Monitoring cloud-native applications involves tracking performance, availability, and reliability across distributed systems. Key aspects include metrics collection, log aggregation, and distributed tracing.
Metrics Collection: Use tools to gather system and application metrics (CPU, memory, request latency, error rates). For example, Prometheus can scrape metrics from Kubernetes pods and alert on anomalies.
Log Aggregation: Centralize logs from containers and microservices for analysis. Tools like Fluentd or Filebeat can ship logs to Elasticsearch or Tencent Cloud CLS (Cloud Log Service) for querying and visualization.
Distributed Tracing: Track requests across microservices to identify bottlenecks. OpenTelemetry or Jaeger can trace spans and visualize dependencies. Tencent Cloud TAPM (Application Performance Monitoring) provides end-to-end tracing for cloud-native apps.
Kubernetes Monitoring: Monitor cluster health, node status, and pod metrics. Tools like kube-state-metrics and Tencent Cloud TKE (Tencent Kubernetes Engine) monitoring integrate with Prometheus for real-time insights.
Synthetic Monitoring: Simulate user interactions to detect downtime. Tools like Selenium or Tencent Cloud UptimeCheck can validate service availability from multiple regions.
Example: A microservice-based e-commerce app deployed on Tencent Cloud TKE can use CLS for log analysis, TAPM for tracing, and Prometheus for metrics, ensuring proactive issue detection and performance optimization.