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.

VyManager puts every VyOS router you run, across every site, into one web control plane with live dashboards and per-site permissions. Organize instances into logical sites, from the datacenter core to the smallest branch office, and add or remove routers without touching a command line. Live dashboards stream interface counters, system information, network graphs, and WireGuard peer status, so a saturated link announces itself before your users do. Configuration adapts to each router's VyOS version, with 1.4, 1.5, and rolling releases supported side by side during the longest upgrade cycle. Access is granted per site with OWNER, ADMIN, and VIEWER roles, API keys authenticate the machines, and SSH credentials stay encrypted at rest. A setup wizard walks a fresh deployment to its first managed router, and light, dark, and custom themes keep the night shift comfortable. For automation, AI assistants can be connected through the companion MCP integration, and the whole stack arrives as Docker Compose services you can redeploy in minutes. 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 licensed.

When checkout slows to a crawl somewhere across forty services, Pinpoint draws you the map of what is actually talking to what and where the time went. The ServerMap renders your whole topology live: services, databases, message queues, and external APIs as nodes whose edges carry transaction counts and error rates, so the unhealthy dependency announces itself visually. Click a node and the scatter chart plots every request against its response time; drag across the suspicious cluster and the CallStack opens those exact transactions at code level, method by method, SQL statement by SQL statement, until the bottleneck has nowhere to hide. The Inspector watches each application's CPU, memory, garbage collection, TPS, and JVM arguments, while realtime active-thread charts show stuck work as it happens. Agents attach to Java, PHP, and Python applications without changing a line of code, and applications already instrumented with OpenTelemetry send their traces straight in over OTLP. Group applications into services so each team sees its own Service Map, then arm alarm templates for slow counts, error rates, and thread saturation before users notice. Error Analysis gathers exceptions and error logs grouped by route, and URI metrics rank your hottest endpoints by cost. 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.

Created by Uber Technologies and graduated as the seventh CNCF top-level project in October 2019 with over 23,000 GitHub stars, Jaeger has become one of the most widely deployed open-source distributed tracing platforms, processing billions of spans per day in production environments at organizations including Uber, Red Hat, and Shopify. Version 2 rebuilt the platform on the OpenTelemetry Collector framework, inheriting its extensible pipeline architecture while implementing Jaeger-specific features as extensions and components, enabling seamless integration with the OpenTelemetry ecosystem through native OTLP protocol support. The platform stores traces in Cassandra 4.0+, Elasticsearch 7.x/8.x, OpenSearch 1.0+, ClickHouse, or the embedded Badger database for development setups. Three sampling strategies control trace volume: head-based sampling with constant, probabilistic, and rate-limiting modes, tail-based sampling using the OpenTelemetry Collector processor that evaluates complete traces before storage decisions, and adaptive sampling that dynamically adjusts probabilities based on observed traffic patterns. Service Performance Monitoring computes RED metrics directly from spans, displaying request rates, error rates, and latency percentiles in the Monitor tab with drill-down from aggregate service views to individual traces. The web UI provides trace search with multi-field filtering, trace detail views with span timeline visualization, trace comparison across services, and dependency graphs mapping service relationships from actual traffic. Deployment options range from a single all-in-one binary for development to distributed collector-ingester-query configurations with Kafka intermediate buffering for production scale. 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.

When a ClickHouse cluster slows down, the answers are buried in system tables nobody wants to query by hand; CHMonitor turns those tables into an operations dashboard that explains what the cluster is doing and what to fix next. Live views cover running queries with elapsed time, memory, and a kill action, while history, failed, slowest, and most-expensive pages rank finished work by CPU, duration, and rows read, each with the full statement and one-click EXPLAIN. Thread-level analysis shows how a single query parallelized, and per-user summaries reveal which analyst or service is eating the cluster. Beyond queries, you get a merge and part-lifecycle timeline, replication queue and Keeper health, a live topology map of shards and replicas, storage breakdowns by database, table, and part, and a query activity heatmap spanning a year. An AI advisor reviews the workload and recommends skip indexes, projections, PREWHERE clauses, and TTL changes ranked by impact, with an MCP interface and built-in agent for asking questions in plain English; it recommends only and never applies DDL. Threshold-based health checks alert to Slack, Discord, PagerDuty, or Opsgenie, multiple ClickHouse hosts are watched from one dashboard, and a companion terminal UI covers quick checks from the shell. 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 licensed.

Pipedash unifies pipelines from twelve CI/CD providers into one self-hosted dashboard for watching statuses, reading job logs, and triggering, rerunning, or cancelling runs without opening each provider's site. Connect GitHub Actions, Gitea Actions, GitLab CI, Azure DevOps, Bitbucket, Buildkite, Jenkins, Tekton, ArgoCD, FluxCD, Komodo, or Prow, and every workflow lands in one list grouped by repository. Filters narrow by status, provider, organization, or time range, and saved views with rules, sub views, and pins give each team its own shortlist. Run history records each attempt with its commit, branch, actor, and duration, and opening a run reveals its jobs and a searchable log viewer that streams live output. Trigger forms load the workflow's own inputs, pipeline variables, or job parameters from the provider, so parameterized runs start with real values. Reruns reuse the original inputs, GitHub runs can restart only failed jobs, and stuck builds can be cancelled singly, in bulk, or by repository. Metrics charts track duration, success rate, and run counts per pipeline by hour, day, week, or month with P95 and P99 values. A notifications inbox gathers failures, degraded workloads, long running builds, and provider outages, while health panels place status pages beside the pipelines they describe. Every dashboard action is a REST API route under /api/v1 with bearer authentication, provider tokens stay encrypted at rest, and the server sends no telemetry. 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 licensed.

