What is the duration, language, and format of Google Professional Cloud Architect Exam
- Number of Questions: 50-60
- Format: Multiple choices, multiple answers
- Language: Google Professional Cloud Architect offered in English (U.S.), Japanese, Spanish, and Portuguese
- Length of Examination: 120 minutes
- Recommended experience: 3+ years of industry experience including 1+ years designing and managing solutions using GCP
- Passing score: 80%
Reference: https://cloud.google.com/certification/cloud-architect
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Getting Ready for the Exam
Following training courses is a great way to be exam-ready. Enrolling in the programs like Architecting with Google Cloud: Design and Process, Google Cloud Fundamentals: Core Infrastructure, and Architecting with Google Compute Engine will help you gain mastery over the test’s content.
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Google Professional Cloud Architect Prerequisites
There are no official prerequisites for taking the Professional Cloud Architect exam, except passing a single qualifying exam. However, it is recommended that the candidates have about three years of practical experience, including one year of designing and managing solutions with the help of Google Cloud Platform.
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Introduction to Google Professional Cloud Architect Exam
Google Professional Cloud Architect Exam is a certification exam that is conducted by Google to validates candidate knowledge and skills of working as a Professional Cloud Architect in the IT industry.
After passing this exam, candidates get a certificate from Google that helps them to demonstrate their proficiency in Google Professional Cloud Architect to their clients and employers.
Google Professional-Cloud-Architect Exam Syllabus Topics:
| Section | Objectives |
| Managing implementation | - Advising development/operation team(s) to ensure successful deployment
- 1. Deployment strategies
- 2. Testing and validation
- 3. Application development best practices
- Interacting with Google Cloud programmatically
- 1. APIs and client libraries
- 2. Infrastructure as Code (IaC)
- 3. Cloud SDK and gcloud CLI
|
| Ensuring solution and operations reliability | - Evaluating quality control measures
- Monitoring/logging/profiling/alerting solution
- 1. Cloud Monitoring and Cloud Logging
- 2. Performance profiling and tracing
- 3. Error reporting and alerting
- Deployment and release management
- 1. Deployment strategies and rollback
- 2. Release management and versioning
- Assisting with support
- 1. Capacity planning and scaling
- 2. Incident response and troubleshooting
|
| Managing and provisioning a solution infrastructure | - Configuring individual storage systems
- 1. Cloud Storage configuration
- 2. Cloud SQL and Spanner
- 3. Datastore and Bigtable
- Configuring network topologies
- 1. Private access and VPN configuration
- 2. VPC design and peering
- 3. Hybrid and multi-cloud connectivity
- Configuring compute systems
- 1. GKE configuration and management
- 2. Cloud Run and Cloud Functions
- 3. Compute Engine configuration
|
| Designing for security and compliance | - Designing for security
- 1. Network security
- 2. Application security
- 3. Data security and encryption
- 4. Identity and Access Management (IAM)
- Designing for compliance
- 1. Data residency and sovereignty
- 2. Regulatory and compliance requirements
- 3. Audit logging and monitoring
|
| Analyzing and optimizing technical and business processes | - Analyzing and defining business processes
- 1. Cost management and optimization
- 2. Stakeholder communication
- 3. Business KPIs and metrics
- Analyzing and defining technical processes
- 1. Software development lifecycle (SDLC)
- 2. Incident management and troubleshooting
- 3. CI/CD pipeline design
|
| Designing and planning a cloud solution architecture | - Designing solution infrastructure that meets business requirements
- 1. Migration planning
- 2. Data and storage architecture
- 3. Cost optimization
- 4. Networking and compute resources
- 5. Integration with existing systems
- 6. Business use cases and product strategy
- Creating a migration plan
- 1. Refactoring and rearchitecting applications
- 2. Planning data migration
- 3. Identifying workloads for migration
- Designing network, storage, and compute resources
- 1. Storage options and data lifecycle management
- 2. Compute engine selection and configuration
- 3. GKE cluster and workload design
- 4. Network design including load balancing and firewall rules
- Enabling future cloud technology
- 1. Implementing future-proof architectures
- 2. Designing for scalability and elasticity
|