How do you monitor cloud-native storage systems for potential issues?

Cloud-native storage systems are distributed storage solutions designed for containerized and microservices architectures, providing persistent data support, elasticity, and high availability. Their importance lies in ensuring the reliable operation of critical applications such as databases. Application scenarios include Kubernetes persistent volumes and stateful services, which rely on dynamic resource management to maintain business continuity.

The core of monitoring includes metrics collection (such as IOPS, latency), log aggregation, and alert mechanisms, using tools like Prometheus and Grafana for real-time analysis of data streams. The feature is automated detection of performance bottlenecks or anomalies, which significantly enhances fault prediction capabilities, operational efficiency, and system reliability, preventing data loss or service disruptions through optimized storage configurations.

Implementation steps: 1. Deploy metric collection agents (e.g., Node Exporter); 2. Set up alert rules to monitor threshold breaches; 3. Analyze logs to identify abnormal patterns. Business values include reducing downtime risks, optimizing resource costs, and ensuring data integrity, with typical scenarios such as handling sudden load surges or insufficient capacity issues.