When the domain you want is already taken, Domain Watchdog tracks its history, warns you as it changes, and can try to register it as soon as it becomes available. Searching any domain returns its registrar, status, nameservers, and registration events from RDAP, the structured JSON successor to WHOIS. A timeline lays out the full lifecycle, from creation through renewals and transfers to final deletion, while deletion forecasting orders tracked domains by their expected drop window. Watchlists group domains with the events that matter, send alerts by email or as webhooks to Slack, Mattermost, or Discord, and publish an iCal feed plus RSS feeds for events and EPP status. Attach a connector for OVH, Gandi, Namecheap, AutoDNS, or Name.com, and an expired domain on the watchlist triggers an order attempt through that provider's API. The app also lists ICANN-accredited registrars and TLDs, and rate limiting with caching minimizes RDAP requests. Administrators can cap watchlists, domains per watchlist, and webhooks per watchlist, toggle public RDAP lookups, and add custom static content to the instance. Scripts can manage watchlists and connectors, search domains, and request user tokens through the documented REST API. 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.

Foreman is the control room for a server fleet, taking machines from blank hardware or an empty VM to configured, monitored hosts through one web interface. Create a host entry and it network-boots by PXE or UEFI HTTP, or starts from a discovery image that phones home its hardware inventory so unknown machines can be claimed and built by rule. Installation runs from templates for Kickstart, Preseed, AutoYaST, Agama, and cloud-init, while host groups bundle the operating system, partition layout, and parameters that make every build of a role identical. The same console provisions onto bare metal, libvirt, VMware, oVirt, Amazon EC2, Google Compute Engine, and OpenStack, because each provider plugs in as a compute resource with its own images and networks. After installation, Puppet classes and parameters, Ansible roles with recurring runs, or Salt states keep configuration enforced, and the reports and facts those tools send back fill dashboards showing which hosts are current, which drifted, and which are erroring. Smart Proxy services carry DHCP, DNS, TFTP, and configuration enforcement into each subnet or datacenter segment, remote execution runs jobs across the fleet, and the Katello plugin adds content and patch management on top. Hammer gives the whole API a command-line face, and role-based access with LDAP or FreeIPA sign-in keeps large teams in their lanes. 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 licensed.

GoAccess processes millions of web log entries in seconds and renders the results as interactive dashboards that update every 200 milliseconds in the terminal or every second via WebSocket-connected HTML reports. Written entirely in C with only ncurses as a dependency, it achieves exceptional performance even on resource-constrained servers, reducing memory usage by approximately 20% and parsing time by 35% in recent releases through optimized in-memory hash tables with on-disk persistence support. The analyzer parses virtually every web log format out of the box (Apache Combined and Common, Nginx, Amazon CloudFront, Amazon S3, AWS Elastic Load Balancing, Google Cloud Storage, Squid, W3C IIS, Caddy JSON, and Traefik) while supporting fully custom log format strings for non-standard configurations. The self-contained HTML dashboard displays 15+ interactive panels covering unique visitors, requested files, static files, 404 errors, referring sites, search keyphrases, geographic location with city-level GeoIP resolution, operating systems, browsers, HTTP status codes, time distribution, and virtual host metrics. WebSocket authentication via JWT provides secure remote access, and incremental log processing ensures data continuity across daemon restarts. Docker deployment requires a single command with volume-mapped access logs. Over 20,800 stars with active development since 2010. 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 production alert fires at 3 a.m., Regen is the self-hosted on-call and incident management platform that makes sure a human answers it, keeping alerts, incidents, schedules, and escalations on one shared timeline instead of split across three tools. Alerts stream in from Prometheus Alertmanager, Grafana, AWS CloudWatch, or any webhook, and deduplication collapses repeat firings before Regen opens an incident automatically; responders can also declare one by hand and let AI draft the title and summary. Layered on-call rotations absorb overrides, holidays, and leave, while multi-step escalation policies with timeouts keep paging the next person until somebody acknowledges, so a critical page never dies in one inbox. The incident timeline syncs to Slack and Microsoft Teams, where bot commands acknowledge, escalate, and post updates without leaving chat, and Telegram notifications cover teams that live there instead. One-click summaries and handoff digests brief the incoming shift, editable postmortem drafts are assembled from the timeline using your own templates, and similar past incidents resurface with what worked last time. AI is bring-your-own-key through OpenAI, Anthropic, or a local Ollama model, and the platform loses nothing core if you never enable it. Schedules and escalation policies import in one click from PagerDuty, Grafana OnCall, or Opsgenie, SAML single sign-on through Okta, Azure AD, or Google Workspace is free, and nothing caps your incidents, schedules, or postmortems. 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.

