Kibana is an open source interface designed to query, analyze, visualize, and manage data stored in Elasticsearch. It serves as the primary frontend for the Elastic Stack, transforming raw log and metric data into interactive charts, graphs, and dashboards. Built with TypeScript, Kibana empowers developers, DevOps engineers, and data analysts to gain operational visibility without writing complex queries manually. It is commonly used in monitoring applications, troubleshooting system failures, and exploring large-scale telemetry data across distributed systems.
Kibana is not a standalone database but a visualization and exploration layer that depends on Elasticsearch. It is ideal for users who need to explore time-series data, create custom dashboards, or monitor application performance in real-time. The tool is widely adopted in production environments for observability and is also used by contributors to test new features or submit code improvements via its open development model.
What You Get
- Interactive Visualizations - Create bar charts, line graphs, pie charts, heatmaps, and more from Elasticsearch data using a drag-and-drop interface, enabling non-technical users to explore metrics without writing queries.
- Dashboards - Combine multiple visualizations into a single, shareable dashboard to monitor key metrics such as application latency, server CPU usage, or error rates across services.
- Discover Tool - Browse and filter raw log data in real-time with a full-text search interface, supporting Lucene query syntax for advanced filtering and field-based searches.
- Observability Suite - Pre-built modules for application performance monitoring (APM), infrastructure metrics, and logs to quickly set up end-to-end observability pipelines.
- Version Compatibility Enforcement - Ensures stable operation by enforcing version matching between Kibana and Elasticsearch, with clear warnings or fatal errors for incompatible versions to prevent data corruption or misconfiguration.
Common Use Cases
- Building a real-time application monitoring system - A DevOps team uses Kibana to visualize API response times, error rates, and server health from Elasticsearch-indexed logs, creating dashboards that alert on anomalies in production microservices.
- Troubleshooting distributed system failures - Engineers query Elasticsearch logs via Kibana’s Discover tab to trace a failed transaction across multiple services by filtering on trace IDs and timestamps.
- Problem: Manual log analysis is slow → Solution: Kibana - Before Kibana, teams grepped through gigabytes of log files; now they use Kibana’s Discover and Lens to filter, aggregate, and visualize logs in seconds with zero code.
- Team: SREs managing cloud-native infrastructure - Site Reliability Engineers use Kibana dashboards to monitor Kubernetes pod states, container restarts, and network latency across AWS, GCP, and Azure clusters via centralized logging with Filebeat and Metricbeat.
Under The Hood
The project is a sophisticated, configuration-driven framework tailored for building extensible, plugin-based applications within a serverless Kibana environment. It emphasizes flexibility through tiered customization and modular architecture, enabling diverse deployment modes and product types.
Architecture
This system adopts a layered, modular architecture designed for adaptability in serverless Kibana setups. It leverages configuration composition and conditional feature activation to support dynamic customization across environments.
- Configuration-driven architecture enables flexible, tier-based overrides for Kibana features and plugin behavior
- Feature privilege controls and plugin enablement/disabling mechanisms ensure clear separation of concerns across product types
- Centralized configuration files and feature flagging facilitate decoupled yet cohesive plugin ecosystems
- Strong emphasis on modular design supports scalable and maintainable application extensions
Tech Stack
Built with TypeScript and React, the framework integrates deeply with Kibana’s internal tools and ecosystems to support large-scale UI development.
- Built using TypeScript and React, with Kibana’s core framework as the foundation for UI and plugin systems
- Relies heavily on @kbn and @elastic packages, RxJS for reactive programming, and lodash for utility functions
- Leverages Kibana’s build system, Yarn for dependency management, and configuration-based tooling setups
- Comprehensive testing stack includes Jest, supertest, and well-organized test suites for unit and integration validation
Code Quality
Code quality is consistently high with strong testing practices, linting, and adherence to style conventions across the codebase.
- Extensive test coverage ensures reliability and maintainability across core modules and components
- Error handling is implemented through widespread try/catch patterns, though some inconsistencies in propagation exist
- Consistent naming and style conventions support readability and long-term code health
- Modular structure enforces clear separation of concerns and reduces cross-module coupling
What Makes It Unique
This project distinguishes itself through its plugin-first approach and developer-focused tooling, enabling scalable and extensible application development.
- Extensive plugin ecosystem with standardized lifecycle management and modular extension patterns
- Innovative API documentation generation and versioning that streamline integration and maintainability
- Deep Kibana visualization and data handling integration enables rich embeddable components and real-time interaction
- Developer-centric tooling including examples, testing utilities, and dependency injection patterns simplify complex plugin workflows