Pulse monitors your entire heterogeneous infrastructure from one screen: Proxmox VE, Proxmox Backup Server, Proxmox Mail Gateway, Docker, Podman, Docker Swarm, Kubernetes, TrueNAS SCALE/CORE, VMware vSphere, and standalone Linux/Windows/macOS machines. The Go binary embeds a SolidJS/TypeScript frontend, delivering WebSocket-driven dashboards with sub-second metric updates on port 7655. A unified agent auto-detects Docker, Podman, Kubernetes, and Proxmox on each host without manual configuration and self-updates silently, while Proxmox nodes need only API credentials with zero agent installation. Smart alerts use adaptive hysteresis-based thresholds to prevent notification floods, pushing to Discord, Slack, Telegram, Teams, email, ntfy.sh, Gotify, and generic webhooks with per-resource overrides. The standout feature is Pulse Patrol: scheduled AI health checks running every ten minutes to seven days using OpenAI, Anthropic, Gemini, or local Ollama models. Patrol catches silent backup failures, capacity creep, restart loops, unhealthy containers, and clock drift that dashboards miss when nobody is watching. Platform-specific views render Proxmox nodes, Ceph clusters, Docker Compose projects, Kubernetes workloads, TrueNAS pools, and vSphere VMs in familiar layouts. OIDC, SSO, and SAML authentication with credential encryption at rest secures access. 6,500+ stars and 441 releases since February 2025. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Reaching 24,000 GitHub stars within two years of its first commit in July 2024, Beszel delivers Netdata-grade monitoring dashboards from a single Docker container with no Prometheus stack, no external database, and no complex configuration — just a one-binary hub on PocketBase (SQLite embedded) and a sub-15 MB agent per host that auto-discovers Docker and Podman containers on contact. The agent connects outbound via WebSocket or SSH tunnel, requiring zero open ports on monitored servers and zero manual network configuration. Per-host metrics cover CPU usage, memory with swap and ZFS ARC breakdown, disk I/O across multiple partitions, network throughput, load average, sensor temperatures, battery charge, and GPU utilization with power draw for Nvidia, AMD, and Intel cards — features that competitors lock behind paid tiers. S.M.A.R.T. disk health including eMMC wear indicators and Linux mdraid array status surface hardware degradation before failures occur. Container statistics track CPU, memory, and network history per container with automatic discovery as new containers start. Configurable threshold alerts notify via email, Discord, Telegram, ntfy, Pushover, Gotify, Matrix, Mattermost, Signal, Slack, Microsoft Teams, and Twilio when metrics exceed defined limits. Multi-user accounts with OAuth/OIDC authentication let teams share monitored systems with role-based access, while automatic backups persist data to disk or S3-compatible storage. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

ServerBee delivers complete fleet monitoring from a single Rust binary that embeds both the server and web UI, requiring no external database or heavy runtime. Lightweight agents installed on each node stream CPU, memory, disk, network, load, temperature, GPU, and disk I/O metrics over persistent WebSocket connections to a central server backed by embedded SQLite. The real-time React dashboard presents 17 drag-and-drop widget types across custom layouts, with historical charts spanning one hour to 30 days and monthly traffic statistics with billing-cycle prediction and cost insights including burn rate and per-resource unit cost scoring. Network monitoring covers ICMP, TCP, and HTTP ping probes, service monitors for SSL certificates, DNS records, HTTP keyword matching, TCP ports, and WHOIS expiration, plus network-quality probing across 96 China 3-ISP and international presets with IP-quality and streaming-unlock detection. Remote management features include a web terminal with sandboxed file manager, Docker container stats with logs and events, firewall configuration, and agent auto-update capabilities. Public status pages display 90-day uptime timelines, while alerting supports email and webhook notifications with flexible trigger expressions. A native iOS companion app provides mobile monitoring access. Deploy via Docker or download the single binary for Linux, macOS, or Windows, 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.

