Logging every drive, charge, and idle stretch of a Tesla to a database you own, TeslaMate shows where the battery went, including degradation, vampire drain, and charging cost. Battery health comes first: the dashboard estimates usable capacity, range lost, and degradation against mileage. Idle losses come next, with Vampire Drain listing how much charge disappears during every idle period and a States view recording every online, asleep, and offline stretch. The car is left alone to fall asleep, so logging adds no extra vampire drain. Charging sessions show curves, energy added and used, efficiency, and cost, using per-location prices attached to geo-fences drawn on a map. Each drive records second-by-second speed, power, elevation, and temperature, plotted on a route map beside tire pressure and consumption charts. Trip, Drives, Efficiency, Drive Stats, Mileage, Updates, Statistics, and a lifetime driving map fill in the rest. Live vehicle data goes out over MQTT to Home Assistant, Node-RED, and Telegram, and old history imports from TeslaFi or tesla-apiscraper. Several vehicles on one Tesla account work together, addresses are looked up automatically, and the web interface offers light, dark, or system themes in 19 languages. Sign-in uses Tesla access and refresh tokens that TeslaMate encrypts with a key you set. It works best on an always-on server. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Whether it is a delivery van, a trailer in a storage yard, or a dog on a hike, Traccar is the GPS tracking server that puts it on one live map you host and control. Every position and event lands in your own SQL database. Over 200 protocols covering 2000+ tracker models decode out of the box, so a Teltonika fleet unit and a budget dongle share one device list. Pick a device to see speed, address, ignition, and total distance. Routes replay on a timeline slider, and a ruler tool measures distances. Geofences can be polygons, polylines, or circles, linked to devices or groups, colored as you like, and limited by calendar schedules. Alerts for overspeed, fuel drops, offline devices, alarms, and maintenance arrive by web, email, push, SMS, Telegram, or WhatsApp. Reports cover trips, stops, summaries, charts, events, and positions, with Excel export and scheduled email delivery. Commands go out over the tracker's own connection or by SMS, queued for offline devices. Computed attributes derive ignition or fuel values from raw inputs using expressions. Resellers get admin, manager, user, and read-only roles with device limits, plus white-label branding. Traccar Client lets a smartphone report as a tracker, and Traccar Manager monitors devices from mobile. Teams who want AI assistants to query their devices can add the MCP endpoint, which is optional. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Every DJI and Litchi flight you have ever logged becomes a searchable dashboard on your own server with Open DroneLog, a free, open-source alternative to DroneLogbook, Airdata UAV, and Flight Reader. Drop in DJI .txt logs, Litchi CSV files, or Airdata CSV exports and units are detected automatically, while deduplication on drone serial, battery serial, and start time lets you re-import a folder without duplicate flights. Each flight opens as a 3D terrain map with satellite, topographic, and OpenStreetMap layers, then replays from 0.5x to 16x speed with live telemetry and an RC joystick overlay. Synchronized charts plot height, speed, battery cell voltages, attitude, RC signal, GPS, and distance to home, with drag-to-zoom. Filters narrow flights by date, drone, battery, controller, duration, altitude, distance, tag, or map area, and automatic tags such as Night Flight and Low Battery arrive with offline reverse-geocoded locations. The overview dashboard adds an activity heatmap, per-drone and per-battery charts, and a cluster map. Battery health bars track cycle counts and capacity history, and maintenance thresholds show as color-coded progress bars. Export flights as CSV, JSON, GPX, or KML, build printable HTML flight reports that save as PDF, or generate a FlyCard image for social media. A sync folder imports new logs automatically, pilot profiles can sit behind passwords, and full-database backup and restore moves data between desktop and Docker. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

When Clarkson, the once-popular fuel logger, stopped receiving updates, Hammond stepped in as its logical successor - a self-hosted vehicle expense tracker. Written in Go with a Vue.js interface and SQLite storage - a single lightweight container, no external database - it tracks every cost your vehicles generate: fuel fill-ups with cost, volume, and odometer readings; maintenance and repairs; and arbitrary other expenses, each attachable with photos and documents stored against the vehicle. The multi-user, multi-vehicle design is what sets it apart from phone apps: a household or small business adds all its vehicles and all its drivers, shares vehicles across users, and every fill-up lands in one ledger no matter who was driving. The Quick Entries feature respects how expenses actually happen - snap a photo of the receipt or pump screen at the gas station, then complete the structured entry later when you have a minute. Reporting works at both the vehicle level (cost per distance, fuel economy trends) and across the whole fleet. Migration matters here: importers for Clarkson, Fuelly, and Drivvo bring years of fill-up history along, so switching does not mean starting your data over.

