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Google Professional-Cloud-Architect Exam Syllabus Topics:

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

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최신 Google Cloud Certified Professional-Cloud-Architect 무료샘플문제 (Q176-Q181):

질문 # 176
Case Study: 2 - TerramEarth Case Study
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.
Company Background
TerramEarth formed in 1946, when several small, family owned companies combined to retool after World War II. The company cares about their employees and customers and considers them to be extended members of their family.
TerramEarth is proud of their ability to innovate on their core products and find new markets as their customers' needs change. For the past 20 years trends in the industry have been largely toward increasing productivity by using larger vehicles with a human operator.
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-based systems that reside in a data center. These systems gzip CSV files from the field and upload via FTP, transform and aggregate them, 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, without
increasing the cost of carrying surplus inventory
- Support the dealer network with more data on how their customers use
their equipment IP 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
CEO Statement
We have been successful in capitalizing on the trend toward larger vehicles to increase the productivity of our customers. Technological change is occurring rapidly and TerramEarth has taken advantage of connected devices technology to provide our customers with better services, such as our intelligent farming equipment. With this technology, we have been able to increase farmers' yields by 25%, by using past trends to adjust how our vehicles operate. These advances have led to the rapid growth of our agricultural product line, which we expect will generate 50% of our revenues by 2020.
CTO Statement
Our competitive advantage has always been in the manufacturing process with our ability to build better vehicles for tower 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. Unfortunately, our CEO doesn't take technology obsolescence seriously and he considers the many new companies in our industry to be niche players. My goals are to build our skills while addressing immediate market needs through incremental innovations.
For this question, refer to the TerramEarth case study. TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US. Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles. You want to run this job on all the data. What is the most cost-effective way to run this job?

정답：C

설명：
Compressed Data save $$$
Region bucket cheaper than Multi Region
References: https://medium.com/google-cloud/google-cloud-storage-what-bucket-class-for-the- bestperformance-5c847ac8f9f2


질문 # 177
You set up an autoscaling instance group to serve web traffic for an upcoming launch. After configuring the instance group as a backend service to an HTTP(S) load balancer, you notice that virtual machine (VM) instances are being terminated and re-launched every minute. The instances do not have a public IP address. You have verified the appropriate web response is coming from each instance using the curl command. You want to ensure the backend is configured correctly. What should you do?

정답：A


질문 # 178
For this question, refer to the Dress4Win case study. Dress4Win is expected to grow to 10 times its size in 1 year with a corresponding growth in data and traffic that mirrors the existing patterns of usage. The CIO has set the target of migrating production infrastructure to the cloud within the next 6 months. How will you configure the solution to scale for this growth without making major application changes and still maximize the ROI?

정답：A


질문 # 179
For this question, refer to the EHR Healthcare case study. You are responsible for designing the Google Cloud network architecture for Google Kubernetes Engine. You want to follow Google best practices. Considering the EHR Healthcare business and technical requirements, what should you do to reduce the attack surface?

정답：D

설명：
https://cloud.google.com/kubernetes-engine/docs/concepts/private-cluster-concept#overview


질문 # 180
You have an outage in your Compute Engine managed instance group: all instance keep restarting after 5 seconds. You have a health check configured, but autoscaling is disabled. Your colleague, who is a Linux expert, offered to look into the issue. You need to make sure that he can access the VMs. What should you do?

정답：A

설명：
Explanation
https://cloud.google.com/compute/docs/instance-groups/autohealing-instances-in-migs Health checks used for autohealing should be conservative so they don't preemptively delete and recreate your instances. When an autohealer health check is too aggressive, the autohealer might mistake busy instances for failed instances and unnecessarily restart them, reducing availability


질문 # 181
......

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