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.

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.

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.

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.

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.

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.

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.

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.

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.

With 20,500+ GitHub stars and over 6,000 organizations running it in production — including a Fortune 100 company ingesting more than 4 PB per day — OpenObserve is the open-source observability platform that replaces your entire Datadog, Splunk, or ELK stack with a single Rust binary deploying in under two minutes. Apache Parquet columnar storage with zstd compression on S3-compatible object storage delivers 140x lower storage costs than Elasticsearch while providing better query performance on a quarter of the hardware. Ingest logs, metrics, and distributed traces via native OpenTelemetry OTLP endpoints with no vendor lock-in. Query logs and traces with standard SQL, metrics with SQL or PromQL — no proprietary query language to learn. The built-in dashboard builder offers 19 chart types including time-series graphs, heatmaps, gauges, tables, and top-K lists with drag-and-drop layout combining data from all signal types. Data pipelines process, enrich, redact, or normalize ingestion streams using Vector Remap Language for real-time transformations including PII redaction and logs-to-metrics conversion. Real User Monitoring captures frontend performance with session replay. The Service Catalog provides topology-based trace analysis with side-panel drill-downs into database queries and error details. Alerting supports real-time and scheduled rules with SQL and PromQL conditions. Native multi-tenancy isolates organizations and streams with complete data separation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPLv3 licensed.

Across logs, traces, and metrics, Monoscope gives engineering teams one self-hosted workspace for finding what broke, asking questions in plain English, and hearing about problems before users do. Start in the Explorer: search events with KQL or an Ask AI prompt, flip between log rows, bar and line charts, log patterns, and sessions, and narrow results with facets for service, level, and HTTP status. Open any span to read its attributes, then follow the full trace across services in a waterfall, timeline, or map view. Live Tail streams new events as they arrive, and the Service Map draws every dependency with its error rate, latency, and requests per second. Build dashboards from widgets with copyable KQL and SQL, then set scheduled monitors with warn and alert thresholds, cron monitors, and uptime checks. An Issues inbox gathers API changes, errors, and log patterns so each one can be acknowledged, archived, or marked as spam, while Reports send scheduled summaries by email. Telemetry arrives over OTLP gRPC on port 4317 from OpenTelemetry SDKs and collectors. The monoscope CLI emits JSON for scripts, and an MCP server at /api/v1/mcp lets Claude, Cursor, and Cline search events and triage issues. Natural-language search uses the OpenAI-compatible model you configure. 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.

An open-source application performance monitoring platform for microservices, Kubernetes, and service meshes, Apache SkyWalking draws the live service map and ties slow requests to their traces, logs, and metrics. Agents cover Java, .NET Core, PHP, Node.js, Go, Lua, Rust, C++, browser JavaScript, and Python, and OpenTelemetry, Zipkin, Prometheus, Zabbix, and Telegraf data can be ingested too. Start at the service topology map, follow a request through the trace waterfall, then drill into the instance and its API dependencies. When the cause is inside the code, trace profiling, async-profiler, Go pprof, eBPF, and network profiling render flame graphs and process graphs in the same console. The Rover eBPF agent profiles Kubernetes workloads for CPU and network problems, and Istio and Envoy service meshes, including Istio Ambient, report into the same dashboards. Alarm rules target a service, deployment, or API, and alarms and telemetry can be forwarded to third-party systems. Metric and log analysis rules hot-update at runtime without a restart, and a live debugger shows what each rule stage receives and produces. An AI assistant answers plain-language questions with charts, topology, and traces from live data, using an OpenAI-compatible or Amazon Bedrock model you configure, and an MCP connection serves your own AI client. 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.

Backed by 44,000 GitHub stars and trusted by over four million developers, Sentry is the debugging platform that captures errors, traces, replays, profiles, and metrics from your applications and connects them all through distributed tracing. The error tracking engine captures full stack traces with source context, breadcrumbs, and automatic demangling for native crashes, while intelligent grouping consolidates duplicate events into actionable issues with regression detection and automatic assignment. Performance monitoring instruments your frameworks automatically, capturing every database query, API call, cache hit, and queue operation as spans within distributed traces that flow across frontend, backend, and mobile boundaries. Session Replay produces video-like recordings of real user sessions showing DOM interactions, network requests, console messages, and errors on a synchronized timeline, with AI-powered summaries that describe what happened without watching the full replay. Continuous profiling captures CPU execution data at the function and line level for Node.js, Python, iOS, and Android, linking slow spans directly to the exact code responsible. Cron monitoring tracks scheduled jobs for failures, missed runs, and duration anomalies. The alerting engine fires notifications through Slack, PagerDuty, Opsgenie, and webhooks on new issues, regressions, error spikes, or when latency and crash-free session rate thresholds are crossed. Self-hosted deployment runs as a Docker Compose stack with PostgreSQL, ClickHouse, Kafka, Redis, and Relay. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. FSL licensed.

GlitchTip speaks Sentry's protocol without Sentry's operational weight - open-source error tracking that your existing SDKs already understand. The pitch is pragmatic: instrument your application with the official Sentry SDKs you already know - any language they cover - and point the DSN at your own GlitchTip instance instead. Errors, exceptions, log messages, and Content Security Policy violations flow into one place for triage, grouped into issues with stack traces, with alerts delivered by email or webhook the moment things break. Where self-hosted Sentry has ballooned into a docker-compose stack of twenty-plus containers, GlitchTip is a deliberately lean Django and PostgreSQL application a small team can actually run. Beyond errors, it bundles three more monitoring concerns: performance monitoring takes a works-out-of-the-box approach - no dashboard building, just your slowest web requests, database queries, and transactions surfaced automatically; uptime monitoring pings your sites and alerts on failures, or runs in reverse as a dead-man's-switch heartbeat for cron jobs that must check in on schedule; and log search puts application logs alongside errors for faster debugging. Unlimited projects and team members, MIT-licensed, built by Burke Software - your event volume is limited only by your own hardware.

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.

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.