Kibana

Open-source interface for querying, analyzing, visualizing, and managing data stored in Elasticsearch. It provides a single UI for search, dashboards, alerting, and machine learning workflows, designed for speed and scale across structured, semi-structured, and unstructured data.

Widely adopted by enterprises such as Lawrence Livermore National Laboratory, Cisco, and Microsoft for observability, security, and search use cases. Kibana distinguishes itself by uniting logs, metrics, traces, and security signals in one platform, with built-in anomaly detection, geospatial analysis, and natural-language query support. Unlike generic BI tools, it speaks natively to Elasticsearch and offers an embedded Dev Tools Console for running API calls and testing queries.

Key features:

• Interactive dashboards with metrics, XY charts, graphs, maps, and tables, plus live data and drill-down
• Dev Tools Console for running Elasticsearch API calls, testing queries, and debugging with autocomplete
• No-code machine learning for anomaly detection, rare-event detection, and automated alert rules
• Geospatial visualization with multilayer maps, distance filters, and shape overlays for location-based analysis
• Kibana as code via REST API and Terraform provider for Discover sessions, dashboards, visualizations, and alert rules
• Natural-language and ES|QL querying with field-level summaries and inline ML analysis

Teams rely on it for log analytics and observability, SIEM and threat hunting with MITRE ATT&CK correlation, and custom enterprise search across websites or internal content. Developers use the Dev Tools Console for ad-hoc queries and debugging, ingest data through connectors, and deploy on-premises or via cloud-managed options.