Why This Was a Big Deal

Getting Started with Docker

Linux Native Install

Where This Actually Helps

A Few Rough Edges

Fitting It Into Your Stack

Should You Try It? If you've been following TapMap's development, you probably already know the single biggest complaint from the community: "Cool tool, but where's the Linux support?" Well, as of the latest update, TapMap now officially supports Linux and Docker deployments. And honestly, it's about time. TapMap has quietly become one of the better network and infrastructure mapping tools out there. It gives you a visual representation of your services, connections, and dependencies — basically a living architecture diagram that actually stays up to date. The problem? It was stuck on macOS and Windows for way too long. If you're running production infrastructure, chances are your servers are Linux boxes. Wanting to run your infrastructure mapping tool on the same OS as your actual infrastructure isn't exactly a wild ask. The Docker support sweetens the deal even more — now you can spin up TapMap as just another container in your stack. The Docker setup is refreshingly simple. No weird volume mount gymnastics, no custom networking hacks. Here's what a basic docker-compose.yml looks like: Run docker compose up -d and you're good. Hit localhost:8080 and you should see the dashboard. I had it scanning my home lab network within about three minutes of pulling the image. If Docker isn't your thing (no judgment... okay, a little judgment), the native Linux install is straightforward too: One thing I noticed — if you're running on a headless server, make sure you're passing --host 0.0.0.0 instead of relying on the default localhost binding. I spent a solid ten minutes wondering why I couldn't reach the UI from my laptop before I remembered that classic gotcha. I've been running TapMap on a small Kubernetes cluster for about a week now, and the thing that surprised me most is how useful it is for onboarding. We had a new dev join the team, and instead of spending an hour walking through our service mesh on a whiteboard, I just shared the TapMap dashboard URL. They could see every service, how they connect, and which ones talk to external APIs. A few scenarios where Docker deployment really shines: Let's be honest — this is a first release on these platforms, and it shows in a couple of places. The auto-discovery agent is a bit aggressive on resource usage during initial scans. On a Raspberry Pi 4, my first full scan pegged the CPU at 100% for about two minutes. After the initial map is built, subsequent scans are incremental and much lighter, but heads up if you're running on constrained hardware. Also, the Linux build doesn't support the system tray integration that macOS and Windows have. You get a systemd service or a foreground process, which is fine for servers but slightly less convenient on a Linux desktop. One pattern I've found useful is pairing TapMap with your existing auth and monitoring tools. If you're already using something like Grafana for metrics, TapMap fills a different niche — it's not showing you how your services are performing, it's showing you what's connected to what and whether that matches your expectations. For authentication on the dashboard, you'll want to put it behind a reverse proxy with proper auth if you're exposing it beyond localhost. Tools like Authon, Authentik, and Keycloak can handle the SSO layer so you're not rolling your own login page for yet another internal tool. Here's a quick nginx snippet to proxy TapMap behind basic auth as a starting point: If you're managing more than a handful of services and you've ever drawn a network diagram that was outdated by the time you finished it — yeah, give TapMap a look. The Docker deployment makes it a zero-commitment experiment. Pull the image, run it for a day, see if the auto-generated map matches your mental model of your infrastructure. I bet it won't, and that's exactly the point. The Linux and Docker support turns TapMap from a "cool desktop app" into something you can actually run in production environments where it's most useful. It's not perfect yet, but the foundation is solid, and the team seems responsive to community feedback — after all, this entire release exists because people asked for it on GitHub and Reddit. I'll probably do a deeper write-up once I've run it in production for a month or so. For now, the Docker route is the easiest way to kick the tires without committing to anything. Templates let you quickly answer FAQs or store snippets for re-use. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse