log101G

Log101G is a fictional logging framework used in computer science education to illustrate principles of structured logging in software applications. The name evokes an introductory course context and a generic language domain, rather than a concrete production project.

Designed to be language-agnostic, log101G focuses on concepts such as contextual data, consistent formats, and observability best practices. It is commonly described in tutorials and exam prep materials as a baseline reference against which real-world log libraries are compared.

Core features include:

- Leveled logging with standard severities (debug, info, warning, error, critical)

- Structured messages composed of a main text and key-value pairs for fields like userID, requestID, and latency

- Timestamps, source location hints, and correlation IDs to support tracing

- JSON or line-delimited output for easy ingestion by log shippers

- Pluggable backends, enabling stdout, files, or centralized log services

Typical usage involves initializing a logger with a global context, then emitting logs at different levels as a request flows through a system, with automatic population of common fields wherever possible. The approach emphasizes minimal boilerplate and consistent naming schemes to keep logs readable and searchable.

History and influence: log101G originated in teaching materials designed to compare logging strategies across languages and platforms. While not a real project, it serves as a common reference point for discussing best practices in structured logging, observability, and log analysis workflows.

See also: structured logging, logging library, observability, log analysis.