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| Section | Objectives |
|---|---|
| Design for security and compliance | - Implement identity and access management (IAM) - Configure data protection and encryption |
| Design and plan a cloud solution architecture | - Plan security and compliance requirements - Design Google Cloud solutions based on business requirements - Design for reliability, scalability, and availability |
| Manage implementations of cloud architecture | - Ensure solution reliability and operational excellence - Manage deployment and production systems |
| Analyze and optimize technical and business processes | - Monitor, log, and optimize system performance - Optimize cost and resource usage |
| Manage and provision the solution infrastructure | - Automate infrastructure deployment - Provision compute, storage, and network resources |
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질문 # 134
During a high traffic portion of the day, one of your relational databases crashes, but the replica is never promoted to a master. You want to avoid this in the future.
What should you do?
정답：B
질문 # 135
You are migrating third-party applications from optimized on-premises virtual machines to Google Cloud. You are unsure about the optimum CPU and memory options. The application have a consistent usage patterns across multiple weeks. You want to optimize resource usage for the lowest cost. What should you do?
정답：A
설명：
Create a Compute engine instance with CPU and Memory options similar to your application's current on-premises virtual machine. Install the cloud monitoring agent, and deploy the third party application. Run a load with normal traffic levels on third party application and follow the Rightsizing Recommendations in the Cloud Console
https://cloud.google.com/migrate/compute-engine/docs/4.9/concepts/planning-a-migration/cloud-instance-rightsizing?hl=en
질문 # 136
Your company plans to migrate a multi-petabyte data set to the cloud. The data set must be available 24hrs a day. Your business analysts have experience only with using a SQL interface.
How should you store the data to optimize it for ease of analysis?
정답：D
설명：
Explanation
Explanation:
BigQuery is Google's serverless, highly scalable, low cost enterprise data warehouse designed to make all your data analysts productive. Because there is no infrastructure to manage, you can focus on analyzing data to find meaningful insights using familiar SQL and you don't need a database administrator.
BigQuery enables you to analyze all your data by creating a logical data warehouse over managed, columnar storage as well as data from object storage, and spreadsheets.
Reference: https://cloud.google.com/bigquery/
질문 # 137
Case Study: 13 - KnightMotives Automotive
Company Overview
KnightMotives is a car manufacturer specializing in autonomous, self-driving vehicles, including Battery Electric Vehicles (BEVs), hybrids and traditional internal combustion engine (ICE) vehicles. While KnightMotives has made strides with the in-vehicle experience in their BEV fleet, the hybrid and ICE vehicles have yet to implement these new systems and are viewed poorly by critics and drivers. The lack of modern in-vehicle technology in hybrid and ICE vehicles has resulted in declining sales and customer satisfaction.
KnightMotives wants to modernize the consumer experience across all vehicles within five years Artificial Intelligence offers a unique opportunity to revolutionize the in-vehicle experience, as well as the shopping buying and service/maintenance experience. Investment in this new technology will require a shift in financial priorities on a global scale.
KnightMotives also wants to improve their online ordering system, which is unreliable. Systems for customers to build their vehicle online for acquisition through a dealer are not delivering the data or reliability that dealers need, causing. A strain in the relationship between KnightMotives and dealers. Service technicians and sales staff need better tooling to enhance dealer successes, including built-to-order vehicles.
Solution Concept
KnightMotives wants to shift from manufacturing cars to creating a complete and compelling
"automotive experience." Then strategy prioritizes delivering a consistent experience across all models, developing AI-powered features, generating new revenue from data monetization, adopting a digital focus to differentiate their brand from competitors, and developing better tools for mechanics and salespeople.
Existing Technical Environment
KnightMotives's IT is largely on-premises with some applications on major cloud platforms. Their supply chain runs on an outdated mainframe, and Enterprise Resource Planning (ERP) is also outdated, making new promotions and dealer discounts difficult to implement. Dealers have no budget for new equipment. There is fragmentation across vehicles with multiple code bases, and significant technical debt from supporting backwards compatibility. Network connectivity to manufacturing plants and vehicle connectivity in rural areas are challenges.
Business Requirements
Key business requirements include fostering a personalized relationship with the driver and delivering a cohesive experience across all models. Creating a better build-to-order model will reduce time on the lot and provide transparency for both dealers and customers. Additionally, KnightMotives seeks to monetize corporate data to finance new technology investments, as their current AI infrastructure is obsolete and corporate data remains siloed. Security is a paramount concern due to past data breaches Adherence to European Union (EU) data protection regulations, especially for emerging autonomous platforms, is critical.
KnightMotives plans to make significant investments in fully autonomous driving capabilities, with initial implementation targeting regions with favorable regulatory environments. Prioritizing employee upskilling, attracting top-tier talent, and fostering better communication between business and technical teams are also critical objectives.
Technical Requirements
- Modernizing the in-vehicle experience includes developing a consistent user experience (UX)
that seamlessly integrates AI-powered features across all models, updating in-vehicle hardware and software in legacy models to support new UX features and AI capabilities, and ensuring reliable network connectivity, especially in rural areas, to support real-time AI features and data transmission.
- Network upgrades are necessary to support increased data traffic and improve connectivity
between plants and headquarters.
- IT infrastructure modernization requires adopting a hybrid cloud strategy to leverage the
benefits of both on-premises and cloud infrastructure, and gradually modernizing or replacing legacy systems to improve efficiency and agility.
- Autonomous vehicle development and testing requires investing in cutting-edge AI and machine
learning technologies, building a robust simulation environment, and ensuring compliance with evolving regulations related to autonomous vehicles.
- Data monetization and insights requires implementing a robust data management platform,
strict data security and privacy measures, and a scalable AI/ML infrastructure.
- Increased focus on security and risk management involves implementing a comprehensive
security framework to protect against cyber threats and data breaches, developing an incident response plan, and providing security awareness training to employees.
- Providing a delightful experience for dealers and customers requires improving the online build-
to-order system; developing modern dealer tools to streamline dealer operations, including sales, service, and inventory management; and implementing a comprehensive Customer Relationship Management (CRM) system to track customer interactions personalize experiences, and improve customer satisfaction.
Executive Statement
KnightMotives is committed to enhancing safety and saving lives by leveraging an extensive body of data - encompassing driving, road conditions, behavioral studies, and crash safety statistics - to create compelling digital experiences for drivers. Our AI consistently outperforms national safety statistics, ensuring the unique and coveted KnightMotives experience is aligned across all our vehicle models.
Michael Knight, KnightMotives CEO
For this question, refer to the KnightMotives Automotive case study. KnightMotives has developed and deployed a model on Vertex AI that can provide personalized recommendations in the new car configuration application. Customers will receive optional equipment recommendations that best suit their persona. Previous usage data from the car configuration application has been used for model training features. You know from past experience that customer behavior can change over time. For example, in times of economic certainty and rising stock markets, customers tend to purchase more expensive options. You want to detect when customer behavior gradually changes over time so you can adjust the model. What should you do?
정답：C
설명：
Prediction drift detection in Vertex AI Model Monitoring is designed to identify gradual changes in the distribution of incoming prediction features (and/or outputs) compared with a baseline, which is exactly what you need to catch shifts in customer behavior over time and trigger model review or retraining.
질문 # 138
For this question, refer to the EHR Healthcare case study. You are responsible for ensuring that EHR's use of Google Cloud will pass an upcoming privacy compliance audit. What should you do? (Choose two.)
정답：A,D
설명：
https://cloud.google.com/security/compliance/hipaa
질문 # 139
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