You improve CloudApp’s monitoring to prevent SLA violations. Simulation Details: CloudApp is a leading technology company specializing in microservices-based applications that drive operational efficiency and innovation. Serving over 500 enterprise clients globally, including Fortune 500 companies, CloudApp delivers cutting-edge solutions such as a real-time analytics platform capable of processing over 1 million data points per second and an e-commerce API that handles over 10 million daily transactions with sub-500ms response times. Operating in a highly competitive sector, CloudApp is committed to maintaining 99.99% uptime under stringent Service Level Agreements (SLAs), where any outage can result in significant financial penalties and reputational damage. In 2023, a major outage caused by unmonitored slow endpoints highlighted the need for more precise monitoring metrics. This incident led to the development of a new monitoring dashboard, spearheaded by Lead Developer Thomas Graham, to enhance system reliability and reduce SLA violations by 40%. CloudApp fosters a collaborative environment where technical precision meets business priorities, ensuring solutions deliver meaningful outcomes for stakeholders. You take on the role of a DevOps Engineer at CloudApp, collaborating with Lead Developer Thomas Graham to implement critical monitoring metrics in the HealthMonitor.java file. Your task is to design and refine three essential methods: getHealth(), getSlowEndpoints(), and getMostCalledEndpoint(). These methods are vital to ensuring system reliability, reducing SLA violations, and providing actionable insights for CloudApp’s monitoring dashboard. Through real-time chat with Thomas, you’ll receive technical guidance and feedback to refine your implementation. You’ll need to balance technical precision with business objectives, ensuring your solutions align with CloudApp’s SLA requirements and avoid false alarms. This mission challenges you to think critically, process data efficiently, and communicate your technical decisions effectively. - Collaborate with Thomas Graham to understand the technical and business requirements for the monitoring metrics. - Implement and refine the getHealth(), getSlowEndpoints(), and getMostCalledEndpoint() methods in the HealthMonitor.java file. - Ensure your implementation aligns with SLA requirements, avoids false alarms, and provides actionable insights for system monitoring. - Successfully complete the simulation by delivering a robust and reliable monitoring solution that enhances CloudApp’s dashboard.