apache/hertzbeat

An AI-powered next-generation open source real-time observability system.

Apache HertzBeat – Real‑time Observability Platform

What it is – HertzBeat is an open‑source, Apache‑licensed system for observability: collecting metrics and logs from services, analysing them, and sending alerts. The README markets it as AI‑powered, but the core functionality is a unified, agent‑less monitoring stack that speaks Prometheus, OTLP and a handful of other protocols.

Key capabilities

  • Metrics & logs – Pulls data from databases, caches, web servers, Kubernetes, Docker, etc. via HTTP, JMX, SSH, SNMP, JDBC, Prometheus and custom YML templates.
  • Alerting & notifications – Define threshold rules, grouping, silencing and route alerts to Email, Discord, Slack, Telegram, DingTalk, WeChat, SMS, Webhook and more.
  • AI features – Mentioned as “HertzBeat AI” for smarter interactions, though the README does not detail specific models or inference.
  • Agent‑less design – No side‑car agents required; collectors run as separate Docker containers or can be deployed in a cluster.
  • Scalable architecture – Horizontal‑scale collector clusters, public/private modes, cloud‑edge collaboration.
  • Status pages – Built‑in UI to publish real‑time service status to end users.

How to get started

  1. Docker – docker run -d -p 1157:1157 -p 1158:1158 --name hertzbeat apache/hertzbeat then open http://localhost:1157 (default admin/hertzbeat).
  2. Collector – Run another container with IDENTITY, MANAGER_HOST and MANAGER_PORT env vars to add a data‑gathering node.
  3. Package – Download a tarball, edit application.yml, and start with ./bin/startup.sh.
  4. Source – Build the Java backend (maven, Java 25) and the Next.js frontend (Node.js, pnpm).
  5. Docker‑compose / Helm – Full stack (HertzBeat + PostgreSQL/MySQL + TSDB) can be deployed via provided compose files or Helm charts.

Who it’s for – Teams that need a single pane of glass for monitoring heterogeneous infrastructure without installing agents on every host. It competes with Prometheus‑Grafana stacks, but adds built‑in log ingestion, alert routing and a UI for status pages.

Community & ecosystem – Active Discord, Reddit, mailing lists, and a presence in the CNCF Observability Landscape. The project builds on Java Spring Boot, Netty, Next.js, React, Tailwind, and many other OSS components.

License – Apache License 2.0.

All details are taken directly from the repository’s README.

Related

  • Project
    SigNoz/signoz

    An open-source observability platform built on OpenTelemetry that unifies logs, metrics, and traces to monitor applications, infrastructure, and AI/LLM pipelines.

  • Project
    eunomia-bpf/agentsight

    AgentSight is a kernel‑level observability tool for AI agents. Using eBPF and TLS tracing, it records prompts, model calls, subprocesses, file and network activity without requiring any SDK or proxy. It provides live dashboards (`top`), replay visualisations (`vis`), queryable SQLite logs, and OpenTelemetry export, helping developers debug failures, audit security, and understand token/resource costs of agents such as Claude Code, Gemini CLI, and Python‑based tools.

  • Project
    perplexityai/numbat

    numbat is an endpoint visibility and security tool that monitors, detects, and optionally blocks unauthorized AI agent activity across desktops, CLIs, and IDEs.

  • Project
    CloudDetail/apo

    An intelligent observability platform that uses AI agents and a specialized data plane to automate root cause analysis and diagnostic workflows for system monitoring.

  • Dispatch
    Solving the Agentic Data Gap: Introducing Airbyte Agents

    Airbyte Agents introduces a unified context layer and Context Store to reduce API churn and token waste when AI agents interact with multiple operational data sources.