Subtask 2.3: Compute Systems

**CASE STUDY: HealthCare360** **Company Overview:** HealthCare360 provides EHR systems to hospitals in NA and EU. **Current Environment:** Isolated on-prem deployments. Fragmented data. **Business Requirements:** Centralize EHR in cloud. Enable cross-hospital research. Ensure compliance. **Executive Statements:** CEO: 'Transforming to SaaS.' CFO: 'Need cost attribution per tenant.' CSO: 'Zero compromise on HIPAA/GDPR.' **Technical Requirements:** Multi-region active-active deployment. Microservices on GKE. End-to-end encryption (CMEK). Strict network perimeters. **Constraints:** Zero data loss (RPO=0). RTO < 15 minutes. HIPAA (US) and GDPR (EU) compliance. **QUESTION:** How should you configure the GKE clusters to ensure the highest level of network security and isolation for the microservices?

You are designing a highly available web application on Compute Engine. The application must survive a zone failure without manual intervention. How should you configure the Compute Engine instances?

A financial institution wants to modernize its applications using containers. However, due to strict regulatory requirements, some core banking databases and the applications that query them must remain in their on-premises data center. They want a unified way to manage Kubernetes clusters and enforce security policies across both GCP and on-premises environments. What should you recommend?

CASE STUDY: ShopGlobal Overview: Retailer, 2000 employees, $500M revenue. US-Central co-lo, Java/Tomcat monolith, Oracle RAC 20TB, batch inventory sync. Business Req: Handle 10x Black Friday spikes, personalized recommendations, modernize to microservices. Execs: CEO wants omnichannel; CFO needs predictable spend; CTO demands zero downtime cutover. Tech Req: PCI-DSS compliance, automated image processing, real-time inventory, CI/CD. Constraints: Complex Oracle stored procedures, team learning containers, strict bi-annual audits. QUESTION: Which compute platform should you recommend for the modernized microservices architecture, considering the team is just learning containers?

CASE STUDY: AeroMech Overview: Aviation manufacturer, 5000 employees, $2B revenue. 100 engines, 10k sensors/engine, 1GB data/flight. On-prem Hadoop. Business Req: Predictive maintenance, secure data sharing with airlines, monetize data. Execs: CEO wants new revenue; CFO demands ML ROI; CTO says on-prem storage unfeasible. Tech Req: High-throughput ingestion, PB-scale storage, train ML on historical data, deploy ML to edge (aircraft). Constraints: Intermittent low-bandwidth flight connectivity, aviation data compliance, data scientists use Python/Jupyter. QUESTION: To meet the requirement of deploying ML models to the aircraft for real-time anomaly detection, which approach should you use?

You are deploying a web application to Cloud Run. The application occasionally experiences sudden, massive spikes in traffic. During these spikes, the application takes 10 seconds to start up, causing timeout errors for users. How can you mitigate these cold start latencies?

A development team wants to deploy a simple Node.js web application. They want zero infrastructure management, automatic scaling from zero to handle traffic, and they only want to pay when their code is executing. They do not want to build Docker containers. Which compute service should they use?

CASE STUDY: RetailMart Overview: Industry: Retail/E-commerce Size: 2000 employees, $500M revenue Environment: - Monolithic Java app on VMware - Oracle RAC DB - F5 Load Balancers - 10 Gbps Direct Connect to AWS Requirements: - CapEx to OpEx - Handle 10x Black Friday traffic - Personalized recommendations - Modernize without impacting sales Exec Statements: - CEO: Omnichannel experience. - CFO: Predictable costs, no hardware refresh. - CTO: Break monolith, but Oracle DB stays on-prem for 2 years. Tech Reqs: - Zero downtime deployments - PCI-DSS compliance - Image processing pipeline - Async order processing Constraints: - Hybrid architecture required - Team knows Spring Boot, zero Kubernetes exp - 6-month timeline QUESTION: Which compute service should you select to host the new Spring Boot microservices, given the team's skills and the 6-month timeline?

CASE STUDY: RetailMart Overview: Industry: Retail/E-commerce Size: 2000 employees, $500M revenue Environment: - Monolithic Java app on VMware - Oracle RAC DB - F5 Load Balancers - 10 Gbps Direct Connect to AWS Requirements: - CapEx to OpEx - Handle 10x Black Friday traffic - Personalized recommendations - Modernize without impacting sales Exec Statements: - CEO: Omnichannel experience. - CFO: Predictable costs, no hardware refresh. - CTO: Break monolith, but Oracle DB stays on-prem for 2 years. Tech Reqs: - Zero downtime deployments - PCI-DSS compliance - Image processing pipeline - Async order processing Constraints: - Hybrid architecture required - Team knows Spring Boot, zero Kubernetes exp - 6-month timeline QUESTION: How should you design the asynchronous order processing system to ensure no orders are lost during Black Friday spikes?

