DataBuff — AI-Native APM Built On Opentelemetry
Mission: build the strongest OpenTelemetry APM backend
AI-native · OTLP-native · multi-agent out of the box · self-hosted traces, metrics, topology
Live Demo · Documentation · Open Source APM · 简体中文 · Community
Demo login: admin / Databuff@123
AI multi-agent troubleshooting · Service health · Call graph topology
Keywords: AI-Native APM · OpenTelemetry APM · OTLP Backend · Multi-Agent · Distributed Tracing · AIOps · Open Source APM · MCP · Self-Hosted Observability
What is DataBuff
DataBuff is an AI-native APM backend built on Opentelemetry — ingest traces, metrics, and logs via OTLP, with full-stack monitoring, service topology, RED metrics, and out-of-the-box multi-agent AI troubleshooting.
The goal is not "yet another observability UI," but to build the strongest OpenTelemetry APM backend — letting LLMs query live telemetry directly, from natural-language query → multi-agent inspection → root-cause analysis → ops remediation.
Listed on OpenTelemetry official Vendors (Native OTLP) and CNCF Landscape.
⭐ Star the project · Live Demo · Documentation
Why DataBuff
If you are evaluating an OpenTelemetry APM backend, or want AI that actually closes the troubleshooting loop, DataBuff is built for you:
- AI-native, not bolted on — LLMs query traces, metrics, topology, and alerts directly; add an API key after install, no separate AI platform needed
- Multi-agent out of the box — AI Brain orchestrates query, inspection, ops, and Q&A experts in parallel
- Fully embrace OpenTelemetry — OTLP-native ingestion with existing instrumentation as-is; SkyWalking compatible for smooth migration
- Clear mission — build the strongest OpenTelemetry APM backend: self-hosted, production-grade, extensible
- Minimal deployment — Ingest + Doris + Web, one Docker command to run
Key Features
🤖 AI-Native
- Not a bolt-on chat box — LLM answers from real telemetry, not hallucination
- Multi-agent collaboration out of the box — AI Brain orchestrates query, inspection, ops, and Q&A experts
- AI application observability (Roadmap) — LLM call chains · token analytics · agent topology · skill/tool/model tracing
- MCP both ways — expose capabilities to Cursor / Claude; ingest external MCPs like Prometheus
- Bring your own model — Kimi, DeepSeek, GLM, Ollama, and other OpenAI-compatible APIs
📊 OpenTelemetry-Native
- OTLP-native ingestion — gRPC
4317/ HTTP4318for Traces + Metrics + Logs - eBPF APM — kernel-level, non-intrusive collection; call chains and performance data without code changes
- Dual-protocol support — OTLP native + SkyWalking native gRPC (
11800); switch by changing exporter address - Alerting loop — threshold detection, scheduled evaluation, alert event history
🐳 Engineering Foundation
- 3-component stack — Ingest + Doris + Web, no middleware sprawl
- Skill extensibility — custom digital experts without touching core code
Feature Gallery
Out-of-the-box multi-agent AI on top of a full OpenTelemetry APM.
Natural Language Query
Ask "which service was slowest" in plain language — AI ranks results, no query language required.
Multi-Agent Collaboration
Complex tasks dispatched to multiple experts in parallel, synthesized into a forwardable incident report.
Root Cause Analysis
Pull topology, rank metrics, attribute bottlenecks by share — conclusions ready for your incident report.
APM UI
Global topology, service list, and trace drill-down — AI reads the data, the UI confirms it.
More capabilities in Documentation
Architecture & Ingestion
| Protocol | Port / Endpoint | Signals |
|---|---|---|
| OTLP (OpenTelemetry native) | gRPC 4317 · HTTP 4318 | Traces + Metrics + Logs |
| SkyWalking native gRPC | gRPC 11800 | Trace + JVM metrics + Logs |
Quick Start in 5 Minutes
- Install platform — one command to launch Ingest + Doris + Web
curl -fsSL https://databuff.ai/databuff/ai-apm-install.sh | bash
- Install demo (optional) — auto-report traces and see topology quickly
curl -fsSL https://databuff.ai/databuff/ai-apm-demo-install.sh | bash
- Connect a model → start troubleshooting — open
http://YOUR_HOST:27403, loginadmin/Databuff@123, add API key to enable AI
Offline install / Kubernetes install
Offline install — download the bundle from the install page:
tar -zxvf databuff-ai-apm-offline-<version>-<arch>.tar.gz
cd databuff-ai-apm-offline-<version>-<arch> && sudo ./install.sh
Kubernetes install
curl -fsSL https://databuff.ai/databuff/ai-apm-k8s-install.sh | bash
curl -fsSL https://databuff.ai/databuff/ai-apm-demo-k8s-install.sh | bash # demo optional
Documentation
| Doc | Description |
|---|---|
| Documentation | Product overview, user guides, ops reference |
| OTLP ingestion guide | OpenTelemetry SDK / Collector setup |
| Competitive comparison | vs Jaeger, SigNoz, SkyWalking, and more |
| Migration guide | Migrate from other APM tools |
Contributing
If you are building AI-native APM / OpenTelemetry observability, help make the strongest OpenTelemetry APM backend a real, usable open-source foundation:
- ⭐ Star this repo and Watch for updates
- 🐛 Open an Issue to report bugs or request features
- 🤝 Read CONTRIBUTING.md and submit a PR
- 💬 Scan the QR code to join our WeChat community
Scan to join the DataBuff community
License
This repository is licensed under Apache-2.0.