Subtask 4.1: Technical Processes

**CASE STUDY: TechStream Gaming** **Company Overview:** TechStream Gaming is a global gaming company with 500 employees and $50M annual revenue. **Current Environment:** On-premises data centers in US and EU. 200 servers. MySQL databases (5 TB). Peak users: 2M. Cost: $100K/mo. **Business Requirements:** Reduce costs by 40%. Support 5x user growth. Launch in APAC, SA, Africa. Improve deployment to daily. **Executive Statements:** CEO: 'Scale rapidly.' CFO: 'Max $100K/mo, ROI 18mo.' CTO: 'Limited cloud exp, 99.95% uptime.' **Technical Requirements:** <100ms latency globally. Real-time analytics. 5x traffic spikes. EU data residency. DDoS protection. CI/CD. **Constraints:** 12-month migration. Max 4-hour downtime. 20 devs (Java/MySQL), 5 ops (limited cloud). Budget $2M. **QUESTION:** How should you design the real-time analytics pipeline for player behavior data?

**CASE STUDY: Dress4Win** **Company Overview:** Dress4Win is a web-based retail company that helps users organize their wardrobes. **Current Environment:** Colocated data center. Tomcat app servers, Nginx web servers, MySQL databases, Redis caching. 100TB of image data on SAN. **Business Requirements:** Migrate to cloud to handle seasonal spikes (Black Friday). Reduce CapEx. Enable rapid prototyping. **Executive Statements:** CEO: 'Innovate faster, stop worrying about servers.' CFO: 'Move to OpEx. Ensure PCI-DSS compliance.' CTO: 'Modernize stack but migrate quickly first.' **Technical Requirements:** Secure hybrid connectivity during migration. PCI-DSS compliance. Automated scaling. CI/CD for microservices. **Constraints:** Migration must be completed before Q4 holiday season (6 months). Limited budget for refactoring during initial migration. **QUESTION:** For the post-migration modernization phase, the CTO wants to implement CI/CD for new microservices. Which GCP services should you recommend?

**CASE STUDY: TerramEarth** **Company Overview:** TerramEarth manufactures heavy equipment. 2 million vehicles in the field. **Current Environment:** Vehicles send telemetry via cellular. Processing 100,000 msgs/sec. On-prem Hadoop cluster. **Business Requirements:** Predict equipment failure. Reduce warranty costs. Provide fleet dashboard. **Executive Statements:** CEO: 'Monetize data.' CFO: 'Storage costs spiraling.' CTO: 'Need scalable ingestion and ML.' **Technical Requirements:** Ingest 500,000 msgs/sec. Store petabytes cost-effectively. Train ML models. Real-time anomaly detection. **Constraints:** Intermittent connectivity. Strict vehicle authentication. **QUESTION:** Which THREE GCP services should you combine to build the pipeline for real-time anomaly detection and predictive maintenance ML training? (Select THREE)

Your company has a hybrid cloud architecture. You have internal applications running on-premises and on GCP. You want on-premises servers to be able to resolve the DNS names of GCP Compute Engine instances (e.g., `myserver.c.myproject.internal`). How should you configure Cloud DNS?

You need to back up a 500 GB Persistent Disk attached to a Compute Engine instance. The disk contains a highly active database. You want to minimize the time the database is locked during the backup process. What is the most efficient way to take the backup?

You are managing a fleet of Compute Engine instances in a Managed Instance Group (MIG). The application processes messages from a Cloud Pub/Sub topic. Traffic is highly variable. You want the MIG to scale out when there is a backlog of messages and scale in when the queue is empty. How should you configure the autoscaler?

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: How should you address the CTO's requirement for a zero-downtime cutover from the legacy monolith to the new microservices?

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: Which GCP service should you recommend for the data scientists to explore data and train models, given their preference for Python and Jupyter?

You are designing a secure CI/CD pipeline for Google Kubernetes Engine (GKE). You must ensure that only container images that have been scanned for vulnerabilities and explicitly approved by the QA team can be deployed to the production cluster. Which GCP service should you use?

