{"name":"traceway: OpenTelemetry-Native Observability in One Platform","description":"Traceway is an MIT-licensed observability platform built on OpenTelemetry, combining traces, logs, metrics, errors, session replay, and more. Self-host it with Docker Compose or use Traceway Cloud to investigate application issues in one place.","github":"https://github.com/tracewayapp/traceway","url":"https://osrepos.com/repo/tracewayapp-traceway","source":"osrepos.com","sourceDescription":"This repository profile is provided by osrepos.com, an open source repository discovery platform.","repositoryProfile":"https://osrepos.com/repo/tracewayapp-traceway","generatedFor":"open source discovery and AI-assisted research","markdown":"https://osrepos.com/repo/tracewayapp-traceway.md","json":"https://osrepos.com/repo/tracewayapp-traceway.json","topics":["go","self-hosted","monitoring","observability","session-replay","on-call-paging"],"keywords":["go","self-hosted","monitoring","observability","session-replay","on-call-paging"],"stars":null,"summary":"Traceway is an MIT-licensed observability platform built on OpenTelemetry, combining traces, logs, metrics, errors, session replay, and more. Self-host it with Docker Compose or use Traceway Cloud to investigate application issues in one place.","content":"## Overview\n\nTraceway is an OpenTelemetry-native observability platform built on OpenTelemetry. It brings traces, logs, metrics, exceptions, session replay, AI tracing, and on-call paging together so teams can connect production signals and investigate problems without assembling a separate toolchain. Backend services send telemetry over OTLP/HTTP; browser and mobile apps use Traceway integrations.\n\nIt is aimed at teams that want a unified observability service they can self-host or use through Traceway Cloud. The repository includes a Go backend, SvelteKit dashboard, CLI, agent skills, and examples. Its MIT license applies to the project, and the README describes its features as available without an open-core split.\n\n## Key Features\n\n- Ingest OpenTelemetry traces, logs, and metrics over OTLP/HTTP, with trace-linked log search and span waterfalls.\n- Group exceptions by fingerprint and rank issues, with source maps and mobile symbolication support.\n- Track endpoint latency, throughput, and error rates, and define SLOs with error budgets and burn-rate alerts.\n- Capture session replays for web and mobile projects to provide context around errors.\n- Inspect AI usage, including token and cost data, latency, and conversations.\n- Configure on-call rotations, escalation policies, and notifications through supported channels.\n- Deploy with Docker Compose, use embedded Go mode, or choose the documented SQLite and DuckDB deployment options.\n- Use the read-only `traceway` CLI and agent skills to query telemetry; write access is a separate opt-in feature.\n\n## Use Cases\n\n- An application team wants traces, logs, and metrics connected while diagnosing a production error.\n- A team shipping web or mobile apps needs to inspect the user session leading up to a crash or exception.\n- Platform engineers want to monitor endpoint performance and alert on service-level objectives.\n- Teams operating LLM-backed applications want visibility into AI request costs, tokens, latency, and conversations.\n- A Go developer wants to embed a lightweight observability backend in an application rather than deploy the standalone stack.\n\n## Our Take\n\nTraceway is an actively maintained, broad OpenTelemetry-based observability option, with recent commits and releases, but its contribution history is concentrated around one contributor.\n\n**Good fit if:**\n- You want a self-hosted or managed platform that combines OpenTelemetry telemetry with errors, replay, and alerting.\n- Your services can report through OpenTelemetry and you want to avoid stitching together separate observability tools.\n- You value an MIT-licensed project and are comfortable evaluating a rapidly developed platform with concentrated contributions.\n\n**Look elsewhere if:**\n- Your environment depends on a specific integration or capability not listed in the repository documentation.\n- You need a project whose development is not heavily dependent on one contributor.\n- You do not want to operate a Docker Compose deployment or use the managed cloud option.\n\n## Project Health\n\n| Signal | Value |\n|---|---|\n| Status | **Active**: regular commits and releases |\n| Last commit | 2026-10-29 (1 day ago) |\n| Commits, last 90 days | 100+ |\n| Releases, last 12 months | 100+ (latest cli/v2.0.8, 2026-10-28) |\n| Contributors | 18 (top contributor: 79% of commits) |\n| Issues closed, last 90 days | 35+ (typically closed in 7 days) |\n| Pull requests merged, last 90 days | 69 (typically merged in 1 day) |\n| Project age | 11 months |\n\nChecked on 2026-10-31 with the GitHub API.\n\n## Project Facts\n\n- Language: Go\n- License: MIT\n- Stars: 1.8k\n- Forks: 92\n- Topics: alerting, exception-tracker, issue-tracking, logs, metrics, monitoring, observability-platform, open-telemetry\n- Website: https://tracewayapp.com\n- Archived: no\n\n## What You Need\n\nDetected in the repository:\n\n- Go (main language on GitHub)\n- A Dockerfile, so it can run in a container; a Compose file sets up the related services\n- A Helm chart for Kubernetes\n- Automated checks on GitHub Actions\n\n## Getting Started\n\n```bash\ngit clone https://github.com/tracewayapp/traceway\ncd traceway && docker compose up -d\n```\n\nOpen `http://localhost` and point an OpenTelemetry exporter at the local OTLP endpoint. See the [README](https://github.com/tracewayapp/traceway) and [self-hosting documentation](https://docs.tracewayapp.com/server/docker-compose) for configuration and production deployment details.\n\n## License in Plain Words\n\n**MIT** (permissive).\n\n- Commercial use: yes\n- Modify and redistribute: yes\n- You must keep: the copyright and license notice\n- Share your changes: no\n\nA summary, not legal advice: the LICENSE file is what applies.\n\n## Alternatives\n\n- [hertzbeat](https://osrepos.com/repo/apache-hertzbeat): HertzBeat focuses on agentless infrastructure and service monitoring, metrics, logs, and alerts rather than application traces, errors, and session replay.\n\n| Project | Language | License | Stars | Status |\n|---|---|---|---|---|\n| **traceway** | Go | MIT | 1.8k | Active |\n| [hertzbeat](https://osrepos.com/repo/apache-hertzbeat) | Java | Apache-2.0 | 7.4k | Active |\n\n## Considerations\n\n- Project health is marked Active, with regular commits and releases and ongoing issue and pull-request handling. However, most reported code contributions come from one person, which is a contributor-concentration risk.\n- The recommended standalone setup uses Docker Compose and the documented stack includes ClickHouse and PostgreSQL. Embedded SQLite mode is available, with DuckDB as another documented option.\n- Profiling is explicitly described as experimental, so teams should assess its suitability before relying on it.\n- The README provides test commands, but the supplied requirements data does not indicate tests as a project requirement. Teams adopting it should assess the test coverage relevant to their deployment.\n- The repository is MIT licensed. Review the license and deployment documentation for your own distribution and operational requirements.","metrics":{"detailViews":2,"githubClicks":0},"dates":{"published":null,"modified":"2026-10-31T01:03:31.000Z"}}