<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> Traceway offers a unified, OpenTelemetry-native observability platform designed to simplify the complex landscape of monitoring distributed systems. It targets engineers and power users by consolidating logs, traces, metrics, session replay, and AI tracing into a single, self-hostable application, eliminating the need for multiple disparate tools and reducing operational overhead.

How It Works

This platform leverages OpenTelemetry as its core, ingesting data directly via OTLP/HTTP from any compatible SDK without requiring a separate collector or vendor-specific agents. Traceway's novel approach integrates diverse observability signals—including end-to-end traces, trace-linked logs, metrics, exceptions with source mapping, user session replays, and AI observability (LLM costs/conversations)—into a cohesive system. This unified data model, linked by a single trace ID, provides deeper insights and a more streamlined debugging experience compared to stitching together multiple open-source or proprietary solutions.

Quick Start & Requirements

Self-hosting is recommended via Docker: clone the repository, navigate to the directory, and run docker compose up -d. The dashboard is accessible at http://localhost. Point any OpenTelemetry SDK to http://localhost/api/otel/v1/traces (or /metrics, /logs) to begin ingesting data. An embedded mode is available for Go applications, running Traceway with SQLite directly within the Go process. Production deployment details, TLS, and storage configuration are covered in the self-hosting documentation.

• Primary Install/Run: docker compose up -d (standalone), go run (embedded).
• Non-default Prerequisites: Docker (standalone), Go (embedded). Standalone mode requires ClickHouse and PostgreSQL; embedded mode uses SQLite.
• Links: Website, Docs, Cloud, Discord.

Highlighted Details

• Native OTLP/HTTP ingest supports traces, metrics, and logs from any OpenTelemetry SDK.
• Integrates session replay and AI observability alongside traditional logs, traces, and metrics in a single view.
• Features trace-linked structured logs, source-mapped exceptions, and AI observability for LLM interactions.
• Fully MIT licensed, offering complete freedom for self-hosting and commercial use without "open core" or restrictive licenses.

Maintenance & Community

Traceway is developed openly, with a strong emphasis on community engagement via Discord for discussions, roadmap input, support, and sharing production use cases. Contributions are welcomed through pull requests, with maintainers actively reviewing and merging changes.

Licensing & Compatibility

The project is released under the permissive MIT license. This license allows for broad adoption, including use in commercial, closed-source applications, without imposing copyleft obligations or vendor lock-in.

Limitations & Caveats

The README does not explicitly detail alpha/beta status or known critical limitations. The embedded mode relies on SQLite, which may present scalability constraints for extremely high-volume production environments compared to the standalone ClickHouse/PostgreSQL backend.