Trusted by millions of engineers and deployed on over 80,000 GitHub stars worth of community confidence, Netdata delivers true real-time monitoring at per-second granularity — 10-60x faster than Prometheus, Datadog, or any conventional monitoring stack that averages away the transient anomalies lasting 2-10 seconds where most production incidents originate. A single installation command deploys the agent with zero configuration, automatically discovering every running process, container, systemd service, network connection, disk, and application on the host within seconds. Unsupervised machine learning trains multiple models per metric directly at the edge, detecting anomalies without thresholds, baselines, or manual tuning. The distributed Parent-Child architecture scales horizontally from a single Raspberry Pi to fleets exceeding 100,000 nodes while maintaining sub-2-second visualization latency and storing metrics at approximately 0.5 bytes per sample through tiered compression. Native network monitoring provides live topology maps, NetFlow and sFlow analytics, SNMP device polling across 200+ profiles, and trap handling — capabilities that typically require a separate NPM product. Hundreds of pre-configured alerts cover systems and applications out of the box, with AI-powered root cause analysis surfacing correlated metrics through natural language via MCP-compatible AI assistants. The agent supports Linux, macOS, FreeBSD, Kubernetes, and Docker with eBPF-based kernel observability requiring no application instrumentation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPL v3+ licensed.

Monitoring everything from network switches to Kubernetes clusters since 2001 with over 6,200 GitHub stars and deployments exceeding 100,000 devices per installation, Zabbix has established itself as one of the most mature and feature-rich open-source monitoring platforms available, trusted by organizations including Dell, Salesforce, ICANN, and T-Mobile. The platform collects metrics from virtually any source using Zabbix Agent written in C, Zabbix Agent 2 written in Go with native plugin support, SNMP v1/v2c/v3 polling and trapping, IPMI for hardware health, JMX for Java applications, SSH and Telnet checks, HTTP/HTTPS polling, and ODBC database queries. Version 7.0 LTS introduced synthetic browser monitoring that executes user-defined JavaScript via WebDriver to simulate multi-step user interactions on websites, proxy load balancing with automatic host redistribution across proxy groups for high availability, in-memory proxy data buffering delivering up to 100x performance improvement, native multi-factor authentication with TOTP and Duo support, and just-in-time user provisioning from SAML and LDAP. Low-level discovery automatically detects file systems, network interfaces, SNMP OIDs, VMware resources, and Kubernetes pods, creating monitoring items and triggers dynamically. The alerting engine correlates events with configurable escalation chains, sending notifications through Slack, Microsoft Teams, PagerDuty, Jira, email, and SMS with customizable message templates. Over 1,000 official templates provide instant monitoring for Linux, Windows, VMware, AWS, Azure, Docker, PostgreSQL, MySQL, Apache, Nginx, and hundreds more. 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.

Instead of deploying proprietary background agents across dozens of target nodes, engineers rely on Apache HertzBeat to monitor real-time infrastructure health, metrics gathering, threshold alerting, and public status pages from a central operations platform. Operations teams can poll hundreds of target services without deploying proprietary background daemons, gathering performance data across Linux hosts, Kubernetes clusters, SQL databases, and network switches using native connection protocols. Engineers can define custom monitoring targets directly within the web dashboard by composing declarative YAML templates that specify polling intervals, parsing expressions, and metric extraction rules. The centralized alert engine processes inbound threshold events, suppresses cascading alert storms during maintenance windows, and dispatches actionable incident notifications to Discord channels, Slack rooms, Telegram groups, and webhook endpoints. Telemetry streams flow into interactive charts with customizable refresh cadences, enabling site reliability engineers to inspect latency waterfalls, correlate log spikes against CPU exhaustion, and track disk capacity trends over extended timeframes. Administrators can also publish real-time public status pages that inform external stakeholders about service availability, scheduled downtime, and ongoing incident resolutions. 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.

Website analytics, uptime monitoring, and server status - three tools most teams run separately - combined in Tianji, an open-source observability platform. The analytics layer tracks page views, unique visitors, referrers, and UTM parameters with a lightweight cookie-less script, which keeps collection GDPR and CCPA friendly. The uptime monitor checks availability and latency on configurable intervals, accepts passively reported results, and publishes public status pages for incident communication. Server status agents report CPU, memory, disk, and network metrics with threshold-based alerts, and notifications route through webhooks, Slack, Telegram, and other channels with noise control. It also includes anonymous telemetry for tracking deployments of your own open-source projects, surveys, waitlists, team collaboration, and an OpenAPI interface for integrations and exports. The consolidation is the point: traffic analytics, uptime checks, and server metrics share one interface and one alerting layer, so diagnosing an incident does not mean hopping between Google Analytics, Uptime Kuma, and Prometheus - and the built-in public status pages replace a separate paid Statuspage-style subscription. Because collection uses no cookies with IP truncation and aggregation by default, basic traffic measurement requires no consent banner. Built in TypeScript under the Apache 2.0 license and inspired by Umami and Uptime Kuma, it is deliberately right-sized for independent developers and small SaaS teams whose monitoring needs are real but lightweight.

