cat
CAT 作为服务端项目基础组件，提供了 Java, C/C++, Node.js, Python, Go 等多语言客户端，已经在美团点评的基础架构中间件框架（MVC框架，RPC框架，数据库框架，缓存框架等，消息队列，配置系统等）深度集成，为美团点评各业务线提供系统丰富的性能指标、健康状况、实时告警等。
Real-time application monitoring platform that tracks errors, slow requests, and performance metrics across distributed services as they happen, with dashboards and alerts.
CAT is a real-time application monitoring platform originally built by Meituan-Dianping (a major Chinese tech company). It solves the problem of knowing what's happening inside your software systems right now — tracking errors, slow requests, and performance metrics across all your services as they occur, not after the fact.
The way it works: small client libraries embedded in your application code send monitoring data (transactions, events, heartbeats, metrics) to a central CAT server, which processes everything in near-real-time and displays dashboards and alerts. Because data processing completes within seconds of generation, your engineering team can spot and respond to problems almost immediately rather than discovering them from user complaints.
CAT is designed for large-scale distributed systems — multiple services spread across many servers — and includes a high-availability setup to ensure the monitoring system itself doesn't become a point of failure. Client libraries are available for Java, C, C++, Python, Go, and Node.js, so teams with mixed technology stacks can use a single monitoring platform. You would use this if you're running backend services and need real-time visibility into performance, error rates, and system health. The server is written in Java and stores log data in HDFS (Hadoop's distributed file system).
Where it fits
- Monitor error rates and slow requests across multiple backend services in real-time.
- Set up alerts to catch performance degradation or system failures within seconds of occurrence.
- Track application health metrics and transaction data across a distributed system with mixed technology stacks.
- Diagnose production issues quickly using centralized dashboards instead of waiting for user complaints.