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.

Point your routers at Akvorado and every NetFlow, IPFIX, and sFlow record crossing your network becomes a chart you can interrogate. The web console opens on a live summary of flows per second, exporter count, and traffic split by autonomous system, port, protocol, country, and address family. From there, the visualize page turns stored flows into stacked, line, grid, and heatmap time series, plus Sankey diagrams that show how traffic moves between networks, interfaces, and countries. Filters use a simple SQL-like syntax, so a question like which customers pulled traffic over a transit link last night becomes a query, not a support ticket to your future self. Because the outlet polls each exporter with SNMP or gNMI, flows arrive wearing real interface names, descriptions, and speeds instead of raw ifIndex numbers nobody can read. GeoIP lookups attach country and city to addresses, classification rules tag providers, peers, and connectivity types, and optional BMP sessions add AS paths and BGP communities to every flow. Retention is tiered: raw flows keep full detail for recent days while one-minute, five-minute, and hourly rollups stretch summaries across a year of history. A Grafana plugin is available too, so the same flow data can sit on the dashboards your team already watches. 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.

Network traffic stops being a mystery once ntopng names the hosts, applications, and protocols behind every flow, live in your browser. To find the host saturating an uplink, open the dashboard, which ranks top talkers, countries, autonomous systems, and protocols beside historical charts. To see what a suspicious host is contacting, open its page for traffic, ports, DNS queries, TLS details, and visited sites, plus a map of its conversations. Deep packet inspection recognizes applications such as Facebook, YouTube, and BitTorrent, so charts name the app behind the bytes instead of relying on port numbers alone. The console reads packets from a SPAN port or TAP and NetFlow, sFlow, or IPFIX records from routers and switches through nProbe, so it can cover a single switch or many remote sites. Behavioural checks raise alerts for flows, hosts, and interfaces and send them to email, Discord, Telegram, or webhooks. Active monitoring probes remote hosts over ICMP and HTTP/S, and network discovery lists the devices on your local network. A REST API and Lua scripting pull statistics into your own tools and add custom checks. 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.

A flight recorder for production code, Parca profiles CPU and memory continuously and keeps the history to query after something breaks. A slow memory leak or a momentary CPU spike is already on record by the time anyone looks. Point it at any service that exposes pprof endpoints, or deploy the eBPF-based Parca Agent to profile every process on a Linux host or Kubernetes node without touching application code. The agent covers C, C++, Rust, Go, and more. In the web UI, pick a profile type such as on-CPU, narrow it with Prometheus-style label selectors, sum or group by any label, and click a point on the time series to open its flame graph. Switch the same query to a table, add extra panels, or try the alpha Flame Chart and Sandwich views. After a deploy, open the Compare page, set two queries side by side by label or time range, and the functions that gained or lost CPU time stand out as a diff. Native binaries are symbolized from uploaded debuginfo or upstream debuginfod servers. Recent releases add support for OpenTelemetry eBPF profiler profiles and GPU profile types. Optional persistence keeps history across restarts, and a Prometheus-style scrape configuration with service discovery decides what gets profiled. 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.

TapMap draws a computer's live network connections on an interactive world map, so you can watch which applications are talking to which services, where those services sit, and what normal looks like for that machine. A local pipeline scans active sockets, extracts the remote addresses, and enriches them with geolocation from databases stored on the machine itself. Every connection carries the owning application or process, its network operator, and the operating system's verification status for that app, and places that share a location are highlighted when connections overlap. The same view lists local open ports, both TCP listeners and bound UDP sockets, established services on your LAN, and public services whose location could not be mapped. A rolling 30-day history turns raw connections into awareness: an Insights panel surfaces new applications, providers, countries, and ports, plus the most frequent activity, while a Significant Connections log records first sightings and failed verifications. A Daily Activity Report goes further, sorting applications into seen-once, occasional, recurring, and stable patterns, analyzing provider concentration, and charting country activity with detailed timelines. New significant connections can raise a desktop notification or publish to an MQTT broker you configure. Nothing is sent anywhere by default: processing happens locally, with no telemetry. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

NetMap answers the four questions every homelab owner asks in four different tools: what is on my network, what address did it get, is it still up, and why is the firewall shouting about it. Devices you add appear automatically on a visual canvas where you can drag them into place, draw the links between them, and group them into VLANs or separate sites, and the layout is still there when you come back. Behind the map, every device is watched continuously: ping times graphed over history, service checks on the ports you care about, a heartbeat strip that betrays intermittent dropouts, and an uptime percentage that settles arguments. Address management stops being a spreadsheet: define subnets, import the leases your router already handed out, see used and free addresses as a grid, and get warned before a duplicate assignment causes a mysterious outage. Firewall logs stream in live and each entry links to the device it concerns, ready to search by address, port, or protocol. When something new appears, a network scan discovers hosts with their names, hardware addresses, and open ports for review before they join the inventory. 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.

