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.

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.

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.

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.

With over 16,500 GitHub stars and a track record powering connected vehicle fleets, smart city sensor networks, and industrial IoT deployments, EMQX is the MQTT messaging platform engineered to handle 100 million concurrent device connections in a single cluster while processing millions of messages per second with sub-millisecond latency. The protocol stack supports MQTT 5.0, 3.1.1, and 3.1 with full QoS 0/1/2 support, shared subscriptions, retained messages, and will messages, plus MQTT over QUIC for faster connection setup, reduced head-of-line blocking, and seamless connection migration on mobile networks. The gateway framework extends connectivity to MQTT-SN, CoAP, LwM2M, STOMP, and ExProto for bridging legacy industrial protocols. The SQL-based rule engine processes and transforms messages in real time with over 50 pre-built integrations including Kafka, PostgreSQL, MySQL, MongoDB, InfluxDB, TimescaleDB, ClickHouse, Redis, AWS Kinesis, GCP Pub/Sub, and Azure Event Hubs. The visual Flow Designer creates data processing pipelines without code. Built on Erlang/OTP with a masterless distributed architecture using Mria for state replication, the cluster separates Core nodes for data consistency and Replicant nodes for client-handling workloads. Authentication supports username/password, JWT, PSK, X.509 certificates, and LDAP with configurable ACL rules. The built-in dashboard provides real-time monitoring of connections, subscriptions, topics, message rates, and cluster health. Deployment runs via Docker, Kubernetes with the EMQX Operator, or native packages. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSL 1.1 licensed.

Over 400 technologies and thousands of smart devices from any manufacturer, unified under one roof: openHAB is the vendor-neutral home automation platform with a pluggable binding architecture. Each binding translates a device or service into openHAB's clean abstraction: Things expose Channels, Channels link to Items, and Items feed a rules engine that runs your home. That engine meets you at your skill level: Blockly gives non-programmers drag-and-drop visual logic, JS Scripting (GraalJS with the openhab-js library) is the modern text-based standard, the classic Rules DSL remains supported, and JSR223 opens the door to Python, Ruby, and Groovy. Time- and event-based triggers, scripts, notifications, and voice control compose into automations of any complexity, and users report decade-old rule sets still running rock solid. The Main UI handles configuration, semantic modeling, and now built-in charting - no external Grafana required. Built in Java on Apache Karaf's OSGi runtime and stewarded by the non-profit openHAB Foundation, it requires no cloud to function: everything runs locally, talking directly to your devices. Optional connectors bridge to Alexa, Google Assistant, and HomeKit, with iOS, Android, and web apps for control from anywhere.

Wire nodes together in a browser, deploy in one click, and real-time data flows from sources through transformations to outputs: Node-RED is the OpenJS Foundation's flow-based programming tool for event-driven applications. Born at IBM as a proof-of-concept for manipulating MQTT topic mappings, it has become the lingua franca of IoT and automation glue - home automation, industrial control, edge data collection - with a community library of over 5,000 contributed nodes and flows covering protocols, devices, and services. Where visual wiring runs out, JavaScript function nodes written in a rich in-editor code editor take over, and every flow serializes to importable, exportable JSON that shares cleanly and version-controls sensibly. Version 5.0 (2026) delivered the largest editor overhaul in the project's history: a rethought layout with Explorer and Information panels in a split sidebar, a native dark theme with theme variants, improved accessibility, and refreshed node appearance. The runtime is lightweight Node.js, exploiting the event-driven non-blocking model so the same flows run on a Raspberry Pi at the network edge or a cloud VM. Apache-2.0 licensed with 240+ contributors, it pairs naturally with dashboard nodes for live charts and controls.