Web analytics
Deploy Umami
Privacy-focused website analytics with a small runtime and PostgreSQL-backed data.
Why use it
See which pages and campaigns bring visitors without adding a large analytics stack.
Build plan
- Add a Dockerfile pinned to a released Umami image or build the upstream source.
- Create managed PostgreSQL and pass its connection string as DATABASE_URL.
- Generate APP_SECRET, expose port 3000 and use /api/heartbeat for health checks.
Resources and values
Resources
1 ServicePostgreSQLRequired values
DATABASE_URLAPP_SECRETCheck before you deploy
Change the default administrator password as soon as the first deployment is live.
Ask your coding agent
Deploy Umami on aidrop from a small repository with a pinned production image. Create managed PostgreSQL, configure DATABASE_URL and generate a strong APP_SECRET. Run the service on port 3000, use /api/heartbeat as the health path and deploy it. Do not store application data on the container filesystem. Return the public address and the first-login steps.
Put Umami online
Connect your coding agent, paste the quickstart and keep the build, runtime and public address in one aidrop Project.
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