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Google Professional-Cloud-Architect Exam Syllabus Topics:

SectionObjectives
Topic 1: Designing for security and compliance- Designing for security
  • 1. Identity and Access Management (IAM)
  • 2. Application security
  • 3. Data security and encryption
  • 4. Network security
- Designing for compliance
  • 1. Regulatory and compliance requirements
  • 2. Data residency and sovereignty
  • 3. Audit logging and monitoring
Topic 2: Ensuring solution and operations reliability- Evaluating quality control measures
- Deployment and release management
  • 1. Release management and versioning
  • 2. Deployment strategies and rollback
- Monitoring/logging/profiling/alerting solution
  • 1. Performance profiling and tracing
  • 2. Cloud Monitoring and Cloud Logging
  • 3. Error reporting and alerting
- Assisting with support
  • 1. Incident response and troubleshooting
  • 2. Capacity planning and scaling
Topic 3: Managing implementation- Interacting with Google Cloud programmatically
  • 1. Infrastructure as Code (IaC)
  • 2. APIs and client libraries
  • 3. Cloud SDK and gcloud CLI
- Advising development/operation team(s) to ensure successful deployment
  • 1. Application development best practices
  • 2. Testing and validation
  • 3. Deployment strategies
Topic 4: Managing and provisioning a solution infrastructure- Configuring network topologies
  • 1. Hybrid and multi-cloud connectivity
  • 2. Private access and VPN configuration
  • 3. VPC design and peering
- Configuring compute systems
  • 1. Compute Engine configuration
  • 2. GKE configuration and management
  • 3. Cloud Run and Cloud Functions
- Configuring individual storage systems
  • 1. Datastore and Bigtable
  • 2. Cloud Storage configuration
  • 3. Cloud SQL and Spanner
Topic 5: Analyzing and optimizing technical and business processes- Analyzing and defining technical processes
  • 1. Incident management and troubleshooting
  • 2. Software development lifecycle (SDLC)
  • 3. CI/CD pipeline design
- Analyzing and defining business processes
  • 1. Business KPIs and metrics
  • 2. Cost management and optimization
  • 3. Stakeholder communication
Topic 6: Designing and planning a cloud solution architecture- Designing network, storage, and compute resources
  • 1. Compute engine selection and configuration
  • 2. Network design including load balancing and firewall rules
  • 3. GKE cluster and workload design
  • 4. Storage options and data lifecycle management
- Creating a migration plan
  • 1. Identifying workloads for migration
  • 2. Refactoring and rearchitecting applications
  • 3. Planning data migration
- Designing solution infrastructure that meets business requirements
  • 1. Integration with existing systems
  • 2. Business use cases and product strategy
  • 3. Data and storage architecture
  • 4. Networking and compute resources
  • 5. Cost optimization
  • 6. Migration planning
- Enabling future cloud technology
  • 1. Designing for scalability and elasticity
  • 2. Implementing future-proof architectures

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q193-Q198):

NEW QUESTION # 193
You want to allow your operations learn to store togs from all the production protects in your Organization, without during logs from other projects All of the production projects are contained in a folder. You want to ensure that all logs for existing and new production projects are captured automatically. What should you do?

Answer: B

Explanation:
An aggregated export is a type of sink that combines and routes log entries from the Google Cloud resources contained by an organization or folder1. By creating an aggregated export on the Production folder, you can capture all the logs from the existing and new production projects in that folder automatically1.
A log sink is a destination for log entries that match a filter1. By setting the log sink to be a Cloud Storage bucket in an operations project, you can store the log entries in Cloud Storage and allow your operations team to access them1.


NEW QUESTION # 194
Your company creates rendering software which users can download from the company website.
Your company has customers all over the world. You want to minimize latency for all your customers. You want to follow Google-recommended practices. How should you store the files?

Answer: B

Explanation:
Multi-Region buckets will persist data only in the regions of a continent, e.g. Europe. If you want to store in GCS globally, you'll need to create separate buckets for the continents and sync the data across them.


NEW QUESTION # 195
You are designing the storage architecture for a financial analytics platform. The platform ingests and stores terabytes of transactional data daily, which is used for both real-time fraud detection and long-term historical analysis. Transaction data from the last 30 days must be accessible with very low latency for the fraud detection engine. Data older than 30 days is accessed infrequently for quarterly reports, where retrieval times of a few seconds are acceptable. All data must be retained for five years to meet compliance regulations. You need to design a solution as cost-effective as possible. What should you do?

Answer: C

Explanation:
According to Google Cloud Storage documentation , the choice of storage class depends on the access frequency and retention period.
For the first 30 days, data requires " very low latency, " making Standard Storage necessary. For data older than 30 days that is accessed for " quarterly reports " (roughly every 90 days) where " retrieval times of a few seconds " are acceptable, Coldline Storage is the most cost-effective choice. Coldline is designed for data accessed at most once a quarter. Transitioning to Archive (Option C) would be too aggressive, as Archive is intended for data accessed less than once a year and may have higher retrieval costs. Option B (BigQuery) is excellent for analytics but can be significantly more expensive than Cloud Storage for simple long-term retention of terabytes of raw transaction data. Object Lifecycle Management automates this transition, ensuring cost-efficiency over the 5-year compliance window.


NEW QUESTION # 196
For this question, refer to the TerramEarth case study. To be compliant with European GDPR regulation, TerramEarth is required to delete data generated from its European customers after a period of 36 months when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and BigQuery. What should you do?

Answer: A

Explanation:
https://cloud.google.com/bigquery/docs/managing-partitioned-tables#partition-expiration
https://cloud.google.com/storage/docs/lifecycle


NEW QUESTION # 197
You are designing a new insurance claims processing application that will be deployed on Google Kubernetes Engine (GKE). Your company ' s compliance team requires a complete and non-repudiable audit trail for all administrative actions from day one. Your application must capture who deploys a new container image, who modifies the GKE cluster ' s configuration, and who interacts with running pods or Kubernetes secrets using kubectl. What should you do?

Answer: C

Explanation:
According to GKE Security documentation , Kubernetes API Server Audit Logging is the primary source of truth for administrative actions within a cluster. This feature captures every call made to the API server, including those made via kubectl, the Cloud Console, or automated controllers.
By enabling GKE Audit Logging and ensuring Cloud Audit Logs (specifically Admin Activity and Data Access logs) are active, you fulfill the requirement for a non-repudiable trail. This log will contain:
* Who: The identity of the caller (the IAM user or service account).
* What: The action taken (e.g., create pod, get secret, patch deployment).
* When: The timestamp of the operation.
Option A (Binary Authorization) is a preventative control, not an audit logging tool. Option C (Security Command Center) is for threat detection, not for maintaining a raw audit trail. Option D (DaemonSet) collects application logs from within containers, but cannot capture administrative API calls like " modifying cluster configuration " or " accessing secrets " made through the Kubernetes control plane.


NEW QUESTION # 198
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