grafana: Explore and Visualize Observability Data

Overview

Grafana brings observability data from multiple sources into dashboards and exploration tools. Teams can query and compare data without requiring it all to be stored in one system, helping them understand service behavior and monitor important signals.

It is aimed at engineering and operations teams that need to visualize metrics and logs, investigate issues, and define alerts. Its usefulness depends on connecting the data sources relevant to the team's environment.

Key Features

• Build dashboards with configurable visualization panels.
• Use template variables to create reusable, dynamic dashboards.
• Explore data through ad-hoc queries and drilldowns.
• Switch from metrics to logs while preserving label filters.
• Compare queries and time ranges in a split view.
• Define alert rules and send notifications to external systems.
• Combine queries from different data sources in one graph.

Use Cases

• Operations teams can monitor service metrics and receive alerts when selected signals need attention.
• Engineers investigating an incident can explore metrics, compare time ranges, and follow related labels into logs.
• Platform teams can create reusable dashboards for different services or environments with template variables.
• Organizations with data spread across multiple systems can visualize queries from different sources together.

Getting Started

See the installation guides for setup options. For the project overview and contribution instructions, see the repository README.

Alternatives

• superset: Superset focuses on SQL-based business intelligence and self-service analytics, while Grafana centers on operational metrics, logs, traces, and alerting.
• Chartbrew: Chartbrew builds live reporting dashboards from APIs and databases, while Grafana is geared toward operational observability and alerting.

Considerations

Grafana is distributed under AGPL-3.0-only, with Apache-2.0 exceptions described in LICENSING.md. It is a visualization and exploration platform, so teams should identify and configure the data sources they need; the repository describes support for mixing sources but does not provide a single universal data store.