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.

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.

Browser tests, load tests, uptime checks, public status pages, and an AI incident investigator all live in one self-hosted dashboard called Supercheck. Write browser, API, database, custom, and k6 performance tests in a built-in code editor, or record a flow with the Chrome and Edge Recorder extension and save it as a Playwright script. Group tests into scheduled jobs, trigger them from CI with trigger keys, and review run logs, screenshots, traces, and reports. Five monitor types cover HTTP endpoints, website SSL expiry, ping, TCP and UDP ports, and scheduled synthetic browser journeys, with administrator-defined check locations and alerts to email, Slack, Discord, Telegram, Microsoft Teams, or webhooks. Status pages publish component health with 90-day uptime, incidents, scheduled maintenance, badges, and subscriber notifications under a subdomain or custom domain. When something breaks, the incident workspace collects evidence, drafts an evidence brief, and runs a read-only AI investigation across connectors such as GitHub, Prometheus, Grafana, and Kubernetes, while Copilot answers questions about that evidence. Requirements link expectations to tests and show coverage, and AI can extract them from a PRD. Organizations, projects, six roles, API keys, and audit trails keep teams in their lanes, and the CLI pulls, diffs, and deploys resources as code. 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.

Parseable replaces expensive Elasticsearch clusters and fragmented monitoring stacks with a single Rust binary that ingests, queries, and stores logs, metrics, and traces on commodity object storage at a fraction of the cost. The data lake architecture decouples stateless compute from S3-compatible storage, enabling independent scaling of ingestion throughput and query capacity while cutting storage costs by up to 90% compared to indexed alternatives. OpenTelemetry-native OTLP ingestion accepts telemetry from existing OTel collector pipelines, Prometheus Remote Write endpoints, Kafka consumers, eBPF probes, and popular logging agents including Fluentd, Fluent Bit, and Vector without proprietary format conversions. The SQL-first query interface enables cross-signal analysis across all telemetry types, while native PromQL support with 50+ functions and 12 aggregation operators provides Prometheus-compatible metrics querying that works directly with Grafana dashboards. Built-in features include customizable dashboards, real-time alerting with Webhook, Slack, and Alertmanager targets, role-based access control, OpenID single sign-on integration, LogIQ automatic unstructured-to-structured log transformation, smart caching for frequently accessed data, and retention policies for lifecycle management. AI-powered Keystone Q&A provides natural language to SQL conversion and dataset summarization. All data stored as standard Apache Parquet on object storage remains accessible to any Parquet-compatible engine (DuckDB, Spark, Trino), ensuring zero vendor lock-in. Deploys on AWS S3, Azure Blob, Google Cloud Storage, MinIO, Wasabi, and DigitalOcean Spaces. 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.

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.

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.

With 11,400+ GitHub stars and active development since 2019, Gatus is the developer-oriented status page and health monitoring tool that ships as a single statically-linked Go binary in a scratch Docker image under 20 MB — deploying in seconds while monitoring your entire infrastructure across 12 protocols from a single YAML configuration file. Define health checks for HTTP, ICMP, TCP, DNS, gRPC, WebSocket, SSH, UDP, SCTP, STARTTLS, and TLS endpoints with conditions that go far beyond simple ping: evaluate response status codes, body content with JSONPath expressions, response time thresholds, certificate expiration days, DNS record values, and IP address ranges. Each endpoint supports independent alerting through Slack, Microsoft Teams, PagerDuty, Discord, Telegram, Twilio, Mattermost, Google Chat, email, Gotify, Pushover, and custom webhook providers with configurable failure thresholds and descriptions. The built-in status page displays uptime badges, response time graphs, and incident timelines with maintenance window support for planned downtime communication. External endpoints accept push-based health reports from services behind firewalls. Prometheus metrics export via the /metrics endpoint enables integration with existing observability stacks. OIDC and Basic Authentication protect the dashboard. PostgreSQL persistence stores historical uptime data. The official Helm chart supports Kubernetes deployment with liveness probes and PVC storage, while a community sidecar auto-generates endpoint configurations from Kubernetes Ingress and HTTPRoute resources. 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.

Breeze is an open-source RMM and PSA platform for MSPs that watches every managed device, and its built-in AI operator investigates alerts and drafts fixes for your approval. See live CPU, memory, disk, and network health for the whole fleet, with hardware and software inventory on every Windows, macOS, and Linux endpoint. Approve and deploy operating system and application patches in rings and maintenance windows, or push scripts and software to hundreds of devices at once. Open a remote terminal, browse files, or take over the desktop with multi-display support when a user needs hands-on help. Network discovery scans each site for unmanaged devices, while configuration policies and drift checks keep machines aligned with your baseline. Tickets, time entries, quotes, and invoices live beside the device work, so a resolved issue becomes a billable record without a second system. Clients get their own portal to raise requests and follow progress, and the multi-tenant structure keeps every customer separate from day one. When the AI operator acts, tiered approvals and a full audit log show exactly what it did and who allowed it. 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.