Your company is planning a massive marketing campaign that will require spinning up 5,000 new Compute Engine instances in the us-central1 region. What should you do first to ensure the capacity is available?

You are setting up a CI/CD pipeline using Cloud Build. You want the pipeline to automatically trigger whenever a developer pushes code to the 'main' branch in Cloud Source Repositories. Which TWO components must you configure? (Select TWO)

You need to design a logging architecture. Security audit logs must be retained for 3 years for compliance. Application error logs need to be analyzed in real-time to trigger alerts. Which TWO Cloud Logging export destinations should you configure? (Select TWO)

CASE STUDY: TechStream Gaming Overview: Industry: Gaming Size: 500 employees, $100M revenue Environment: - On-prem US/EU - 200 servers - MySQL (5 TB) - 2M peak users - $100K/mo cost Requirements: - Reduce costs 40% - 5x growth - Launch APAC/SA/Africa - Daily deployments Exec Statements: - CEO: Scale rapidly. - CFO: Max $100K/mo, 18mo ROI. - CTO: Limited cloud exp, 99.95% uptime. Tech Reqs: - <100ms latency globally - Real-time analytics - 5x seasonal spikes - EU data residency - DDoS protection - CI/CD Constraints: - 12mo migration - <4hr downtime - 20 Java/MySQL devs, 5 ops - $2M budget QUESTION: How should you design the real-time analytics pipeline for player behavior?

CASE STUDY: HealthData Inc Overview: Industry: Healthcare Analytics Size: 1000 employees Environment: - Co-located data center - Hadoop cluster - SFTP servers - 50 TB patient data Requirements: - ML models for diagnostics - Secure data sharing portals - Break data silos Exec Statements: - CEO: Need compute for ML. - CRO: HIPAA compliance is top priority. - CTO: Managed services needed to replace Hadoop. Tech Reqs: - Strict HIPAA compliance - Automated PHI de-identification - Comprehensive audit logging - CMEK - Network isolation (no public internet) Constraints: - US data sovereignty - 7-year retention (immutable) - Easy auditor access QUESTION: To satisfy the requirement for 'easy auditor access' to comprehensive audit logs, how should you configure Cloud Logging?

CASE STUDY: ManuIoT Overview: Industry: Manufacturing Size: 100 factories globally Environment: - 100,000 sensors - Local SCADA - Fragmented SQL Server DBs - No central analytics Requirements: - Predictive maintenance - Real-time global dashboards - Edge computing Exec Statements: - CEO: Monetize telemetry. - CFO: Costs must scale linearly. - VP Ops: Factory lines need local control if internet drops. Tech Reqs: - Ingest 1M msgs/sec - Stream processing - Offline factory capabilities - Train ML centrally, deploy to edge Constraints: - Low bandwidth/high latency at factories - Legacy MQTT protocol - Zero IT staff at factories QUESTION: Which service should you use to perform real-time anomaly detection on the streaming sensor data before it is stored?

A highly regulated financial institution uses GKE to run its applications. The security team mandates that only container images that have been scanned for vulnerabilities and explicitly signed by the QA team can be deployed to the production cluster. How should you enforce this policy?

Your team is planning a massive load testing event for a new application. You anticipate needing to provision 5,000 Compute Engine instances with GPUs in the `us-central1` region for a 48-hour period next weekend. What must you do to ensure the resources are available?

Your team wants to deploy a new version of a critical application. They want to minimize risk by routing only 5% of user traffic to the new version initially, monitoring it for errors, and then gradually increasing the traffic to 100%. If errors occur, they want to instantly route all traffic back to the old version. Which TWO deployment strategies support this requirement? (Select TWO)

Your company is adopting a DevSecOps culture. The security team wants to ensure that only container images that have been built by the official CI/CD pipeline and scanned for vulnerabilities can be deployed to the production GKE cluster. How should you enforce this?

Your company generates massive amounts of application logs across hundreds of Compute Engine VMs. The security team needs to retain all logs for 7 years for compliance. The operations team needs to query the last 30 days of logs in real-time to troubleshoot production issues. How should you configure Cloud Logging to meet BOTH requirements cost-effectively? (Select TWO)