Backend logging is the systematic recording of events, errors, and state changes within server-side applications to enable debugging, monitoring, and security compliance. In distributed systems, effective logging transforms raw event streams into actionable insights, balancing verbosity with cost through sampling, aggregation, and structured formats. Always log in UTC, use structured JSON, and treat correlation IDs as non-negotiable — these foundational decisions determine whether your logs serve production debugging or drown engineers in noise.
What This Cheat Sheet Covers
This topic spans 21 focused tables and 130 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: Structured Logging Formats
| Format | Example | Description |
|---|---|---|
{"timestamp":"2026-05-16T14:30:00Z", "level":"ERROR","service":"api", "correlationId":"abc-123","message":"Auth failed"} | • Key-value pairs enabling efficient parsing and querying • industry standard for centralized log systems | |
<134>1 2026-05-16T14:30:00Z app-1 api - ID47 [user="john"] Auth failed | • Modern syslog format with structured data and metadata fields • supports custom key-value extensions | |
<134>May 16 14:30:00 app-1 api: Auth failed | • Legacy plaintext syslog format • limited to 1024 bytes • widely supported but lacks structure |