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

When 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.

HyperDX correlates logs, metrics, traces, session replays, and errors in a single interface so engineers can resolve production incidents in minutes instead of hours. Nearly 10,000 GitHub stars reflect its role as the integrated UI layer for the ClickStack blueprint endorsed by ClickHouse. The platform connects to any ClickHouse cluster as its storage backend, working with existing table structures without requiring data migration or proprietary ingestion formats. An intuitive Lucene-like search syntax supports full-text queries and property filtering like level:err or service.name:api without needing SQL, while native JSON string querying and event delta analysis surface anomalies in high-cardinality datasets. One-click cross-signal correlation lets you jump from a log line to its distributed trace, from a slow span to associated logs, or from a frontend session replay to the backend errors it triggered. The OpenTelemetry Collector accepts telemetry via OTLP on gRPC port 4317 and HTTP port 4318, supporting automatic instrumentation for Node.js, Python, Java, Go, Ruby, and browser applications. APM tracks HTTP request latency, database query duration, and external service calls with trace waterfall visualizations. Configurable alerts trigger via webhook, Slack, PagerDuty, or email when thresholds are breached. Deploys via Docker Compose with ClickHouse, MongoDB, Redis, and the OpenTelemetry Collector. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Pinpoint distributed system bottlenecks across polyglot microservices using Uptrace, an open telemetry monitoring platform that correlates traces, metrics, and logs inside a unified diagnostic dashboard. Engineers can track end-to-end request flows across polyglot microservices, inspecting database queries, third-party API calls, and internal function calls with sub-millisecond precision. The platform automatically aggregates spans into high-level latency percentiles, highlighting p50, p90, and p99 bottlenecks while calculating baseline error rates across production deployments. Integrated log correlation links log entries directly to parent trace spans, eliminating the friction of manual search across separate monitoring tools during active outages. You can construct custom dashboard views using a visual query builder, monitor cluster nodes, and map out upstream and downstream service dependencies with interactive topological graphs. Automated alerting channels notify on-call teams via Slack, Telegram, webhooks, or email whenever error budgets or metric thresholds trigger an incident. 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.

Production debugging slows to a crawl when logs, distributed traces, metrics, and session replays live in four disconnected dashboards, which is why Traceway consolidates every OpenTelemetry signal into a single self-hosted observability platform. Point any standard OTLP exporter directly at the ingestion endpoints without maintaining an intermediary collector or installing proprietary vendor SDKs. When an unhandled exception fires in production, automatic SHA-256 stack trace fingerprinting groups duplicates into prioritized issues complete with source-mapped frames and attached browser or Flutter session replays showing exact user clicks before the crash. Clicking any structured log entry jumps straight to its corresponding distributed span waterfall so engineers can trace slow database queries or failing downstream HTTP calls across microservices. Route performance bottlenecks surface immediately through per-endpoint P50, P95, and P99 latency percentiles ranked by Apdex and a five-factor impact score. Teams shipping AI features can also inspect LLM token consumption, model costs, tool calls, and multi-turn conversations grouped by customer identifier. Built-in on-call rotation schedules, escalation policies, and multi-channel alerts via Slack, Telegram, Pushover, email, and webhooks ensure incidents reach the right responder with one-click acknowledgment links. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT 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.

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.

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.

When an alert fires on any of your Prometheus Alertmanagers, Karma shows it once, on one filterable dashboard, and lets you acknowledge or silence it from there. Identical alerts from different servers merge into one entry tagged with every server that saw it, HA pairs included. Groups follow the group_by settings of your Alertmanager routes, and shared labels and annotations collapse into a footer. Multi-grid mode gives each value of a label, or each Alertmanager, cluster, or receiver, its own grid, keeping production and staging apart. Configurable label colors make hosts and severities easy to spot. Optional history draws 24 hourly blocks per group from the Prometheus servers that fired it, and an inhibited alert's muted button lists whatever is suppressing it. One click acknowledges an alert with a short-lived silence, and the separate kthxbye daemon can keep extending it until the alert resolves. The silence modal creates, edits, and expires silences, and ticket IDs in comments can become links. A Dead Man's Switch check raises a visible error when the alerting pipeline goes quiet. Basic auth or a proxy's header identifies each user, silence ACLs stop one team from silencing another's alerts, and read-only mode disables silence management. Default filters open the view your team triages first, and light and dark themes follow the browser. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

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.

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.

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.

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.

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.

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.

Define a service level objective in a few lines of YAML and Pyrra writes the Prometheus recording rules and multi-window burn rate alerts for it, then tracks the remaining error budget in a web interface. An objective can be an error ratio or a latency target, declared as a Kubernetes custom resource or as a plain file read from disk when running under Docker or as binaries. Grouping labels fan one definition out into an objective per route or handler. The objectives page lists each SLO with its window, target, availability, and remaining budget, sorted so the worst offenders sit on top; columns can be sorted or hidden, and a search box or a click on any label filters the list. Opening an objective highlights availability and error budget, plots the budget over time, and charts requests, errors, and duration with a time range picker and absolute or relative scales. Below the charts, a table shows the four generated alerts with their severities. Generated alerts carry a link back to the objective's page, and severities can be overridden in the spec. Queries go to Prometheus, Thanos, or Mimir, with basic auth, bearer tokens, or tenant IDs, and ready-made Grafana dashboards chart the same objectives. 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.

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.

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.