What Traceway Does
Traceway is an MIT-licensed observability platform that runs every signal a modern team needs — logs, distributed traces, metrics, exceptions, session replay, and AI/LLM tracing — through a single self-hosted stack. It is OpenTelemetry-native: you point any OTel SDK at the backend over OTLP/HTTP and data flows in without a Collector, without a proprietary vendor SDK, and without per-event metering. The deploy story is the differentiator. A single docker-compose up brings the entire stack online in roughly ninety seconds, which is closer to how developers expect modern infrastructure to behave than the typical Prometheus-Loki-Tempo-Grafana assembly job.
Architecture and the 90-Second Deploy Promise
Under the hood, Traceway is a deliberately minimal Go/Gin backend that fronts ClickHouse for telemetry storage and PostgreSQL for relational data. A SvelteKit dashboard handles the UI, and the entire system is shipped as Docker images that wire themselves together via compose. For teams that do not want to operate ClickHouse, there is an embedded SQLite mode that runs inside any Go application with zero external dependencies — useful for smaller deployments, local development, or single-tenant SaaS products that want observability without spinning up extra infrastructure.
The 90-second deploy claim holds up in practice. On a fresh VPS or laptop, the gap between cloning the repo and pointing your first OTel SDK at it is genuinely a couple of minutes, not the half-day of YAML wrangling that the equivalent open-source stack typically takes. That bar matters because the alternative for most teams is either paying Datadog rates or building their own stack from a half-dozen open-source pieces, and both are expensive in different ways.
AI and LLM Tracing as a First-Class Signal
Where Traceway pulls clearly ahead of general-purpose alternatives is its AI observability layer. It captures LLM cost, token counts, latency, and full conversation traces across providers, with native support for OpenRouter and any OTel-compatible AI gateway. For teams building LLM-powered applications, this means production-grade tracing without routing sensitive prompts through a third-party SaaS — the entire trail stays inside your own infrastructure, which is often the difference between a tool you can use on customer data and one you cannot.
This positions Traceway in the same conversation as Langfuse, Pydantic Logfire, and OpenLIT, but with a meaningfully wider scope. Those three are AI-observability tools that also do some general telemetry; Traceway is a general telemetry tool that treats AI tracing as a peer signal rather than a bolt-on. For a team running mixed workloads — traditional services plus a few LLM-powered features — that wider scope removes the need to operate two observability stacks side by side.
SDK Coverage and Alerting
Backend SDK coverage spans Go (Gin, Chi, Fiber, net/http), Node.js (NestJS, Hono, Cloudflare Workers), and PHP (Symfony). On the frontend, Next.js, React, Vue, and Svelte are supported with session replay included rather than as a separate $200/month add-on. Mobile coverage extends to Flutter, Android, and React Native. The list reads like a checklist for a typical modern stack, which is the right bar for a platform claiming to be a single-pane-of-glass replacement for assembling multiple tools.