Tesla collects enormous amounts of data from your car. TeslaMate lets you collect it yourself, on hardware you control, with dashboards you can actually use.
If you own a Tesla, your car generates a continuous stream of telemetry: location, battery state, charge sessions, drive efficiency, tire pressure, climate usage, and more. Tesla uses this data for its own purposes. You, the person who paid for the car, get a simplified view through the Tesla app. TeslaMate, an open-source project that connects to Tesla's API, flips that dynamic: it logs everything to a database on your own hardware, visualizes it through Grafana dashboards, and keeps your data entirely under your control.
I've been running TeslaMate on a Raspberry Pi for over a year. Here's what you need to know to get started, what actually works well, and where you'll hit friction.
Why Self-Host Your Tesla Data
The case for self-hosted logging has gotten stronger as Tesla tightens its software ecosystem. As we reported earlier this year, Tesla discontinued its Autopilot package in February and moved basic driver assistance features behind a $99/month FSD subscription. That subscription push signals a broader pattern: Tesla increasingly treats vehicle features and data as recurring revenue opportunities, not things you buy once and own.
Self-hosted logging is a counterweight to that trend. TeslaMate gives you a permanent, queryable record of your vehicle's behavior. You can track battery degradation over years, analyze your real-world efficiency across seasons, monitor charging costs, and build automations through MQTT integration. If you ever sell the car, you have a complete maintenance and performance history — and if Tesla changes its app or API access, your historical data stays put.
There's also a privacy angle. Tesla's own data collection is extensive, and the company's track record on data handling hasn't always inspired confidence. Running your own logging means your location history and driving patterns live on your network, not Tesla's servers.
What You Need to Get Started
TeslaMate runs as a set of Docker containers: the main application, a PostgreSQL database, Grafana for dashboards, and an MQTT broker (Mosquitto) for real-time data streaming. The official TeslaMate documentation provides a Docker Compose file that spins up all four services with a single command.
Hardware
You don't need much. A Raspberry Pi 4 with 4GB of RAM handles the workload comfortably. I've also run it on a mini PC (Intel N100-based) that doubles as a general home server. Any Linux machine with Docker support works. If you already run a NAS like Synology or Unraid, TeslaMate can run there too.
Expect the database to grow to a few gigabytes per year of logging. A 64GB SD card on a Pi is fine for a single vehicle, though I'd recommend an SSD for longevity. SD cards wear out under constant database writes.
Software Setup
The Docker Compose setup is genuinely straightforward. You create a docker-compose.yml file, set a few environment variables (encryption key, database credentials, timezone), and run docker compose up -d. As outlined in the TeslaMate Docker install guide, the default configuration gets you running on your local network with minimal effort.
Here's the critical security note from the documentation: this default setup is intended for home network use only. Your Tesla API tokens are stored in the application, and exposing TeslaMate to the internet without proper security is a real risk. The project recommends using a VPN (Tailscale or WireGuard), Cloudflare Tunnel, or a reverse proxy with TLS and authentication if you want remote access. There are advanced guides for setting up Traefik or Apache2 with HTTP Basic Auth.
Tesla API Authentication
TeslaMate connects to Tesla's API to pull vehicle data. You'll need to authenticate with your Tesla account during initial setup. The project encrypts your tokens locally using the encryption key you set in the environment variables. Change the default secretkey to something strong — this protects your Tesla account credentials at rest.
What You Actually Get
Once TeslaMate is running, it polls your car's state every few seconds when the vehicle is awake and logs everything to PostgreSQL. Grafana serves pre-built dashboards that cover the major use cases.
Battery and Charging
The battery degradation dashboard is the single most useful view. It plots your battery's usable capacity over time, giving you a real trendline instead of guesswork. After a year of data, I can see that my Model 3's battery has degraded roughly in line with what the community reports — a steep initial drop followed by a long, slow decline. This is data Tesla doesn't surface in its app.
Charging history tracks every session: location, energy added, cost (if you configure rates), duration, and charge curve. If you charge at home on a time-of-use electricity plan, you can calculate exactly what you're spending per mile.
Driving Efficiency
Each drive is logged with distance, energy consumed, average speed, outside temperature, and calculated efficiency. Over months, you can see how cold weather hammers range (in my case, roughly 30% in a Midwest winter) and how highway versus city driving affects consumption. This is the kind of longitudinal data that's genuinely useful for trip planning.
Location and Privacy
TeslaMate logs GPS coordinates for every drive and park event. This is powerful for tracking where you've been, but it's also exactly the kind of data you don't want exposed. Keep your instance locked down. The geofencing feature lets you name locations (home, work, favorite charger) and filter dashboards accordingly.
Where It Gets Tricky
TeslaMate isn't without friction. A few areas where I've spent real troubleshooting time:
Vampire drain and sleep management. TeslaMate needs to poll the car to get data, but polling keeps the car awake, which drains the battery. The project has built-in sleep detection that backs off polling when the car is idle, but getting the balance right takes some tuning. If you also use the Tesla app frequently or have other third-party integrations hitting the API, the car may never sleep properly.
API changes. Tesla has historically changed its API without much warning. TeslaMate's maintainers have kept up, but there have been periods where updates broke authentication or data collection. The project now supports Tesla's Fleet API for business fleet users, but individual users still rely on the older API path. How long that remains stable is an open question.
Grafana learning curve. The pre-built dashboards are excellent. Customizing them requires learning Grafana's query editor and PostgreSQL syntax. It's not insurmountable, but it's a real time investment if you want bespoke views.
Data migration and backups. The project includes backup and restore documentation, but moving between hardware (say, from a Pi to a proper server) requires careful handling of the PostgreSQL database. I've done it twice. It works, but test your backups before you need them.
The Bigger Picture: Your Car, Your Data
The impulse to self-host vehicle telemetry connects to a broader tension in how automakers treat data. Tesla is far from the only company collecting extensive vehicle data, but it's arguably the most aggressive at monetizing the software layer. Understanding what your car is actually doing — how the battery is aging, what your real efficiency looks like, where your energy costs go — shouldn't require reverse engineering.
The Tesla hardware hacking community has pushed this even further: security researcher David Schütz documented running a Tesla Model 3's computer on his desk using parts from crashed cars sourced on eBay, where MCU units go for $200–$300. His work, part of Tesla's bug bounty program, shows just how much of the vehicle's intelligence lives in a surprisingly compact computer — and how accessible that hardware is to anyone willing to dig in.
TeslaMate sits at a more practical point on that spectrum — no need to pull apart a car. You need Docker, a spare machine, and an afternoon. The payoff is a complete, private record of your vehicle's life that no subscription change or app update can take away.
If you're the kind of person who tracks your home energy usage or runs a Pi-hole, TeslaMate is a natural fit. If you've never touched Docker, it's a reasonable first project — the documentation is solid, and the community (primarily on Discord and GitHub) is active. Start with the default Docker Compose setup on your home network, get comfortable with the dashboards, and expand from there.
Your car is already logging everything. You might as well have a copy.