Sixty-thousand-plus GitHub stars make Uptime Kuma the most popular self-hosted monitoring tool - MIT-licensed, Node.js, and the standard replacement for UptimeRobot, Pingdom, and Freshping. It watches a dozen monitor types: HTTP(S) endpoints with keyword and JSON-query content validation, TCP ports, ICMP ping, DNS records, WebSockets, Docker containers via the socket, Steam game servers, MQTT brokers, gRPC services, and push-based heartbeats for cron jobs and internal workers. Checks run at intervals as tight as 20 seconds - versus UptimeRobot's 5-minute free tier - with unlimited monitors and unlimited data retention. When something fails, alerts fan out through 90+ notification channels: Slack, Discord, Telegram, email with LiquidJS templating, PagerDuty, OpsGenie, ntfy, Gotify, Matrix, and dozens more via native providers plus the Apprise library. Unlimited public or password-protected status pages - mappable to specific domains and organized into monitor groups - communicate health to customers, with maintenance windows that suppress alerts during planned work. The reactive dashboard graphs response times, tracks SSL certificate expiry with advance warnings, supports proxies and 2FA, and ships in dozens of languages. One Docker container with a SQLite volume covers an entire infrastructure.

With 10,400 GitHub stars, 153 contributors, and no per-monitor pricing to worry about, Checkmate delivers comprehensive infrastructure monitoring from a single self-hosted dashboard — tracking uptime, page speed, server hardware, Docker containers, and even game servers without sending a byte of telemetry off your network. Ten monitor types cover HTTP, ping, TCP, gRPC, WebSocket, DNS, SSL certificate expiry, Docker container health, Lighthouse page speed with Core Web Vitals tracking, and game server status for over 100 server types including Minecraft and CS2. The Globalping integration enables geo-distributed monitoring from six continents, running ping and HTTP checks from Africa, Asia, Europe, North America, South America, and Oceania with results plotted on an interactive map. The optional Capture agent written in Go collects CPU, RAM, disk usage, temperature, and network metrics from any Linux, Windows, Mac, or Raspberry Pi host. Public status pages ship with four built-in themes and custom branding support, showing per-service uptime bars and incident history on a single shareable URL. Alert notifications reach teams through email, Discord, Slack, PagerDuty, Microsoft Teams, Telegram, Matrix, ntfy, Twilio SMS, and webhooks. Deploy via a single Docker Compose file requiring roughly 1 GB RAM — up and running in under five minutes on any Docker host. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPLv3 licensed.

Maintenant replaces three to five separate monitoring tools with a single Go binary that consolidates container discovery, endpoint monitoring, SSL tracking, resource metrics, and public status pages without requiring any external database. The embedded Vue 3 frontend serves on port 8080 immediately after deployment, auto-discovering Docker containers and Kubernetes pods through direct socket and API access without configuration. HTTP and TCP endpoint monitoring validates availability with configurable intervals, while TLS certificate tracking alerts before expiration across all monitored domains. Resource metrics collect CPU, RAM, network throughput, and disk usage per container with real-time Server-Sent Events streaming to the dashboard. Heartbeat and cron monitoring accepts pings from external scheduled jobs, triggering alerts on missed check-ins via webhook callbacks and Discord notifications. The built-in alert engine supports escalation rules and notification batching. Public status pages expose component health to end users without authentication, customizable per monitored service. Network security insights analyze exposed ports, container privilege levels, and host configuration to produce a posture score. Update intelligence scans OCI registries to detect available container image updates with digest comparison. The REST API with SSE broker enables automation, and the integrated MCP server provides tooling for AI assistant integration. SQLite in WAL mode stores all data with zero operational overhead. 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.

