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.

With 3,900 GitHub stars, 140 contributors, and 380 releases since its 2022 launch, Grafana OnCall delivers developer-friendly incident response that routes alerts from any monitoring system to the right engineer at the right time through the right channel. The platform accepts alerts via unique API URLs from Alertmanager, Grafana Alerting, Zabbix, Datadog, Pagerduty-compatible sources, Jira, inbound email, and generic HTTP webhooks, then applies routing templates to direct each alert to the appropriate escalation chain. Escalation chains define notification sequences — notify the primary on-call via Slack, wait 5 minutes, escalate to SMS and phone, wait 10 minutes, page the secondary on-call and notify the engineering manager — continuing until acknowledgment or resolution. On-call schedules support multi-layer rotations with overrides, shift swaps, and timezone-aware handoffs rendered directly inside Grafana dashboards. ChatOps integration publishes alert groups to Slack channels and Telegram groups with interactive buttons for acknowledge, resolve, and silence actions. Template engines based on Jinja2 control alert grouping, appearance rendering, and behavioral automation. The REST API enables programmatic management of integrations, schedules, and escalation policies. Deploy via Docker Compose with PostgreSQL, Redis, and Celery workers alongside your existing Grafana instance. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GNU AGPL v3 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.

OpsiMate gives on-call teams one queue for alerts that would otherwise arrive in five different dashboards, each demanding attention in its own tab. Connect Grafana, Datadog, Zabbix, Uptime Kuma, Google Cloud, or any custom webhook source and watch incoming alerts land in one table with their source, service, severity, tags, and status attached. Filter the noise down to the team or service you own, group related alerts so one incident does not look like forty separate emergencies, and use mute policies when a known problem should stop paging people. Acknowledge work with one click, assign ownership so nobody wonders who is responding, resolve alerts from the same screen, and follow deep links back into Grafana or Zabbix when you need the original chart or trigger. Let supported integrations auto-resolve alerts when the underlying monitor recovers, and use root-cause notes and insights to keep the next responder from starting at zero. Discover services running in Docker, Kubernetes, and Linux virtual machines so the alert queue stays connected to the infrastructure behind 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.

When an alert fires, OnGrid investigates it for you: an AI operations agent that correlates metrics, logs, traces, and topology, then names the root cause in plain language. A coordinator agent hands each question to specialist SRE, network, or database sub-agents, and the incident investigator walks the service graph for blast radius, queries Prometheus, Loki, and Tempo, and pins the cause to a line of source code before posting its report back to chat. Lightweight edge agents on every host dial out over a single tunnel, so no inbound ports are opened, and operators can reach any machine through an audited browser shell. The agent works through more than 26 read-only inspection tools in a sandbox, while anything that changes production waits behind an approval gate. Ask questions or receive reports in Slack, Telegram, Larksuite, DingTalk, or WeCom, and run it on Anthropic, OpenAI, GLM, DeepSeek, Gemini, Kimi, or any OpenAI-compatible endpoint. A workflow builder turns triggers, agents, tools, and notifications into repeatable automations, and a knowledge vault indexes runbooks, incident history, and repositories for search. Enroll Kubernetes clusters to inspect workloads and manage upgrades, or discover network neighbors, verify them over SNMP, and map them into the topology. Role-based access separates admins, users, and viewers. 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.