May is a self-hosted dashboard that tracks everything your vehicles cost and everything they are about to need, from fuel fill-ups to the MOT renewal you would otherwise forget. Log a fill-up and consumption in L/100km or MPG calculates itself, with a quick-entry mode for the forecourt and receipts attachable to every record. Cars, vans, motorbikes, and scooters each get their own history: expenses by category, recurring insurance and tax payments, trip logs for mileage claims, tire sets with distance worked out per set, and maintenance schedules driven by mileage, engine hours, or dates. Reminders for MOT, service, insurance, and tax arrive by email, ntfy, Pushover, or webhook, and subscribe into Apple, Google, or Outlook calendars. The analytics dashboard charts spending trends and consumption statistics, while PDF reports package a vehicle's whole story for record-keeping, receipts included. Vehicles share between family or team accounts with full, fuel-and-charging-only, or read-only roles. UK drivers get DVLA MOT and tax lookups plus live forecourt prices for saved stations from government feeds, no API key required. Documents, favourite stations, Fuelly CSV import, full JSON and CSV export, custom units and currencies, and a Home Assistant integration complete the garage. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Vehicle maintenance records shouldn't live in a homemade spreadsheet and a shoebox of receipts - LubeLogger exists because of exactly that. It's a self-hosted .NET web application (from Hargata Softworks) that gives every vehicle in your garage a complete digital history: service, repair, and upgrade records categorized and searchable, with invoices and receipts attached as documents; fuel fill-ups that compute economy in MPG, UK MPG, L/100KM, or KM/L without spreadsheet tedium; taxes, odometer logs, inspections, equipment, and supplies inventory for tracking the parts and fluids on your shelf. The reminder system is what saves engines: recurring reminders trigger by date, odometer reading, or whichever comes first - exactly how real service intervals work - so oil changes and timing belts stop relying on memory. A dashboard summarizes expenses by year, month, and category, a planner tracks to-dos by type, priority, and progress, and professional vehicle reports print a full history - genuinely useful when selling a car. Collaboration is built in: invite household members as collaborators on shared vehicles, with single sign-on support. Custom fields adapt records to your needs, CSV import/export moves data freely, an API enables automation, and the mobile-tested UI installs as a PWA on iOS and Android. MIT-licensed.

Your house already has lights, locks, sensors, thermostats, and speakers from many brands, and Home Assistant gives them one local control room with no vendor cloud in the loop. To close the shutters when the outdoor temperature holds above 25 °C, or to be alerted when the garage door is left open, build the routine in the visual editor: When, And if, Then do. Scenes, scripts, and blueprints package it for reuse, and run traces show what it did. More than 1,500 integrations cover Zigbee, Z-Wave, Matter, Thread, MQTT, ESPHome, Bluetooth, Hue, and Sonos, and network discovery offers known devices for one-step setup. To see the house at a glance, drag tile, thermostat, gauge, graph, and map cards into a dashboard, then put it on a TV with Home Assistant Cast. The Energy dashboard answers where the power goes, drawing solar, grid, battery, gas, and water as one distribution diagram with cost totals and per-appliance tracking. To talk to the house, use Assist: natural-language commands, wake words, and custom sentences run locally or through Home Assistant Cloud. The map panel shows who is home, plotting people against zones such as Home, Work, and School from the iOS and Android companion apps. Areas and labels keep large setups tidy, and multi-factor authentication guards each account. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

With over 31,600 GitHub stars and thousands of production deployments, InfluxDB 3 Core is the open-source time series database rebuilt in Rust on the FDAP stack — Apache Flight for high-throughput data transfer, DataFusion for vectorized SQL query execution, Arrow for columnar in-memory representation, and Parquet for compressed columnar storage. The engine delivers sub-10ms query response times on recent data and handles millions of writes per second through line protocol ingestion over HTTP, with unlimited tag cardinality eliminating the high-cardinality limitations that plagued earlier InfluxDB versions. The diskless architecture persists data as compressed Parquet files to S3-compatible object storage, Azure Blob, Google Cloud Storage, or local disk with configurable partitioning strategies, while the write-ahead log and in-memory buffer serve real-time queries against recent data before compaction. Native SQL support through DataFusion includes window functions, CTEs, subqueries, and joins, while InfluxQL maintains backward compatibility with existing InfluxDB 1.x and 2.x applications through the same query API. The embedded Python VM enables processing engine plugins and triggers that execute custom logic on write events, perform cross-database queries, and transform data in real time without external tooling. Flight SQL clients provide high-performance query access from Python, Go, Java, and Rust, and the HTTP API supports writes in line protocol format compatible with Telegraf's 300+ input plugins. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT/Apache 2.0 dual-licensed.

