Install

TreeAlarm VMS runs two ways: with Docker on Linux, or with a native installer on Windows. Both give the same web interface on port 5134.

Downloads

Everything else, including older versions: releases.

Docker on Linux

The deployment repository pulls prebuilt images from Docker Hub. You do not need a source checkout to run the product.

Requirements

• Linux host with Docker Engine and Docker Compose v2
• Ports listed below available
• Disk space for the archive — recording fills whatever you give it

Run it

git clone https://github.com/treealarm/ta_install
cd ta_install
# edit .env — see the next section
docker compose --env-file .env up -d

Or unzip ta_vms-docker.zip, cd ta_vms, and run the same docker compose command.

The first start takes a while as images are pulled. When it settles, open:

http://<host>:5134

Settings you must change

Everything lives in .env. The stack ships with working defaults so it starts unattended; do not expose it before replacing them.

The database and broker passwords must match their copies in the Dapr component files; db-init checks them on every start and stops the stack if they diverge.

Login and users

The stack runs its own Keycloak. The first sign-in is admin / admin; change that password in the web interface. Add users at http://<host>:8013 — new users, password resets, the administrator role. Keycloak’s own console is at http://127.0.0.1:8180, with the administrator password from .env.

Ports

Adding the first camera

Nothing is pre-configured. A default storage volume, a default media router and three recording profiles are created automatically on first boot — the rest is up to you.

Open the web interface and add a camera either through ONVIF discovery or by entering an RTSP URL. To turn on detection: Admin → Analytics, add a watch for the camera and stream and pick the classes. Arming is not required for that — arming controls recording on alarm, not whether the system looks at the picture.

Stopping

docker compose --env-file .env down

Recordings, detection crops and the database live under ./data on the host and survive this. Adding -v wipes them.

Hardware acceleration

Archive re-compression and live HEVC→H.264 transcoding both run on an integrated GPU when there is one. Neither requires it — the CPU path works — but the live transcode measured 43% less CPU per stream on VA-API, and that is the largest sustained cost in the recorder. It needs /dev/dri passed into the container; the deployment repository ships docker-compose.gpu.yml.example for exactly that.

Windows

The Windows installer needs no Docker and runs the services as native Windows services. It supports Windows 10 1809 / Server 2019 or later, x64. Run it as an administrator; it installs the VC++, .NET and ASP.NET Core runtimes it needs. The MSI is for Group Policy or Intune on machines that already have those runtimes.

The first sign-in is admin / admin; users are added at http://<this machine>:8013. The database, recordings and configuration live in C:\ProgramData\TreeAlarm\VMS and survive upgrades and uninstalls. The analytics worker is not part of the Windows build; use the Docker deployment if you need it. The release notes list what else the Windows build leaves out.

Windows installer and release notes →

Licensing and source

The VMS is MIT-licensed; its source, issues and feature requests are at ta_vms. The analytics worker is video_a, AGPL-3.0, because the bundled YOLO26 detectors are AGPL-3.0; the face detector (OMZ face-detection-0205) is Apache-2.0. The Docker images bundle third-party software under its own licences, among it FFmpeg with GPL-licensed encoders.

Source and tools

• ta_vms — the VMS source (MIT)
• video_a — the analytics worker (AGPL-3.0)
• OnvifSim — an ONVIF camera simulator for testing without hardware
• OnvifLib — the ONVIF client library the services use
• roi_transcode — the hardware video encoding library

📩 Stuck? Contact us