Keep is an open-source AIOps and alert management platform built with Python FastAPI and Next.js. It provides a single pane of glass for monitoring alerts from 110+ integrations, alert deduplication, correlation, enrichment, and filtering, YAML-based workflow automation similar to GitHub Actions, AI-powered correlation and summarization, and customizable dashboards for incident management. With 12,100+ GitHub stars, Y Combinator backing, and an Elastic partnership, Keep is the open-source AIOps platform that centralizes alert management across your entire monitoring stack into a single customizable dashboard. Alert deduplication identifies duplicate notifications across providers, correlation groups related alerts into incidents based on rules or AI-powered semantic analysis using pluggable LLM backends supporting OpenAI, Anthropic, and local models via Ollama, and enrichment adds context from external sources like CMDBs and databases. Workflow automation follows a GitHub Actions paradigm with declarative YAML files defining triggers, conditions, and actions that can query MySQL, update Jira tickets, send Slack messages, execute Python scripts, or call REST APIs. Authentication supports no-auth, database, Auth0, Keycloak, OAuth2 Proxy, Okta, and OneLogin. The Common Expression Language enables advanced alert querying, slicing, and rule-based grouping to reduce noise. On RepoCloud, deploy Keep on a dedicated VPS with Docker Compose, root SSH access, and complete control over your alert infrastructure, all under the MIT license.

Alertmanager forgets an alert the moment it resolves; Jarvis remembers everything. This web frontend watches all your Alertmanager clusters at once and streams firing alerts into one live view over WebSocket, no refresh as problems appear or clear. Every alert's lifecycle is stored, so the resolved view answers how often something fired and how long it burned, and a grace period keeps a missed poll from being recorded as a phantom resolution. When an alert lands, claim it so the team sees who is on it, and leave comments bound to that alert fingerprint; notes survive restarts and re-fires, so the next person inherits the context. Silencing gets a rehearsal: preview exactly which alerts a silence will hit before creating it, fire a one-click Fast-Silence from the list, and save templates for recurring maintenance. Filters use the Alertmanager matchers you already know, save as named sets, ride in shareable URLs, and one can be your default view. Point Jarvis at every member of an HA gossip cluster and duplicates collapse by fingerprint, while protected upstreams authenticate with OAuth2, bearer tokens or basic auth per cluster. Sign-in is optional through built-in accounts or any OIDC provider, and it runs as one hardened container on port 8080, with PostgreSQL available when you want replicas. Keep it behind your VPN or an authenticating proxy, as its own docs insist. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache-2.0 licensed.

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.

Trusted by Cal.com, WhiteBIT, and Documenso and backed by 8,800+ GitHub stars, OpenStatus delivers the open-source status page and uptime monitoring platform that replaces Atlassian Statuspage, Better Stack, and Instatus with a single self-hosted deployment. The monitoring engine runs Go-based probes across 28 global regions on three cloud providers checking HTTP, TCP, and DNS endpoints in parallel with configurable intervals and multi-region consensus to eliminate false-positive alerts. Status pages ship with custom domain support, password and email-domain access controls, maintenance windows, grouped monitor components, and subscriber notifications via email and RSS. Incident management provides structured status reports with investigating, identified, monitoring, and resolved timeline phases that publish automatically to affected status pages. The monitoring-as-code workflow supports YAML configuration synced through the CLI, a GitHub Actions integration for CI/CD pipelines, and a Terraform provider for infrastructure-as-code deployments. The typed ConnectRPC JSON-over-HTTP API exposes a published OpenAPI specification with a Node SDK for programmatic access, while an MCP server connects AI assistants like Claude, ChatGPT, and Cursor directly to workspace data. The tech stack combines Next.js with shadcn/ui for the dashboard, Hono for the API server, Drizzle ORM over Turso for application data, and Tinybird for analytics. Private monitoring locations deploy as a single 8.5MB Docker image behind firewalls to check internal services. 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.

