTesting and validation of software and infrastructureService catalog and provisioningDisaster recovery
- Design CI/CD pipelines and deployment strategies
- Implement troubleshooting and root cause analysis processes
- Plan disaster recovery architectures with appropriate RPO/RTO
Analyzing and defining business processes
Stakeholder managementChange managementTeam assessment / skills readinessDecision-making processesCustomer success managementCost optimization / resource optimization (CapEx / OpEx)Business continuity
- Manage stakeholders and organizational change during cloud transformations
- Optimize costs and resources for cloud workloads
- Plan business continuity for cloud-based solutions
Developing procedures to ensure reliability of solutions in production
Chaos engineering and penetration testing
Develop procedures for ensuring production reliability through testing
5
Managing Implementation
13%
Advising development and operation teams to ensure successful deployment
Application and infrastructure deploymentAPI management best practicesTesting frameworksData and system migration and management toolingGemini Cloud Assist
- Advise teams on deployment best practices and tooling
- Implement API management with Apigee
- Select appropriate migration and testing tools
Interacting with Google Cloud programmatically
Cloud Shell Editor, Cloud Code, and Cloud Shell TerminalGoogle Cloud SDKsCloud EmulatorsInfrastructure as CodeGoogle API best practices and client libraries
- Use Google Cloud development tools and SDKs effectively
- Implement Infrastructure as Code with Terraform
- Develop with Google API client libraries following best practices
6
Ensuring Solution and Operations Excellence
12%
Understanding the operational excellence pillar of the Well-Architected Framework
Operational excellence principles and recommendations
Apply operational excellence principles from the Well-Architected Framework
Familiarity with Observability solutions
Monitoring and loggingProfiling and benchmarkingAlerting strategies
- Configure comprehensive observability with monitoring, logging, and alerting
- Use profiling and benchmarking to optimize performance
Deployment and release management
Deployment and release management strategies
Implement deployment and release management best practices
Assisting with the support of deployed solutions
Support processes for deployed solutions
Design support processes for deployed cloud solutions
Evaluating quality control measures
Quality control evaluation
Evaluate and implement quality control measures
Ensuring reliability of solutions in production
Chaos engineering, penetration testing, and load testing
Ensure production reliability through chaos engineering, penetration testing, and load testing
How do I earn this certification?
Passing GCP-PCA earns the Google Cloud Certified - Professional Cloud Architect certification. It sits in the Cloud Architecture track.
Next Level Options
- GCP-PDE - Professional Data EngineerComplementary data engineering skills for architects working with data-intensive solutions
- GCP-PMLE - Professional Machine Learning EngineerAI/ML specialization for architects designing AI-powered solutions
- GCP-PCSE - Professional Cloud Security EngineerDeep security specialization for architects handling sensitive/regulated workloads
- GCP-PCNE - Professional Cloud Network EngineerAdvanced networking for architects designing complex network topologies
- GCP-PCDE - Professional Cloud DevOps EngineerDevOps and SRE practices for architects focused on operational excellence
Alternative Paths
- GCP-PDBE - Professional Cloud Database EngineerDeep database design and management specialization for data-centric architects
- GCP-PCD - Professional Cloud DeveloperHands-on development focus for architects who build cloud-native applications
- GCP-PGWA - Professional Google Workspace Administrator For architects managing Google Workspace environments alongside Google Cloud
Practice with Precision
The PlanetCert Simulator mirrors the real exam environment with authentic questions and timed pressure.
How to study for this exam?
The most effective way to prepare for GCP-PCA is by using the PlanetCert Simulator to practice questions and review detailed explanations.
Who should take this exam?
- 3+ years of industry experience including 1+ years designing and managing solutions using Google Cloud
- Experience with common open-source technologies and software development methodologies
- Experience designing multi-tiered distributed applications across legacy, multicloud, or hybrid environments
- Familiarity with the Google Cloud Well-Architected Framework