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🎉 Traceway 2.0 is here. More reliable traces, better OpenTelemetry compatibility, and a clearer picture of your app. Read the V2 release post →

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Traceway is an OpenTelemetry-native observability platform. It combines logs, traces, metrics, session replay/RUM, exceptions, AI tracing, and on-call paging in one place. Point an OTLP exporter at it and you're in business. No Collector, no glue code, no per-language vendor SDK.

MIT licensed. No BSL. No "open core." Every feature is in the box. Self-host it for free, or run it on Traceway Cloud if you'd rather not babysit infra.

What's in the box

• Logs: Structured, trace-linked, sub-second search. Native OTLP/HTTP ingest from any OTel SDK.
• Traces: End-to-end span waterfalls across every service. Click a log, jump to its span.
• Endpoints: Per-route latency percentiles (P50/P95/P99), throughput, and error rate, ranked by Apdex and a 5-factor impact score.
• Metrics: Host, runtime, and custom metrics. Any dimension, any chart, with custom widget groups.
• Exceptions: Stack traces are normalized, given a SHA-256 fingerprint, and grouped into ranked issues. Source-mapped (webpack, esbuild, Vite).
• Profiling (experimental): Flame graphs for CPU, heap, and goroutines with version-to-version diffing and a top-functions table. Ingests native Go pprof and OTLP profiles.
• Session Replay: Watch what the user did right before the error. Available for web (any JS framework) and Flutter.
• AI Observability: LLM cost, tokens, latency, and full conversations across providers (OpenRouter and any OTel-compatible AI gateway). Calls group into conversations via gen_ai.conversation.id, tool calls are parsed from completions and rendered in the chat view, and multi-language content flagging catches conversations containing terms you care about. Per-customer analytics (conversation length, cost per conversation) key on user.id: set it to a stable customer identifier such as your account or tenant id, the same value across all of that user's conversations, never a session id.
• On-Call & Paging: Rotation schedules with layers and overrides, escalation policies, and pages that escalate until someone acknowledges. Delivered via email, Slack, Pushover, Telegram, or SMS, with one-click acknowledge links that need no login.
• Fleet Overview: One organization-wide page above every project: each reporting instance with live CPU, memory, disk and network, plus issues, monitors and open pages across all projects. Kubernetes nodes group by cluster, and a single kubectl apply instruments a whole cluster.

Plus: background-task (job) monitoring, configurable alerts (Slack / GitHub / email / webhook / Pushover / Telegram), multi-tenant orgs with role-based access, and a per-endpoint slow-threshold override.

AI-First

Your agent sets up Traceway, queries production telemetry, and finds the root cause:

npx skills add tracewayapp/traceway

One command installs two skills into Claude Code, Cursor, Codex, or any agent that reads SKILL.md:

• /traceway-setup reads your repo and wires it up: OTel for backends, Traceway SDKs for web and mobile. Then it verifies data actually arrives.
• /traceway installs the traceway CLI and uses it to query exceptions, logs, endpoints, and metrics, from bug report to root cause.

The CLI is designed for agents first: JSON when piped, tables on a TTY, stable error identifiers and exit codes, --fields to trim responses. It's read-only apart from archiving exceptions, which needs an explicit --yes. Nothing hangs, nothing gets damaged.

The skills are plain Markdown in skills/, in the same MIT-licensed repo. No marketplace, no lock-in. Learn more →

Symbolication

app.min.js:1:63 tells you nothing. Traceway resolves minified production errors back to the original file, line, and function the moment they arrive. The same engine handles stripped and obfuscated mobile crashes: iOS and Swift against the build's dSYM, Android against its R8 mapping.txt, Dart and Flutter against their obfuscation map.

The symbolicator is pure Go and built to keep up with ingest. Every debug artifact (a source map, a dSYM, an R8 mapping) compiles once into a binary .tw file and is memory-mapped from disk. Opening a compiled map takes under a microsecond, p99 lookup stays under a millisecond on a cold cache, and no map is re-parsed after a restart. The corpus is a disk budget, not a RAM budget.

The same engine ships as a standalone OpenTelemetry Collector processor, drop-in compatible with Honeycomb's source_map_symbolicator: same component type, same attribute contract, same config keys. Use it in your own pipeline, with or without Traceway behind it.

Upload source maps from CI with npx traceway-sourcemaps --directory ./dist; dSYMs and R8 mappings post to the same endpoint. Benchmarks live in benchmarks/; run them on your fork. Learn more →

Why Traceway

	Enterprise (Datadog / New Relic)	DIY OSS stack (Prometheus + Loki + Tempo + ...)	Traceway
Pricing	Per-event, per-host, per-seat	Free + ops time	Self-host free, fixed cloud tiers
Setup	Vendor SDK per language	Glue 6 tools together	docker compose up -d
License	Proprietary	Mixed (some BSL / open-core)	MIT, no asterisks
OTel	Wrapped in vendor SDK	OTel Collector required	Native OTLP/HTTP ingest
Replay + traces + AI	3 separate products	Wire it yourself	One system, one trace ID

Quick Start

Self-host with Docker (recommended)

git clone https://github.com/tracewayapp/traceway
cd traceway && docker compose up -d
# ✓ dashboard at http://localhost

Point any OTel SDK at http://localhost/api/otel/v1/traces (or /metrics, /logs) and traces start flowing. See the self-hosting docs for production deployment, TLS, and storage configuration.

Prefer a single container with no external databases? The SQLite image is the smallest deployment. The DuckDB image keeps the same zero-dependency setup but adds a columnar telemetry store for far more dashboard headroom. Run either with docker compose -f docker-compose.sqlite.yml up -d or -f docker-compose.duckdb.yml.

Docker images are cryptographically signed with Cosign.

Embedded mode (inside your Go app)

Run Traceway inside your Go process. No Docker, no external databases, SQLite under the hood:

go get github.com/tracewayapp/traceway/backend

import tracewaybackend "github.com/tracewayapp/traceway/backend"

func main() {
    go tracewaybackend.Run(
        tracewaybackend.WithPort(8082),
        tracewaybackend.WithDefaultUser("admin@localhost.com", "admin"),
        tracewaybackend.WithDefaultProject("My App", "opentelemetry", "dev-token"),
    )

    // ... start your app, point its OTel exporter to http://localhost:8082/api/otel/v1/traces
}

Open http://localhost:8082, log in, and hit your app to see traces appear. Full walkthrough in the embedded mode guide, or check the working examples (OTel exporter or Go client SDK).

Supported Integrations

Traceway integrates with the tools you already use. Backends report over OTLP/HTTP, so any OpenTelemetry SDK works. Browser and mobile apps use the Traceway SDKs.

View the full list in the documentation. Missing a framework? Open an issue to request it.

Backend

OpenTelemetry is the integration path for every backend language. Point your OTLP exporter at Traceway and you are done.