JSONlogs

JSONlogs refer to log entries that are encoded as JSON objects. This approach emphasizes structured logging, where each event is captured as a machine-readable data structure rather than plain text. JSONlogs are commonly used in modern software systems to facilitate ingestion by log management, observability, and analytics platforms. They are often delivered as line-delimited JSON, also known as JSON Lines, to support streaming and scalable processing.

A typical JSONlog entry includes fields such as timestamp, level, and message, along with optional metadata about the service or environment. Common fields include service or component, host or instance, environment, and a timestamp in ISO 8601 or epoch format. Additional context fields may include correlation identifiers such as traceId and spanId, requestId for tracing user requests, and error details or stack traces. Custom fields can carry application-specific data, such as user identifiers or transaction details. The structure is designed to be extensible while remaining machine-parseable.

Benefits of JSONlogs include improved interoperability with log-management and monitoring tools, easier filtering and aggregation, and enhanced ability to correlate events across distributed systems. They support search, alerting, and visualization in platforms like ELK/EFK stacks, cloud logging services, and SIEM systems. Potential challenges include increased log volume, the need for careful handling of sensitive information, and the risk of schema drift across different services.

Best practices advocate a consistent schema, a minimal and defined set of standard fields, deterministic log levels, and the inclusion of correlation IDs. It is also advisable to redact sensitive data, document field meanings, and leverage validation where possible. Example: {"timestamp":"2025-12-07T12:00:00Z","level":"INFO","service":"auth","message":"User login succeeded","requestId":"req-123","userId":"u-987"}