How do you monitor hybrid cloud resources for performance issues?

Hybrid cloud resource monitoring, which uniformly tracks performance metrics (such as CPU and memory) of public clouds (e.g., AWS, Azure) and private clouds, is crucial for ensuring high resource availability, cost optimization, and fault prevention, and is widely applied in enterprise IT operations and multi-cloud application scenarios.

Its core components include data collection agents (e.g., Prometheus agents), centralized dashboards (e.g., Grafana), and real-time analysis engines, characterized by multi-source integration and automatic alerting; it identifies delays or bottlenecks through real-time log and metric analysis, improving operational efficiency and reducing business risks.

Implementation steps: 1) Deploy a unified monitoring platform to integrate various cloud APIs; 2) Define key metrics (e.g., response time, error rate); 3) Configure threshold alerting and automated responses. Typical scenarios include identifying peak loads for automatic scaling, with business values of reducing downtime, enhancing user experience, and optimizing cloud expenditures.