Keep users ahead of outages by consolidating infrastructure monitoring into Peekaping, a unified uptime monitoring and incident communication platform that alerts engineering teams to network and application failures before customers experience disruptions. Users can configure automated synthetic checks across HTTP endpoints, database engines, message queues, and container runtimes to verify response latency, payload integrity, and SSL certificate expiration. When performance thresholds degrade or connections drop, the platform broadcasts structured incident notices across twenty-two notification channels including Slack, Discord, Telegram, PagerDuty, and custom webhooks. Visual dashboards display live heartbeat timelines, historical latency percentiles, and rolling availability scores for each monitored endpoint. System administrators can assemble custom public status pages with custom domains, branded color schemes, and component grouping to inform external stakeholders during planned maintenance or unforeseen service degradations. Teams can schedule recurring maintenance windows to pause alert notifications during routine deployments and generate API tokens to automate monitor creation directly from CI/CD deployment pipelines. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

A polished public status page without Statuspage prices or a heavyweight observability suite: Kener is a status and uptime monitoring system built with SvelteKit and Node.js. It runs 11 monitor types - API, Ping, TCP, DNS, SSL certificate, SQL query, Heartbeat, gRPC, and GameDig game-server checks among them - each with configurable intervals and thresholds. Incident management covers the full lifecycle: structured timelines from investigation through resolution, acknowledgements, and subscriber-visible updates, plus maintenance windows with RRULE-based recurring schedules and automatic status transitions. Notifications reach email, Slack, Discord, and custom webhooks through trigger-based workflows with template-driven messaging. One instance can serve multiple branded status pages - per product, team, or region - with custom logos, colors, and CSS, localization into 21 languages, timezone-aware displays, and server-rendered pages that stay fast and SEO-friendly. Operations tooling includes role-based access for teams, API key management, a secrets vault, analytics integrations (Google Analytics, Plausible, Umami, and others), and a REST API with 17+ endpoints for automating incidents and monitors from CI/CD. MIT-licensed; Docker deployment with Redis, SQLite by default, PostgreSQL or MySQL for production.

With 4,500+ GitHub stars and version 1.0.92 released August 2026, xyOps delivers a complete operations platform that unifies workflow automation, job scheduling, server monitoring, alerting, and incident response in one self-hosted system. The platform uses a distributed architecture where a central conductor coordinates lightweight xySat satellite agents running on Linux, macOS, or Windows worker nodes via persistent WebSocket connections. The visual workflow builder lets you chain events, triggers, actions, and monitors into multi-step pipelines with conditional logic, fan-out/fan-in parallelism, multiplex controllers for fleet-wide execution, and configurable resource limits. QuickMon provides per-second CPU, memory, disk, and network visibility streamed live to the web UI, while user-defined monitor plugins sample metrics every minute with time-series storage at hourly, daily, monthly, and yearly resolutions. Alert triggers evaluate expressions against live data and fire notifications via email, webhook, or custom actions, with full server snapshots attached showing every running process, network connection, and resource utilization at the moment of detection. Failed jobs and alerts automatically create tickets with linked logs, metrics history, and context for end-to-end incident tracking. The plugin marketplace supports extensions written in any language, and the Docker plugin enables container-based job execution. Deploy via Docker with persistent volumes on port 5522 for the web UI and 5523 for API access, running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSD-3-Clause licensed.

Sensors watch your infrastructure so your engineers do not have to watch it at 3 a.m. StackStorm is event-driven automation: Python sensors poll or listen to external systems (monitoring alerts, ticket updates, chat messages, webhooks, timers) and inject each event as a trigger. Rules match triggers against criteria you define and fire the response automatically, mapping the event payload straight into action parameters. Actions do the work: SSH commands, REST calls, and integrations for AWS, Docker, OpenStack, Puppet, Jira, Slack, and hundreds more from community packs, or your own scripts wrapped with a few lines of metadata. Multi-step responses become workflows that sequence actions with conditions, branching, and data passed between tasks, handling everything from disk-full remediation to full deployment pipelines. Everything bundles into packs, the shareable units that group sensors, rules, actions, and workflows per product or per automation, installable from the StackStorm Exchange or your own Git repositories. The web UI runs actions, explores workflow executions down to individual task results in real time, manages rules, and installs packs, while every execution, manual or automated, lands in an audit trail with its triggering context. ChatOps aliases even let the team trigger approved automations from chat. 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.

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.

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.