logKb

LogKB is a proposed open-standard knowledge base for logging data and metadata. It aims to provide a unified model for describing log events, traces, and related contextual information so that logs from disparate systems can be stored, searched, and analyzed consistently.

The core idea is to separate raw log text from structured knowledge about those logs. LogKB defines a schema for log entries including fields such as timestamp, level, source, host, service, event_id, correlation_id, message, and an optional structured payload. It also supports provenance, versioning, retention, and access controls, enabling teams to track how a piece of information was produced and modified.

In practice, LogKB provides an abstraction layer that can be implemented over existing log stores or streaming pipelines. It is compatible with JSON-based or JSON-LD encodings and can be integrated with indexing engines for fast search. The standard emphasizes interoperability with incident response tools, SIEMs, and observability platforms, and supports linking log data to a knowledge graph of related entities such as services, users, and events.

Applications include improved incident investigation, auditability, compliance reporting, and machine learning for anomaly detection and root-cause analysis, because each log record carries richer, machine-readable context.

LogKB is an emergent concept rather than a finalized standard. Various proposals and experiments have appeared in open-source communities, and governance models emphasize openness, extensibility, and compatibility with existing logging ecosystems. Adoption depends on community consensus and vendor support.

See also logging, log management, observability, knowledge graph, SIEM.