A development team wants to deploy a microservices application on Kubernetes. They want to focus entirely on writing code and defining pod specifications, without managing nodes, configuring cluster autoscaling, or worrying about node pool upgrades. Which compute option should you recommend?

You are managing a GKE Standard cluster. During peak hours, the pods are consuming all available CPU on the existing nodes, causing new pods to remain in a 'Pending' state. You need the cluster to automatically add more pods when CPU usage is high, and automatically add more VMs to the cluster when there is no room for new pods. Which TWO autoscaling mechanisms must you configure? (Select TWO)

CASE STUDY: TechStream Gaming Company Overview: TechStream Gaming is a global multiplayer game developer with 500 employees and $100M annual revenue. They recently launched a hit mobile game that is growing rapidly. Current Technical Environment: - On-premises data centers in US and EU. - 200 bare-metal servers running Linux. - Self-managed MySQL databases (5 TB total) for player profiles and inventory. - Peak concurrent users: 2 million. - Current monthly infrastructure cost: $150K. Business Requirements: - Reduce infrastructure costs by 40%. - Support 5x user growth over 2 years. - Launch in 3 new regions (APAC, SA, Africa). - Improve deployment speed from 1 week to daily. Executive Statements: - CEO: "We need to scale rapidly to compete. Cloud migration is critical." - CFO: "Cost reduction is paramount. We cannot exceed $100K/month. ROI must be achieved in 18 months." - CTO: "Our team has limited cloud experience. Reliability is non-negotiable - 99.95% uptime minimum." Technical Requirements: - Sub-100ms latency for players globally. - Real-time analytics on player behavior. - Seasonal traffic spikes (5x during holidays). - CI/CD pipeline for daily deployments. Constraints: - Migration must complete in 12 months. - Cannot exceed 4-hour downtime during cutover. - Dev team: 20 engineers (Java, MySQL). - Ops team: 5 engineers (limited cloud experience). QUESTION: Which compute architecture should you recommend for the game servers to meet the deployment speed, scalability, and operational constraints?

CASE STUDY: HealthSecure Company Overview: HealthSecure provides electronic health record (EHR) systems and telemedicine platforms to hospitals across North America. They handle highly sensitive patient data. Current Technical Environment: - Co-located data centers with strict physical security. - Monolithic .NET applications running on Windows Server. - Microsoft SQL Server databases. - Custom-built video streaming solution for telemedicine. Business Requirements: - Migrate to the cloud to improve scalability during telemedicine surges. - Maintain strict compliance with HIPAA and HITECH regulations. - Enable interoperability with other healthcare providers using FHIR standards. Executive Statements: - CEO: "Telemedicine is exploding. We need to scale instantly to meet patient demand." - Chief Risk Officer (CRO): "Security and compliance are our license to operate. A data breach would destroy us." - CTO: "We want to leverage cloud-native AI/ML for medical image analysis in the future." Technical Requirements: - End-to-end encryption for all data at rest and in transit. - Strict network isolation to prevent data exfiltration. - Comprehensive audit logging of all data access. - High availability across multiple regions. Constraints: - Must use Customer-Managed Encryption Keys (CMEK). - Third-party auditors require detailed compliance reports. - Legacy .NET applications cannot be easily containerized without refactoring. QUESTION: Given the constraint that the legacy .NET applications cannot be easily containerized, which compute architecture should you recommend for the migration?

Your development team wants to deploy a microservices application to Google Kubernetes Engine (GKE). The application has highly variable traffic. The operations team is currently understaffed and wants to minimize the time spent managing node pools, OS upgrades, and capacity planning. However, the security team requires that the cluster uses Workload Identity and is entirely private (no public IP addresses for nodes). Which GKE configuration should you choose?

You are deploying a containerized web application to Cloud Run. The application is expected to receive sudden, massive spikes in traffic. You want to ensure the application scales quickly to handle the load, but you also need to prevent the backend database (Cloud SQL) from being overwhelmed by too many concurrent connections. Which TWO settings should you configure on the Cloud Run service? (Select TWO)