RocketplaneIO is a self-hosted AI SRE platform that gives Kubernetes clusters zero-instrumentation eBPF observability plus a copilot capable of safely diagnosing and fixing issues without your telemetry ever leaving your infrastructure. Point it at any cluster, and an eBPF DaemonSet starts capturing HTTP, gRPC, SQL, Redis, and Kafka spans across every service, including compiled binaries, with cross-service context propagation and no code changes required. The live service map draws itself from actual network traffic, matching technology logos from container images and coloring each node's health from RED metrics. Every log line sits two clicks from its parent distributed trace, and a PromQL query engine, embedded from the real Prometheus evaluator, runs over ClickHouse for long-term metric retention. The complete Kubernetes inventory (Services, Ingress, ConfigMaps, network policies, persistent volumes, CRDs) syncs continuously and is searchable alongside traces and logs. When the copilot identifies a problem, it picks from a catalog of roughly 30 risk-classified safe actions; each action verifies its preconditions, captures a before-state snapshot, executes, checks the result, and rolls back automatically on failure. Disruptive operations pause for explicit human approval before proceeding. An MCP endpoint exposes the identical guardrailed toolbox to external AI agents, so Claude Code or Cursor can operate the cluster through the same safety boundary the browser copilot uses. Complex remediations compose as searchable, forkable Starlark workflows that compile deterministically at save. 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.

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.

The de facto dashboard of observability: Grafana is the open-source frontend that turns the data stores you already run into interactive graphs. It does not store metrics itself; it connects to the data stores you already run and turns their contents into interactive dashboards. Supported sources number over 150 via plugins: Prometheus, Loki, Tempo, InfluxDB, Elasticsearch, MySQL, PostgreSQL, Microsoft SQL Server, AWS CloudWatch, Azure Monitor, Google Cloud Monitoring, and many more. Dashboards are built from a large library of panel types (time series, heatmaps, tables, gauges, logs) with template variables for reusable, parameterized views. Unified alerting evaluates rules against any connected data source, not just Prometheus, and routes notifications to Slack, PagerDuty, email, and other channels with grouping and silencing - unlike Prometheus Alertmanager, a single rule can combine a Loki log pattern, a PostgreSQL query result, and a CloudWatch metric. Dashboards serialize to JSON and data sources configure via provisioning files, so the entire observability setup can live in Git and deploy repeatably across environments. Explore mode adds ad-hoc querying outside dashboards, with split view for correlating a metric spike against the matching log lines, and access control spans organizations, teams, folder permissions, and OAuth, LDAP, and SAML integration. Written in Go and TypeScript, AGPL-licensed. Self-hosting gives you unlimited users, dashboards, and queries at flat hosting cost, without Grafana Cloud's usage-based pricing.

With over 31,000 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.

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.

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.

Enterprise security stacks assume an enterprise budget; Wildbox assumes a server you already own. It runs your whole security operation as a set of cooperating services behind a single HTTPS gateway: threat intelligence collectors pull indicators from seven public feeds on a schedule, starting with abuse.ch's Feodo Tracker, and every indicator is searchable in one place. Fifty-two security tools sit behind one API, covering DNS, TLS, email security, headers, and port analysis. The cloud posture service runs 22 configuration checks against your live AWS accounts and keeps each scan's report, while the vulnerability service inventories your assets, prioritizes findings by risk, and tracks them through remediation with SLA checks and alert rules. When something needs doing, YAML playbooks execute response workflows as background jobs, and the agents service writes Claude-generated threat-enrichment reports for suspicious indicators when you give it an API key. An osquery-based sensor streams endpoint telemetry from your hosts into the platform, kept separate per team. Users, teams, roles, and scoped API keys live in the identity service, and the backends accept nothing that did not arrive through the gateway, so your security data never leaves hardware you control. Optional Compose profiles add n8n automation and Prometheus monitoring. 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 over 14,000 GitHub stars and a growing global network of security deployments, CrowdSec turns every attack on any participating server into protection for the entire community. The security engine operates as a combined IDS/IPS and WAF, analyzing log sources from Nginx, Apache, SSH, WordPress, and over 50 other services to detect brute force attacks, port scans, web vulnerability exploitation, and credential stuffing in real time. When one server detects a new threat, the attacker's IP is shared through the community blocklist, proactively protecting thousands of other installations before the attacker can reach them. The built-in WAF powered by Coraza v3 inspects HTTP requests at the application layer, validates against OpenAPI schemas, and applies custom rules with flexible AND/OR condition mixing for precise threat detection. Bot detection serves challenge pages with client fingerprinting to distinguish legitimate traffic from automated scrapers and scanners. Remediation components block malicious IPs at multiple infrastructure layers including iptables, nftables, Nginx, HAProxy, Cloudflare, and AWS Security Groups through the detect-here-remedy-there architecture. The scenario-based detection system ships with default rules for common attack patterns and supports custom scenarios written in YAML with an expressive filter language. A centralized console provides real-time visualization of alerts, threat intelligence analysis, and management of multiple distributed security engines. GDPR compliant by design, all log analysis happens locally and raw logs never leave your infrastructure. 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 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.