> ## Documentation Index
> Fetch the complete documentation index at: https://docs.molesignal.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> One place for logs, metrics, and traces — self-hosted, OpenTelemetry-native, without Datadog pricing.

**MoleSignal** is a self-hosted, OpenTelemetry-native observability platform. Logs, metrics, and
traces share **one storage layer** (Parquet on object storage), **one query engine**
(DataFusion + Arrow), and **one metadata layer** (Postgres) — so a trace, its logs, and the host
metric of the same minute are *actually* connected, not stitched together by hand.

<Note>
  MoleSignal is pre-1.0 and under active development. Expect rough edges, and please
  [open an issue](https://github.com/molesignal/molesignal/issues) — every report shapes the next release.
</Note>

## Why MoleSignal

Today's telemetry tools force a bad trade-off:

* **Commercial SaaS** (Datadog, New Relic, Splunk) correlates the three signals, but the bill grows
  linearly with traffic — a mid-size team easily pays **US\$2k–10k/month** for 100 GB/day.
* **Open-source stacks** (Loki + Mimir + Tempo, or ELK + Prometheus + Jaeger) are free, but logs,
  metrics, and traces live in **three separate stores with three query languages**. The
  "trace ↔ log ↔ host metric" jump everyone needs during an incident has to be stitched by hand.

MoleSignal takes the third path: the three signals are correlated **at the data plane**, not at the
dashboard plane. Self-hosted, so your bill is the S3 cost.

|                             | Commercial SaaS | OSS stack            | **MoleSignal**                |
| --------------------------- | --------------- | -------------------- | ----------------------------- |
| 100 GB/day cost             | \~US\$2k+/mo    | infra only           | **infra only**                |
| Three signals, same storage | ✅ (their cloud) | ❌ 3 stores           | **✅ Parquet + DataFusion**    |
| Cross-signal correlation    | ✅ (paid)        | ⚠️ manual copy-paste | **✅ native**                  |
| Data ownership              | their cloud     | self-hosted          | **self-hosted**               |
| Setup time                  | 5 min           | 6 hours+             | **1 cmd `docker compose up`** |
| Real-time alerts (\<1s)     | yes             | no                   | **yes (`kind: realtime`)**    |

## Get started

<CardGroup cols={2}>
  <Card title="Quickstart" icon="rocket" href="/en-US/quickstart">
    Spin up a sandbox, send your first telemetry, and run a cross-signal query in minutes.
  </Card>

  <Card title="Core concepts" icon="diagram-project" href="/en-US/concepts">
    Orgs, streams, signals, and how correlation works under the hood.
  </Card>

  <Card title="Ingesting data" icon="inbox" href="/en-US/ingestion">
    10 drop-in ingest protocols: OTLP, Prometheus, Loki, Elasticsearch, and more.
  </Card>

  <Card title="Querying" icon="magnifying-glass" href="/en-US/query">
    Full SQL and a PromQL subset over one engine, across all three signals.
  </Card>
</CardGroup>

## Key capabilities

* **Cross-signal correlation** — drill `metric → trace → log → host` and back without losing context.
* **10 ingest protocols** — drop-in replacements for OTLP, Prometheus remote\_write, Loki, Elasticsearch `_bulk`, Syslog, and more.
* **One query engine** — DataFusion SQL with joins/CTEs/window functions, plus a PromQL subset.
* **Alerting** — `scheduled`, `realtime` (fires \<1s), and `anomaly` rules with escalation policies.
* **Multi-tenant & secure** — planner-level org isolation, API tokens, audit log, field-level encryption.
* **Operations** — 6 stateless roles, single binary, Kubernetes manifests, Prometheus `/metrics`.