# Kibana — Data Visualization and Exploration for Elasticsearch

> Kibana is the official visualization layer for the Elastic Stack, providing dashboards, search interfaces, and analytics tools for data stored in Elasticsearch.

## Install

Save in your project root:

# Kibana — Data Visualization and Exploration for Elasticsearch

## Quick Use
```bash
# Run with Docker
docker run -d --name kibana --net elastic -p 5601:5601 docker.elastic.co/kibana/kibana:8.17.0

# Or install on Debian/Ubuntu
sudo apt-get install kibana
sudo systemctl enable --now kibana

# Access the web UI
open http://localhost:5601
```

## Introduction
Kibana is the window into the Elastic Stack. It lets you search, visualize, and build dashboards over data indexed in Elasticsearch—logs, metrics, APM traces, and security events—without writing code.

## What Kibana Does
- Provides Discover for ad-hoc search and filtering of Elasticsearch indices
- Offers a drag-and-drop dashboard builder with 20+ visualization types
- Includes Canvas for pixel-perfect, presentation-ready live reports
- Ships with Lens, an AI-assisted chart builder that suggests visualizations
- Manages Elastic Stack settings, index lifecycle policies, and user roles

## Architecture Overview
Kibana is a Node.js server that communicates with Elasticsearch via its REST API. The browser-based frontend renders visualizations client-side using EUI components. Saved objects (dashboards, visualizations, index patterns) are stored in a dedicated Elasticsearch system index. Plugins extend the core with modules like APM, SIEM, Maps, and Alerting.

## Self-Hosting & Configuration
- Edit `kibana.yml` to set `elasticsearch.hosts` and `server.port`
- Secure access with Elastic's built-in RBAC or an external IdP via SAML/OIDC
- Set `server.basePath` when running behind a reverse proxy
- Use Kibana Spaces to separate dashboards by team or environment
- Scale horizontally by running multiple Kibana instances behind a load balancer

## Key Features
- Lens: intelligent chart suggestions based on the data fields you select
- Alerting: define threshold or anomaly-based rules with actions (email, Slack, webhook)
- Maps: geo-spatial analysis with custom layers, region maps, and heatmaps
- Security app: timeline investigation, detection rules, and case management
- Dev Tools console: execute Elasticsearch queries and API calls directly

## Comparison with Similar Tools
- **Grafana** — multi-datasource; Kibana is deeply integrated with Elasticsearch only
- **Apache Superset** — SQL-first BI tool; Kibana excels at full-text log exploration
- **Datadog** — SaaS observability; Kibana is self-hosted and open-source
- **Splunk** — enterprise log analytics; Kibana offers a free tier with Elastic license

## FAQ
**Q: Is Kibana free?**
A: Kibana is source-available under the Elastic License 2.0. The free Basic tier covers Discover, dashboards, and most visualization features.

**Q: Can Kibana work without Elasticsearch?**
A: No. Kibana requires a running Elasticsearch cluster as its data store and query engine.

**Q: How do I import dashboards from the community?**
A: Use the Saved Objects management page to import `.ndjson` exports, or install prebuilt dashboards via Elastic Agent integrations.

**Q: What hardware does Kibana need?**
A: A minimum of 1 GB RAM for small deployments. Kibana itself is lightweight; the Elasticsearch cluster handles the heavy query work.

## Sources
- https://github.com/elastic/kibana
- https://www.elastic.co/kibana

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Source: https://tokrepo.com/en/workflows/80d740c3-3f30-11f1-9bc6-00163e2b0d79
Author: AI Open Source