How do you use monitoring data to proactively address application issues?

Monitoring data includes application performance metrics, logs, and tracing information, used for real-time detection and diagnosis of issues. Its importance lies in improving application availability and reducing downtime, applicable to cloud-native environments such as Kubernetes management scenarios. The core components include data collection tools (e.g., Prometheus), alert systems, and automated response mechanisms (e.g., K8s autoscaling). In terms of features, it combines AI analysis to achieve predictive maintenance and real-time optimization, reducing MTTR and enhancing system resilience in practical applications, which broadly impacts the operational efficiency of cloud-native platforms. Implementation steps involve deploying monitoring tool integration (e.g., Istio), configuring threshold alerts, and triggering automated responses such as container restart or resource adjustment. The business value is shortening fault response time, optimizing resource utilization, improving user experience, and ultimately reducing operational costs.