What is the role of metrics in observability for cloud-native applications?

Metrics are one of the core pillars of observability for cloud-native applications, providing quantitative measurements of system operating status and performance. In highly dynamic and distributed cloud-native environments (such as microservices and containers), metrics are crucial for real-time monitoring of resource utilization, service performance, and application health, serving as the foundation for stable operation and efficient troubleshooting.

Metrics mainly include infrastructure metrics (CPU, memory, network), application metrics (request latency, error rate, throughput), and business metrics. They are typically time-series data, collected, stored, and queried by tools such as Prometheus. Their core functions lie in visualizing system status, establishing performance baselines, analyzing historical trends, promptly detecting anomalies (such as traffic surges and error spikes), and triggering alerts. They directly impact operational efficiency, capacity planning decisions, and provide key basis for automatic scaling (such as HPA).

The application value of metrics lies in: 1. Proactively identifying performance bottlenecks and potential failure points, reducing Mean Time to Recovery (MTTR); 2. Deeply understanding application behavior and optimizing resource allocation to reduce costs; 3. Verifying the actual performance effects of application changes (such as new version deployments); 4. Supporting business goal monitoring (such as user conversion rates). Through real-time metrics dashboards and historical trend analysis, teams can continuously ensure service SLAs (Service Level Agreements) and improve user experience.