You are deploying a PHP App Engine Standard service with SQL as the backend. You want to minimize the number of queries to the database. What should you do?

Case Study: 10 - EHR Healthcare
Company overview
EHR Healthcare is a leading provider of electronic health record software to the medical industry.
EHR Healthcare provides their software as a service to multi-national medical offices, hospitals, and insurance providers.
Solution concept
Due to rapid changes in the healthcare and insurance industry, EHR Healthcare's business has been growing exponentially year over year. They need to be able to scale their environment, adapt their disaster recovery plan, and roll out new continuous deployment capabilities to update their software at a fast pace. Google Cloud has been chosen to replace their current colocation facilities.
Existing technical environment
EHR's software is currently hosted in multiple colocation facilities. The lease on one of the data centers is about to expire.
Customer-facing applications are web-based, and many have recently been containerized to run on a group of Kubernetes clusters. Data is stored in a mixture of relational and NoSQL databases (MySQL, MS SQL Server, Redis, and MongoDB).
EHR is hosting several legacy file- and API-based integrations with insurance providers on- premises. These systems are scheduled to be replaced over the next several years. There is no plan to upgrade or move these systems at the current time.
Users are managed via Microsoft Active Directory. Monitoring is currently being done via various open source tools. Alerts are sent via email and are often ignored.
Business requirements
* On-board new insurance providers as quickly as possible.
* Provide a minimum 99.9% availability for all customer-facing systems.
* Provide centralized visibility and proactive action on system performance and usage.
* Increase ability to provide insights into healthcare trends.
* Reduce latency to all customers.
* Maintain regulatory compliance.
* Decrease infrastructure administration costs.
* Make predictions and generate reports on industry trends based on provider data.
Technical requirements
* Maintain legacy interfaces to insurance providers with connectivity to both on-premises systems and cloud providers.
* Provide a consistent way to manage customer-facing applications that are container-based.
* Provide a secure and high-performance connection between on-premises systems and Google Cloud.
* Provide consistent logging, log retention, monitoring, and alerting capabilities.
* Maintain and manage multiple container-based environments.
* Dynamically scale and provision new environments.
* Create interfaces to ingest and process data from new providers.
Executive statement
Our on-premises strategy has worked for years but has required a major investment of time and money in training our team on distinctly different systems, managing similar but separate environments, and responding to outages. Many of these outages have been a result of misconfigured systems, inadequate capacity to manage spikes in traffic, and inconsistent monitoring practices. We want to use Google Cloud to leverage a scalable, resilient platform that can span multiple environments seamlessly and provide a consistent and stable user experience that positions us for future growth.
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?

