Google Professional Cloud Architect (GCP) Practice Exam
Google Cloud Certified Professional Cloud Architect
About Google Cloud Certified Professional Cloud Architect
This exam objectively measures an individual’s ability to demonstrate the critical job skills for the role. To earn this certification you must pass the Professional Cloud Architect exam. The format is multiple choice and multiple select. The exam has no prerequisites. This exam must be taken in-person at one of our testing center locations. The certification helps to demonstrate your knowledge of designing, developing, and managing secure, robust, and dynamic solutions on GCP with the Google Cloud Professional Cloud Architect certification.
Exam Details
- Exam Name: Google Cloud Certified Professional Cloud Architect
- Exam Duration: 120 Minutes
- Exam Type: Multiple Choice Examination
- Eligibility/Pre-Requisite: None
- Validity: 2 Years
- Exam Languages: English and Japanese
Skills Measured
A Professional Cloud Architect enables organizations to leverage Google Cloud technologies. With a thorough understanding of cloud architecture and Google Cloud Platform, this individual can design, develop, and manage robust, secure, scalable, highly available, and dynamic solutions to drive business objectives.
Google Cloud Certified - Professional Cloud Architect exam assesses your ability to -
- Check Design and plan a cloud solution architecture
- Check Manage and provision the cloud solution infrastructure
- Check Design for security and compliance
- Check Analyze and optimize technical and business processes
- Check Manage implementations of cloud architecture
- Check Ensure solution and operations reliability
Exam Structure
The Google Professional Cloud Architect Exam covers the latest and updated exam topics -
Domain 1 - Designing and planning a cloud solution architecture (~30%)
1.1 Designing a solution infrastructure that meets business requirements. Considerations include:
- Business use cases and product strategy
- Business continuity plan
- Cost optimization
- Supporting the application design
- Integration patterns with external systems
- Movement of data
- Design decision trade-offs
- Workload disposition strategies (e.g., build, buy, modify, or deprecate)
- Success measurements (e.g., key performance indicators [KPI], return on investment [ROI], metrics)
- Security and Compliance
- Observability
1.2 Designing a solution infrastructure that meets technical requirements. Considerations include:
- High availability and failover design
- Flexibility of cloud resources
- Scalability to meet growth requirements
- Performance and latency
- Gemini Cloud Assist
- Backup and recovery
1.3 Designing network, storage, and compute resources. Considerations include:
- Integration with on-premises/multicloud environments
- Gemini Enterprise Agent Platform solutions (e.g., Gemini LLMs, Agent Builder, Model Garden, Gemini models)
- Cloud-native networking (e.g., VPC, peering, firewalls, container networking, shared VPC, PSC)
- Choosing data processing solutions
- Choosing appropriate storage types (e.g., object, file, databases)
- Mapping compute needs to platform products (e.g., Google Kubernetes Engine [GKE], Cloud Run, Cloud Run functions)
- Choosing compute resources (e.g., spot VMs, custom machine types, specialized workload)
1.4 Creating a migration plan (i.e., documents and architectural diagrams). Considerations include:
- Integrating solutions with existing systems
- Migrating systems and data to support the solution (e.g., Cloud bridge)
- Software license implications
- Network planning
- Testing and proofs of concept
- Dependency management planning
- Financial impact
1.5 Envisioning future solution improvements. Considerations include:
- Cloud and technology improvements
- Evolution of business needs
- Enablement and advocacy
Domain 2 - Managing and provisioning a solution infrastructure (~40%)
2.1 Configuring network topologies. Considerations include:
- Extending to on-premises environments (hybrid networking)
- Extending to a multicloud environment that may include Google Cloud to Google Cloud communication
- Security protection (e.g. intrusion protection, access control, firewalls)
- VPC design and load balancing (e.g., access to cloud, internet, and cloud adjacent services)
2.2 Configuring individual storage systems. Considerations include:
- Data storage allocation
- Data processing/compute provisioning
- Security and access management
- Configuration for data transfer and latency
- Data retention and data life cycle management
- Data growth planning
- Data protection (e.g., backup, recovery)
2.3 Configuring compute systems. Considerations include:
- Compute resource provisioning
- Compute volatility configuration (spot vs. standard)
- Cloud-native network configuration for compute resources (e.g., Google Compute Engine, GKE, serverless networking, VMware Engine)
- Infrastructure orchestration, resource configuration, and patch management
- Container orchestration
- Serverless computing
2.4 Monitoring, logging, profiling, and alerting solutions. Considerations include:
- Monitoring and logging
- Profiling and benchmarking
- Alerting strategies
Domain 3 - Designing for security and compliance (~20%)
3.1 Designing for security. Considerations include:
- Identity and access management (IAM)
- Resource hierarchy (organizations, folders, projects)
- Data security (key management, encryption, secret management)
- Separation of duties (SoD)
- Security controls (e.g., auditing, VPC Service Controls, context aware access, organization policy, hierarchical firewall policy)
- Managing customer-managed encryption keys with Cloud Key Management Service
- Remote access (e.g., IAP, service account impersonation, beyondcorp, RDP, oslogin (SSH), Workload identity federation)
- Securing software supply chain
- Gemini in Security
3.2 Designing for compliance. Considerations include:
- Legislation and regulation (e.g., health record privacy, children’s privacy, data privacy, ownership, data sovereignty)
- Commercial (e.g., sensitive data such as credit card information handling, personally identifiable information [PII])
- Industry certifications (e.g., SOC 2)
- Audits (including logs)
Domain 4 - Managing implementation (~10%)
4.1 Advising development and operations teams to ensure successful deployment of the solution. Considerations include:
- Application and infrastructure deployment
- API management best practices (e.g., Apigee)
- Testing frameworks (load/unit/integration)
- Data and system migration and management tooling
- Gemini Cloud Assist
4.2 Interacting with Google Cloud programmatically. Considerations include::
- Cloud Shell Editor, Cloud Code, and Cloud Shell Terminal
- Google Cloud SDK (e.g., gcloud, gsutil and bq)
- Gemini Code Assist
- Cloud Emulators (e.g. Bigtable, Spanner, Pub/Sub, Firestore)
- Infrastructure as code (e.g., IaC)
- Accessing Google API best practices
- Google API client libraries
What do we offer?
- Full-Length Mock Test with unique questions in each test set
- Practice objective questions with section-wise scores
- In-depth and exhaustive explanation for every question
- Reliable exam reports to evaluate strengths and weaknesses
- Latest Questions with an updated version
- Tips & Tricks to crack the test
- Unlimited access
What are our Practice Exams?
- Practice exams have been designed by professionals and domain experts that simulate real time exam scenario.
- Practice exam questions have been created on the basis of content outlined in the official documentation.
- Each set in the practice exam contains unique questions built with the intent to provide real-time experience to the candidates as well as gain more confidence during exam preparation.
- Practice exams help to self-evaluate against the exam content and work towards building strength to clear the exam.
- You can also create your own practice exam based on your choice and preference