The de facto dashboard of observability: Grafana is the open-source frontend that turns the data stores you already run into interactive graphs. It does not store metrics itself; it connects to the data stores you already run and turns their contents into interactive dashboards. Supported sources number over 150 via plugins: Prometheus, Loki, Tempo, InfluxDB, Elasticsearch, MySQL, PostgreSQL, Microsoft SQL Server, AWS CloudWatch, Azure Monitor, Google Cloud Monitoring, and many more. Dashboards are built from a large library of panel types (time series, heatmaps, tables, gauges, logs) with template variables for reusable, parameterized views. Unified alerting evaluates rules against any connected data source, not just Prometheus, and routes notifications to Slack, PagerDuty, email, and other channels with grouping and silencing - unlike Prometheus Alertmanager, a single rule can combine a Loki log pattern, a PostgreSQL query result, and a CloudWatch metric. Dashboards serialize to JSON and data sources configure via provisioning files, so the entire observability setup can live in Git and deploy repeatably across environments. Explore mode adds ad-hoc querying outside dashboards, with split view for correlating a metric spike against the matching log lines, and access control spans organizations, teams, folder permissions, and OAuth, LDAP, and SAML integration. Written in Go and TypeScript, AGPL-licensed. Self-hosting gives you unlimited users, dashboards, and queries at flat hosting cost, without Grafana Cloud's usage-based pricing.

On the factory floor, the data already exists; it is just locked inside machines, PLCs, and protocols nobody on the analytics team speaks. StreamPipes unlocks it with guided adapters for OPC UA (including a web-based node browser), MQTT, Kafka, Pulsar, REST services, and industrial controllers, turning each source into a live stream in minutes. Domain experts then drag those streams into the pipeline editor, chain processors and sinks on a canvas, and watch connection validation check schema compatibility as they build, with live preview showing real values before anything is saved. Pipelines filter, enrich, aggregate, and route machine data, raise alerts, and write results to the built-in time-series data lake, where the data explorer charts history and spots trends. Finished pipelines run under an overview that starts, stops, and bulk-manages them, while detail views expose logs, metrics, status, and the pipeline as code. Live dashboards carry the same data to shop-floor screens and operations centers, organized around assets so a line, a cell, or a single machine becomes the navigation unit. Developers extend everything with custom adapters, processors, and sinks built on the Java SDK and deployed as microservices, or drive the platform from Python, Go, and Java clients. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

Thousands of devices speaking four different protocols is where IoT projects usually dissolve into glue code; Magistrala replaces that tangle with one platform where MQTT, HTTP, WebSocket, and CoAP clients share a single identity, provisioning, and messaging model. You organise work into domains, register clients for devices and applications, and connect them to channels that control who publishes and who subscribes, with fine-grained policies deciding which client may touch which channel. Protocol adapters bridge the transports, so a sensor publishing over MQTT and a dashboard reading over WebSocket meet in the same channel without translators in between. Telemetry lands in TimescaleDB through dedicated writer services and comes back out through reader APIs, while the bundled three-node FluxMQ cluster carries the messaging load with mutual TLS on device connections. The rules engine reacts to incoming messages with conditions and actions, alarms flag the readings that breach them, and reports package fleet data for the people who never open a terminal. A Community web UI covers domains, clients, channels, messages, and rules for day-to-day operation, and everything deploys as one Docker Compose stack with Prometheus metrics and Jaeger tracing already wired in. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

evcc turns surplus rooftop solar and the cheapest hours of a dynamic tariff into cheap, clean kilometers by coordinating an EV charger, heat pump, and home battery from one local dashboard. Each charging point offers Off, Smart, and Fast modes. In Smart mode, charging starts once the surplus covers the car's minimum power, follows the sun up and down, pauses when clouds win, and can switch between one and three phases on wallboxes that allow it. A solar share slider lets small systems start earlier, and Always charge keeps fussy cars from being interrupted. Set a departure time and a target charge, and a charging plan picks the cheapest or cleanest hours before it, repeating weekly if you like. Tibber, Awattar, fixed and time-based rates, dynamic feed-in prices, and CO2 and solar forecasts all feed those decisions. A home battery can claim the surplus first or lend a boost for fast charging, and load management keeps several chargers inside a circuit's current limit while honoring grid operator dimming. Hundreds of wallboxes, inverters, meters, heat pumps, and vehicle APIs are supported, including Tesla, BMW, Mercedes-Benz, Skoda, and Volkswagen. Sessions land in a history with charts and CSV export, and REST, MQTT, InfluxDB, Grafana, Home Assistant, and openHAB link evcc to the rest of the house. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.