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Google Professional-Cloud-Architect Exam Syllabus Topics:

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

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Google Certified Professional - Cloud Architect (GCP) Sample Questions (Q273-Q278):

NEW QUESTION # 273
For this question, refer to the Dress4Win case study. Considering the given business requirements, how would you automate the deployment of web and transactional data layers?

Answer: B

Explanation:
Topic 7, TerramEarth Case 2
Company Overview
TerramEarth manufactures heavy equipment for the mining and agricultural industries. About 80% of their business is from mining and 20% from agriculture. They currently have over 500 dealers and service centers in 100 countries. Their mission is to build products that make their customers more productive.
Solution Concept
There are 20 million TerramEarth vehicles in operation that collect 120 fields of data per second. Data is stored locally on the vehicle and can be accessed for analysis when a vehicle is serviced. The data is downloaded via a maintenance port. This same port can be used to adjust operational parameters, allowing the vehicles to be upgraded in the field with new computing modules.
Approximately 200,000 vehicles are connected to a cellular network, allowing TerramEarth to collect data directly. At a rate of 120 fields of data per second with 22 hours of operation per day, TerramEarth collects a total of about 9 TB/day from these connected vehicles.
Existing Technical Environment
TerramEarth's existing architecture is composed of Linux and Windows-based systems that reside in a single U.S. west coast based data center. These systems gzip CSV files from the field and upload via FTP, and place the data in their data warehouse. Because this process takes time, aggregated reports are based on data that is 3 weeks old.
With this data, TerramEarth has been able to preemptively stock replacement parts and reduce unplanned downtime of their vehicles by 60%. However, because the data is stale, some customers are without their vehicles for up to 4 weeks while they wait for replacement parts.
Business Requirements
Decrease unplanned vehicle downtime to less than 1 week.
Support the dealer network with more data on how their customers use their equipment to better position new products and services Have the ability to partner with different companies - especially with seed and fertilizer suppliers in the fast-growing agricultural business - to create compelling joint offerings for their customers.
Technical Requirements
Expand beyond a single datacenter to decrease latency to the American Midwest and east coast.
Create a backup strategy.
Increase security of data transfer from equipment to the datacenter.
Improve data in the data warehouse.
Use customer and equipment data to anticipate customer needs.
Application 1: Data ingest
A custom Python application reads uploaded datafiles from a single server, writes to the data warehouse.
Compute:
Windows Server 2008 R2
- 16 CPUs
- 128 GB of RAM
- 10 TB local HDD storage
Application 2: Reporting
An off the shelf application that business analysts use to run a daily report to see what equipment needs repair. Only 2 analysts of a team of 10 (5 west coast, 5 east coast) can connect to the reporting application at a time.
Compute:
Off the shelf application. License tied to number of physical CPUs
- Windows Server 2008 R2
- 16 CPUs
- 32 GB of RAM
- 500 GB HDD
Data warehouse:
A single PostgreSQL server
- RedHat Linux
- 64 CPUs
- 128 GB of RAM
- 4x 6TB HDD in RAID 0
Executive Statement
Our competitive advantage has always been in the manufacturing process, with our ability to build better vehicles for lower cost than our competitors. However, new products with different approaches are constantly being developed, and I'm concerned that we lack the skills to undergo the next wave of transformations in our industry. My goals are to build our skills while addressing immediate market needs through incremental innovations.


NEW QUESTION # 274
Your architecture calls for the centralized collection of all admin activity and VM system logs within your project.
How should you collect these logs from both VMs and services?

Answer: A

Explanation:
Explanation
https://cloud.google.com/logging/docs/agent/default-logs


NEW QUESTION # 275
You want to establish a Compute Engine application in a single VPC across two regions. The application must communicate over VPN to an on-premises network. How should you deploy the VPN?

Answer: A


NEW QUESTION # 276
Your company runs a critical, revenue-generating ecommerce application that is served by a regional managed instance group (MIG) behind an external HTTP(S) Load Balancer. The operations team is currently overwhelmed with low-priority notifications. Your team ' s service level objective (SLO) is to maintain 99.9% availability. You want to minimize noise from non-critical events and ensure that the team is only notified of issues that are actionable and threaten the SLO. What should you do?

Answer: D

Explanation:
According to the Google SRE Handbook , modern monitoring should focus on Symptom-based alerting rather than Cause-based alerting. Option A (Cause-based) leads to " alert fatigue " because high CPU or memory usage may not actually be impacting the user experience if the application is still responding successfully.
The most effective way to protect a 99.9% availability SLO is to use Error Budgets and Burn Rate Alerting
. An error budget is the amount of unreliability your service can tolerate (0.1% for a 99.9% SLO).
By implementing an alert that triggers when the burn rate is high enough to exhaust the budget within 24 hours (Option C), the team is only " paged " for significant, persistent issues that actually threaten the business goal. Smaller, momentary spikes that don ' t meaningfully impact the long-term SLO can be addressed during normal business hours as " low-priority tickets. " This approach significantly reduces noise, improves the signal- to-noise ratio, and ensures that when the team is notified, the issue is critical and requires immediate action to preserve revenue and customer trust.


NEW QUESTION # 277
Your organization has decided to restrict the use of external IP addresses on instances to only approved instances. You want to enforce this requirement across all of your Virtual Private Clouds (VPCs). What should you do?

Answer: A


NEW QUESTION # 278
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