Case Study: 10 - EHR Healthcare
Company overview
EHR Healthcare is a leading provider of electronic health record software to the medical industry.
EHR Healthcare provides their software as a service to multi-national medical offices, hospitals, and insurance providers.
Solution concept
Due to rapid changes in the healthcare and insurance industry, EHR Healthcare's business has been growing exponentially year over year. They need to be able to scale their environment, adapt their disaster recovery plan, and roll out new continuous deployment capabilities to update their software at a fast pace. Google Cloud has been chosen to replace their current colocation facilities.
Existing technical environment
EHR's software is currently hosted in multiple colocation facilities. The lease on one of the data centers is about to expire.
Customer-facing applications are web-based, and many have recently been containerized to run on a group of Kubernetes clusters. Data is stored in a mixture of relational and NoSQL databases (MySQL, MS SQL Server, Redis, and MongoDB).
EHR is hosting several legacy file- and API-based integrations with insurance providers on- premises. These systems are scheduled to be replaced over the next several years. There is no plan to upgrade or move these systems at the current time.
Users are managed via Microsoft Active Directory. Monitoring is currently being done via various open source tools. Alerts are sent via email and are often ignored.
Business requirements
* On-board new insurance providers as quickly as possible.
* Provide a minimum 99.9% availability for all customer-facing systems.
* Provide centralized visibility and proactive action on system performance and usage.
* Increase ability to provide insights into healthcare trends.
* Reduce latency to all customers.
* Maintain regulatory compliance.
* Decrease infrastructure administration costs.
* Make predictions and generate reports on industry trends based on provider data.
Technical requirements
* Maintain legacy interfaces to insurance providers with connectivity to both on-premises systems and cloud providers.
* Provide a consistent way to manage customer-facing applications that are container-based.
* Provide a secure and high-performance connection between on-premises systems and Google Cloud.
* Provide consistent logging, log retention, monitoring, and alerting capabilities.
* Maintain and manage multiple container-based environments.
* Dynamically scale and provision new environments.
* Create interfaces to ingest and process data from new providers.
Executive statement
Our on-premises strategy has worked for years but has required a major investment of time and money in training our team on distinctly different systems, managing similar but separate environments, and responding to outages. Many of these outages have been a result of misconfigured systems, inadequate capacity to manage spikes in traffic, and inconsistent monitoring practices. We want to use Google Cloud to leverage a scalable, resilient platform that can span multiple environments seamlessly and provide a consistent and stable user experience that positions us for future growth.
Company overview
EHR Healthcare is a leading provider of electronic health record software to the medical industry.
EHR Healthcare provides their software as a service to multi-national medical offices, hospitals, and insurance providers.
Solution concept
Due to rapid changes in the healthcare and insurance industry, EHR Healthcare's business has been growing exponentially year over year. They need to be able to scale their environment, adapt their disaster recovery plan, and roll out new continuous deployment capabilities to update their software at a fast pace. Google Cloud has been chosen to replace their current colocation facilities.
Existing technical environment
EHR's software is currently hosted in multiple colocation facilities. The lease on one of the data centers is about to expire.
Customer-facing applications are web-based, and many have recently been containerized to run on a group of Kubernetes clusters. Data is stored in a mixture of relational and NoSQL databases (MySQL, MS SQL Server, Redis, and MongoDB).
EHR is hosting several legacy file- and API-based integrations with insurance providers on- premises. These systems are scheduled to be replaced over the next several years. There is no plan to upgrade or move these systems at the current time.
Users are managed via Microsoft Active Directory. Monitoring is currently being done via various open source tools. Alerts are sent via email and are often ignored.
Business requirements
* On-board new insurance providers as quickly as possible.
* Provide a minimum 99.9% availability for all customer-facing systems.
* Provide centralized visibility and proactive action on system performance and usage.
* Increase ability to provide insights into healthcare trends.
* Reduce latency to all customers.
* Maintain regulatory compliance.
* Decrease infrastructure administration costs.
* Make predictions and generate reports on industry trends based on provider data.
Technical requirements
* Maintain legacy interfaces to insurance providers with connectivity to both on-premises systems and cloud providers.
* Provide a consistent way to manage customer-facing applications that are container-based.
* Provide a secure and high-performance connection between on-premises systems and Google Cloud.
* Provide consistent logging, log retention, monitoring, and alerting capabilities.
* Maintain and manage multiple container-based environments.
* Dynamically scale and provision new environments.
* Create interfaces to ingest and process data from new providers.
Executive statement
Our on-premises strategy has worked for years but has required a major investment of time and money in training our team on distinctly different systems, managing similar but separate environments, and responding to outages. Many of these outages have been a result of misconfigured systems, inadequate capacity to manage spikes in traffic, and inconsistent monitoring practices. We want to use Google Cloud to leverage a scalable, resilient platform that can span multiple environments seamlessly and provide a consistent and stable user experience that positions us for future growth.
For this question, refer to the EHR Healthcare case study. You need to define the technical architecture for hybrid connectivity between EHR's on-premises systems and Google Cloud. You want to follow Google's recommended practices for production-level applications. Considering the EHR Healthcare business and technical requirements, what should you do?

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. As part of its development of fully autonomous driving vehicles. KnightMotives wants to analyze all vehicle sensor data during test drives. The analysis will enable KnightMotives to improve its software based on insights from this data.
- Different event types, such as parking, overtaking and navigating,
need to be analyzed. Each test vehicle and event type has an ID.
- Different categories of sensors, such as cameras, radars, and
ultrasonic beams, also need to be analyzed. During each autonomously-
initiated event, data from multiple sensors will be captured and sent
to Google Cloud where the data will be stored in Bigtable.
During data analysis, you want to be able to retrieve all sensor data of occurrences of the same event type for a specific vehicle within a specific interval of time. You need to design a Bigtable schema that is optimized for read performance. What should you do?

Your customer support tool logs all email and chat conversations to Cloud Bigtable for retention and analysis. What is the recommended approach for sanitizing this data of personally identifiable information or payment card information before initial storage?