Logging
Recording discrete events with timestamps, severity levels, and context. Structured logs (JSON) are searchable; unstructured logs (plaintext) are not. Ship them to a central system.
What is Logging?
Recording discrete events with timestamps, severity levels, and context. Structured logs (JSON) are searchable; unstructured logs (plaintext) are not. Ship them to a central system.
Logging is a intermediate-level concept that sits in the Observability & Monitoring area of system design. Engineers reach for it whenever they need to reason about real-world trade-offs in that space — not just for textbook correctness, but because real production systems at companies like Netflix, Amazon, and Google make these decisions every day.
If you want to go deeper than this definition — with diagrams, code, and a quiz to lock it in — work through the "Logging" lesson linked below. It walks through the why, the mechanism, the trade-offs, and how the giants actually use it in production.
Learn Logging in depth
Full interactive lesson with diagrams, code examples, real-world references, and a quiz.
Open the Logging lessonRelated lessons
Lessons that touch on Logging as part of a larger topic.
Write-Ahead Logging
Write changes to a sequential log before applying them, the foundation of database crash recovery
advanced · consistency models
Audit Logging
Record who did what, when, and why, the immutable trail that compliance, security, and debugging all depend on
intermediate · data governance compliance
Centralized Logging
One place for all logs, the operational backbone of distributed systems
intermediate · observability monitoring
Structured Logging
Logs as data, not text, making every log line queryable and machine-parseable
intermediate · observability monitoring
Security Audit Logging
Recording security-relevant events with tamper-proof, queryable audit trails for compliance and incident investigation
intermediate · security architecture
See also
Related glossary terms you might want to look up next.
Observability
The ability to understand a system's internal state from its external outputs. Built on three pillars: metrics, logs, and traces.
Distributed Tracing
Tracking a request as it flows through multiple services in a distributed system. Each service adds its trace, creating a full picture of the request journey.
Elasticsearch
A distributed search and analytics engine built on Apache Lucene. Powers full-text search, log analysis, and real-time analytics at scale.