Documentation

Welcome to Lighthouse

Lighthouse monitors your business metrics — from Snowflake, BigQuery, or Postgres — and sends Slack alerts the moment something moves. These docs cover everything from initial setup to advanced threshold configuration.

How Lighthouse is organized

Data SourceYour warehouse connection — Snowflake, BigQuery, or Postgres. One per warehouse.

DatasetA table or view within a data source. Defines which columns can be used as metrics, filters, and segments.

MetricA measurement you want to monitor — e.g. "Daily active users, COUNT of user_id." Each metric belongs to one dataset.

ThresholdA rule configured on a metric that sends a Slack or email notification when the value breaches a condition. Thresholds are configured inside the metric — not a separate object.

Data Source→Dataset→Metric→Threshold

⚡

Quickstart

Connect your warehouse, create a metric, and get your first Slack alert in under 10 minutes.

Get started →

🔌

Connect a Warehouse

Snowflake, BigQuery, Postgres, and SQL Server — read-only credentials, connection test required.

Warehouse setup →

📊

Create a Dataset

Point at a table or view and configure which columns can be metrics, filters, and segments.

Dataset guide →

📈

Creating Metrics

Business metrics with aggregations and time windows, or custom SQL — with filters, data lag, and schedules.

Metric guide →

✨

AI Features

Dataset suggestions, metric AI optimization, and the Metric Assistant chat interface.

AI guide →

🔔

Thresholds & Alerts

Absolute, percent-change, and standard deviation thresholds with configurable gating and severity.

Thresholds guide →

💬

Slack Integration

Connect your workspace and understand what each alert message button does.

Slack guide →

🔐

Roles & Permissions

Org-level admin vs member roles and per-resource access control lists.

Permissions →