CoreObs delivers a unified self-hosted dashboard that replaces the typical combination of Uptime Kuma, Homer, and separate monitoring tools with a single interface for managing your entire server infrastructure. The Next.js frontend with shadcn components provides a modern dark-themed UI displaying server hardware metrics collected by a lightweight Go agent that leverages Glances for hardware abstraction — streaming real-time per-core CPU load, RAM utilization, NVIDIA GPU statistics, disk usage, system uptime, and load averages via WebSocket connections. The application registry tracks all self-hosted services with configurable uptime monitoring, availability history charts, and instant notifications through Discord, Telegram, Pushover, and email when services go down or recover. Quick-access links provide one-click navigation to each application's management panel directly from the dashboard. The network visualization module built on React Flow enables creating visual topology maps of your infrastructure with drag-and-drop nodes representing servers, switches, and services connected by labeled edges. Server data can be organized with tags, copied between entries, and monitored with configurable pagination and compact view modes. Deploy via Docker Compose with three containers — the Next.js web interface, the Go monitoring agent, and PostgreSQL 17 for persistent storage. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Homelable turns your entire homelab into a live, interactive network canvas where every device, link, and service shows its real-time status at a glance. Run an nmap-powered network scan against your subnets and the tool fingerprints services, queues unknown devices for review, and drops approved hosts onto a drag-and-drop canvas with 15 native node types covering routers, switches, hypervisors, NAS boxes, IoT sensors, and more. Import your full Zigbee2MQTT mesh (controllers, routers, end devices with link quality indicators) and Z-Wave JS device trees in one click, preserving the actual RF topology without manual wiring. Proxmox integration pulls in hosts, VMs, and LXC containers so you can nest virtual machines inside their parent hypervisor node on the canvas. The Rack Canvas mode documents the physical side of your lab: create racks with configurable U-height, mount gear into slots, and patch ports across devices to track your cabling. Health checks run every 60 seconds using ping, HTTP, HTTPS, TCP, SSH, or Prometheus scrape endpoints, with WebSocket push delivering green, red, or pending status pulses directly to the canvas. Split your infrastructure across multiple canvases organized by site, rack, or purpose, and share a read-only Live View URL with anyone on your network. A built-in Model Context Protocol server lets AI assistants like Claude query and modify your topology through natural language. Deploy on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. 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.

Trusted by thousands of organizations processing billions of time series data points and backed by 17,000+ GitHub stars, VictoriaMetrics delivers a monitoring and time series database that outperforms Prometheus by 16x on query speed while consuming 2.5x less disk space through its optimized compression and storage engine. The architecture supports both single-node deployments handling 10M+ active time series and a horizontally scalable cluster version with vminsert, vmstorage, and vmselect components providing multi-tenancy, replication, and independent namespace isolation. Data ingestion accepts both push protocols including InfluxDB line protocol, Graphite plaintext, OpenTSDB HTTP, CSV, and OpenTelemetry OTLP alongside pull-based Prometheus scraping and remote write, enabling drop-in replacement of existing monitoring stacks without reconfiguring exporters. MetricsQL extends standard PromQL with additional functions, subqueries, and implicit time range alignment while maintaining full backward compatibility with existing Prometheus alerts and Grafana dashboards. The vmalert component processes recording and alerting rules with Alertmanager integration, while vmbackup and vmrestore enable point-in-time snapshots to S3, GCS, and Azure Blob Storage. Stream aggregation operates as a StatsD alternative for pre-aggregating high-cardinality metrics before storage. NFS-compatible storage backends including Amazon EFS and Google Filestore allow shared persistent volumes across cluster nodes. 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.

