Observability for Beginners: Logs, Metrics, Traces, and Everything Around Them
TL;DR · AI Summary
可观测性是现代系统运维的核心，通过日志、指标和追踪三类数据实现系统状态的全面监控。
Key Takeaways
- 日志记录单个事件，适合调试和审计。
- 指标用于聚合和统计多个事件，便于性能分析。
- 追踪用于关联跨服务的事件，支持分布式系统调试。
Outline
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Mindmap
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查看大纲文本（无障碍 / 无 JS 友好）
- 可观测性基础
- 事件
- 时间、上下文、结果
- 日志
- 单个事件记录
- 指标
- 聚合多个事件
- 追踪
- 跨服务事件关联
Highlights
Key sentences worth saving and sharing.
日志记录单个事件，适合调试和审计。
指标用于聚合和统计多个事件，便于性能分析。
追踪用于关联跨服务的事件，支持分布式系统调试。
Observability for Beginners: Logs, Metrics, Traces, and Everything Around Them
Jun 18, 2026
Observability for Beginners: Logs, Metrics, Traces, and Everything Around Them
A running service generates events constantly.
Requests arrive, functions run, errors appear, and each one is a thing that happened at a specific time with a specific context and a specific outcome.
Logs, metrics, and traces are three ways of looking at this same stream. A log captures one event as a line of text, a metric counts or aggregates many events, and a trace links related events as they move across services. Most of the concepts in observability, including cardinality, sampling, and correlation, are consequences of this structure.
In this article, we will look at the basics of observability in detail with concepts like logs, metrics, and traces explained in detail.