Komari turns a scattered fleet of VPS boxes into one clean status wall that shows which servers are alive, struggling, or about to expire. Every node reports CPU, GPU, memory, swap, disk, load, network speed, traffic totals, and uptime to a real-time dashboard, with history views from ten minutes to thirty days or any custom range. Flip between a card grid and a table, search by name, region, or operating system, and tag each machine with its price, billing cycle, and days until renewal. Latency tasks send ICMP, TCP, or HTTP probes and plot the results in per-node charts. Offline alerts wait out a per-node grace period before firing, expiry reminders warn before a plan lapses, and Webhook and custom JavaScript channels deliver them. A multi-tab browser terminal that reattaches after disconnects, remote command execution, and a remote file manager with an editor let you fix problems without leaving the panel. Agents install with a script, a binary, Docker, or an auto-discovery key for batch rollouts, and administrators can switch an agent's version remotely. Plugins run on an embedded JavaScript runtime and can add scheduled jobs, HTTP hooks, static pages, and notification channels. Administrators can add two-factor authentication, OAuth sign-in, API keys for a JSON-RPC 2.0 endpoint, themes from a theme market, and backups. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Kula watches a Linux server every second and turns CPU, memory, disks, network, containers, and applications into a live dashboard you can open before trouble becomes downtime. Follow total and per-core CPU, load averages, memory and swap pressure, disk I/O, filesystem space, temperatures, GPU load, and network throughput as charts update live in the browser. Drag to zoom into history, switch to focus or TV mode for a wall display, and check the System Info page when you need the hardware story behind a spike. Watch Docker, Podman, and cgroup containers beside host metrics, then add PostgreSQL, MySQL or MariaDB, nginx, and Apache monitoring or define custom metrics for the odd service only your team understands. Scrape the Prometheus endpoint into an existing observability stack, open the terminal UI over SSH for a quick live read, or ask the optional local Ollama assistant to discuss charts without sending data to a cloud service. Protect the dashboard with optional Argon2id logins and multiple users, schedule storage snapshots, and keep the whole tool working on closed networks with no external calls. 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.

Servers, services, and network gear report their health to Icinga 2, the open-source monitoring core that runs checks, evaluates thresholds, and decides who gets woken up. A distributed hierarchy of master, satellite, and agent zones scales from a single box to global estates: satellites execute checks in remote regions and keep working when the master is unreachable, while agents run local checks under TLS-secured, certificate-based trust. The object-based configuration language defines hosts, services, dependencies, and notification rules as code, with apply rules generating checks across whole groups automatically. Performance data streams into Graphite, InfluxDB, or Elasticsearch writers, and Icinga DB carries runtime state and history into Redis and SQL for the web frontends. The REST API drives acknowledgements, downtimes, and check scheduling from scripts and chat tools, with fine-grained permissions down to diagnostic information. The 2.16 line hardens API security, streams richer runtime updates to Icinga DB for the new Icinga Notifications 1.0 incident workflows, and lets operators set exact acknowledgement times through the API. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPL-3.0-or-later 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 7,400+ GitHub stars and a feature set that replaces seven separate SaaS subscriptions — Pingdom for monitoring, StatusPage.io for status pages, PagerDuty for on-call, Incident.io for incident management, Datadog for APM, Loggly for logs, and Sentry for error tracking — OneUptime delivers every tool your reliability team needs in a single open-source platform that is genuinely 100% open source under Apache 2.0 (not open-core). Uptime monitoring runs synthetic checks against websites, APIs, ports, SSL certificates, and DNS records from distributed global probes with configurable intervals and thresholds. Branded status pages publish automatically when monitors detect issues, notifying subscribers via email, SMS, webhook, or RSS without manual intervention during an outage. On-call scheduling routes alerts through escalation policies to the right engineer via phone call, SMS, push notification, Slack, or Microsoft Teams. The incident management workflow handles declaration, triage, communication, resolution, and post-mortem generation in a unified timeline. APM collects traces and metrics via native OpenTelemetry integration — no proprietary agents required — while log management provides full-text search and alerting. An AI agent continuously monitors telemetry data, identifies root causes, and opens GitHub pull requests with proposed fixes for review. Deploy via Docker Compose or Kubernetes Helm charts with a Terraform provider for infrastructure-as-code configuration. 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 31,000 GitHub stars and native OpenTelemetry support that eliminates vendor lock-in from day one, SigNoz delivers full-stack observability covering metrics, traces, and logs in a single pane of glass without the per-host pricing model of commercial APM platforms. The platform ingests telemetry data through the OpenTelemetry Collector, supporting auto-instrumentation for Java, Python, Node.js, Go, Ruby, PHP, and .NET applications with zero code changes required for basic tracing. ClickHouse serves as the columnar storage backend, providing fast aggregation queries over billions of spans and log lines with configurable retention policies and tiered storage. The distributed tracing view renders flame graphs and Gantt charts showing request flow across microservices with latency breakdowns, error rates, and p99 percentile calculations. Custom dashboards support PromQL and ClickHouse SQL queries with time-series charts, bar graphs, tables, and value widgets. The log management pipeline supports structured and unstructured logs with full-text search, log pipelines for parsing and enrichment, and correlation with traces via trace IDs. Alert rules can be configured on any metric or log query with notification channels including Slack, PagerDuty, OpsGenie, webhooks, and email. The exceptions monitoring module automatically groups and tracks application errors with stack traces, occurrence counts, and first-seen timestamps. Service maps visualize inter-service dependencies with real-time latency and error rate overlays. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed with an enterprise edition available.

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.

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.

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.

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.

Small server, small monitoring. Statlite watches your applications and their host with a single binary that idles at about 15 MiB, so the observer never becomes the heaviest thing on the box. Point it at a Spring Boot Actuator endpoint and it polls health plus a fixed, curated set of Micrometer metrics: request traffic, latency, CPU, and runtime memory, all drawn as clean charts. Quarkus, Micronaut, and anything else that can answer a fixed JSON metrics profile can join the same dashboard. History lives in one local SQLite file, raw samples only, kept for 90 days by default, so yesterday's latency spike is still there when you go looking. The dashboard also watches the host itself: processor load, memory pressure, and filesystem capacity, including a warning before the metrics database fills its own disk. Restart detection tells you when an application bounced, and per-target Basic Auth support lets you poll protected Actuator endpoints safely. Configuration is one YAML file listing your targets and polling interval, friendly to systemd and Docker alike. Everything is deliberately scoped: no alert manager, no external service, no observability platform to operate. Just open the page and see whether your apps are healthy. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

When a query crosses its threshold, Nightingale, a self-hosted alerting engine, decides who hears about it and how, without moving data out of the stores you already run. Rules use PromQL, log queries, or SQL against Prometheus, VictoriaMetrics, Elasticsearch, Loki, ClickHouse, MySQL, or PostgreSQL, graded S1, S2, or S3 with a for-duration that absorbs brief spikes. Existing Prometheus alert rules import from YAML. Business groups give each team its own rules and dashboards, and sign-in works through OIDC, OAuth2, LDAP, or CAS. Once a rule fires, mute rules silence the noise, subscriptions add recipients, and event pipelines rewrite labels or route conditionally. Delivery reaches Slack, PagerDuty, Discord, Telegram, Jira, email, DingTalk, Feishu, WeCom, SMS, and voice calls, plus HTTP webhooks and scripts for anything else. Evaluation records, active and historical events, and notification results show what happened at each step. If an alert misbehaves, the built-in AI agent explains why it fired or never arrived, and it drafts rules, dashboards, and mutes from plain-language requests. Claude Code, Cursor, and other MCP clients can query alerts and manage alerting through /mcp, read-only by default and bound by the caller's own permissions. At remote sites, n9e-edge keeps evaluating and notifying when the link to the center drops. 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.

Alertmanager forgets an alert the moment it resolves; Jarvis remembers everything. This web frontend watches all your Alertmanager clusters at once and streams firing alerts into one live view over WebSocket, no refresh as problems appear or clear. Every alert's lifecycle is stored, so the resolved view answers how often something fired and how long it burned, and a grace period keeps a missed poll from being recorded as a phantom resolution. When an alert lands, claim it so the team sees who is on it, and leave comments bound to that alert fingerprint; notes survive restarts and re-fires, so the next person inherits the context. Silencing gets a rehearsal: preview exactly which alerts a silence will hit before creating it, fire a one-click Fast-Silence from the list, and save templates for recurring maintenance. Filters use the Alertmanager matchers you already know, save as named sets, ride in shareable URLs, and one can be your default view. Point Jarvis at every member of an HA gossip cluster and duplicates collapse by fingerprint, while protected upstreams authenticate with OAuth2, bearer tokens or basic auth per cluster. Sign-in is optional through built-in accounts or any OIDC provider, and it runs as one hardened container on port 8080, with PostgreSQL available when you want replicas. Keep it behind your VPN or an authenticating proxy, as its own docs insist. 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.

Your database container is probably not at 98 percent memory, whatever docker stats claims, because most of that figure is reclaimable page cache; ContainerFlow subtracts the full cache and shows the memory your containers actually hold. Point it at a Docker socket and it draws the whole estate as a living map: every Compose project discovered automatically, services grouped and colour coded, and the connections between them inferred, app to database, proxy to app, worker to broker. CPU and memory refresh every three seconds, the graph flashes when a container starts, stops, or restarts, and seven days of metric history wait in a local store when you need to know what happened overnight. Click any node and a detail panel opens with live logs you can filter by stream, an inline terminal that runs commands inside the container, and buttons to start, stop, restart, rebuild, recreate, or remove it. The same panel teaches as it works, flagging containers that run with no memory limit, no CPU limit, or no restart policy, while Discord webhooks fire when a container you care about crosses a threshold you set. 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.

Deploying container updates without blind surprises is what Drydock delivers through a monitor-first inspection plane that evaluates image registries, scans CVE vulnerabilities, and automates rollbacks across distributed Docker infrastructure. Systems engineers track container fleets across twenty-three public and private registries including Docker Hub, GitHub Container Registry, Harbor, and Quay using cursor-based pagination and semver classification. The integrated Update Bouncer runs Trivy and Grype static scanners against incoming candidate layers, blocking deployments that fail configurable CVE severity policies while verifying cryptographic signatures through cosign. Operators configure declarative update schedules with stabilization countdown gates that hold back brand-new releases until defined burn-in periods elapse. When updates execute, Drydock creates pre-upgrade container snapshots and evaluates post-launch container health checks, instantly restoring previous image digests and network configs if failures occur. Distributed Portwing edge agents stream live container output and system logs over encrypted WebSockets, allowing central consoles to coordinate remote daemon updates without opening inbound host firewall ports. Automated event triggers dispatch granular notifications and update payloads across seventeen communication channels including Slack, Discord, Telegram, and Home Assistant MQTT brokers. 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.