Coroot uses eBPF to capture metrics, distributed traces, logs, and continuous CPU profiles directly from the Linux kernel, delivering full observability without any application code changes, SDKs, or sidecars. From the first minute of deployment, an automatically generated service map covers every microservice, database, message queue, and external dependency with request rate, error rate, and latency measurements. When a service breaches its SLO, AI-powered inspections analyze telemetry across all dimensions to pinpoint the root cause and send a single consolidated alert with findings, replacing the flood of fragmented notifications typical of traditional monitoring. Deployment tracking automatically discovers Kubernetes rollouts and compares each release against the previous one to detect performance regressions, resource spikes, and cost impacts without CI/CD pipeline integration. Continuous profiling captures CPU flame graphs down to the line of code with negligible overhead. Integrated cost monitoring tracks cloud spending across AWS, GCP, and Azure, attributing expenses to individual services and deployments. Coroot supports Prometheus, OpenTelemetry, and ClickHouse as data sources and works identically on Kubernetes clusters, virtual machines, and bare-metal hosts. 7,700+ GitHub stars. Apache-2.0 licensed.

When an alert fires on any of your Prometheus Alertmanagers, Karma shows it once, on one filterable dashboard, and lets you acknowledge or silence it from there. Identical alerts from different servers merge into one entry tagged with every server that saw it, HA pairs included. Groups follow the group_by settings of your Alertmanager routes, and shared labels and annotations collapse into a footer. Multi-grid mode gives each value of a label, or each Alertmanager, cluster, or receiver, its own grid, keeping production and staging apart. Configurable label colors make hosts and severities easy to spot. Optional history draws 24 hourly blocks per group from the Prometheus servers that fired it, and an inhibited alert's muted button lists whatever is suppressing it. One click acknowledges an alert with a short-lived silence, and the separate kthxbye daemon can keep extending it until the alert resolves. The silence modal creates, edits, and expires silences, and ticket IDs in comments can become links. A Dead Man's Switch check raises a visible error when the alerting pipeline goes quiet. Basic auth or a proxy's header identifies each user, silence ACLs stop one team from silencing another's alerts, and read-only mode disables silence management. Default filters open the view your team triages first, and light and dark themes follow the browser. 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.

Vigil monitors your entire distributed infrastructure and generates a public status page from a single Rust binary small enough to run on a Raspberry Pi, consuming minimal CPU and memory while providing crash-free reliability. Four distinct monitoring modes cover every topology: poll probes check HTTP, TCP, SSH, and ICMP endpoints for reachability with configurable intervals and thresholds; push probes receive health reports from Vigil Reporter libraries embedded in your application code across Node.js, Python, Golang, Rust, TypeScript, Dart, and C#; local probes delegate monitoring to Vigil Local slave daemons running behind firewalls on separate LANs; and script probes execute custom shell commands for specialized health checks. Each monitored service transitions through healthy, sick, and dead states based on consecutive probe failures, with configurable thresholds controlling state transition sensitivity. When services change state, Vigil dispatches notifications through twelve alert channels including Slack, Email, Twilio SMS, Telegram, Pushover, Gotify, XMPP, Matrix, Zulip, Cisco Webex, and generic webhooks. The generated status page displays service groups organized by category with real-time replica status, system load metrics from reporter probes, and a maintenance announcement system for communicating planned downtime through the Manager HTTP API. Configuration uses a single TOML file defining all probes, services, and notification channels with no database dependency. Docker deployment pulls the official image with volume-mounted configuration. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MPL-2.0 licensed.

Continuous infrastructure monitoring meets automated SSL expiration tracking in Kuvasz, a self-hosted uptime platform that alerts DevOps teams before outages disrupt production operations. Operators can configure granular health checks across HTTP endpoints, ICMP ping targets, and raw TCP ports with custom polling intervals down to seconds. Automated SSL inspectors track certificate validity, issuing early warning notices before cryptographic chains expire and disrupt production traffic. A push monitoring system receives incoming heartbeat signals from background cron jobs, database backups, and recurring automation scripts, triggering alerts whenever expected pings fail to arrive on schedule. Multi-channel dispatchers route incident notifications through Slack, Discord, Telegram, Microsoft Teams, PagerDuty, and custom webhook payloads with adjustable failure count thresholds to eliminate transient false alarms. Maintenance windows let teams schedule planned downtime through one-off intervals or recurring cron expressions, automatically muting notifications during deployment cycles. Public and private status pages publish categorized system health metrics, historical latency charts, and incident timelines to keep internal stakeholders and end users informed. An integrated Model Context Protocol server allows AI assistants to query monitoring states and toggle checks directly via conversational interfaces. 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.