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DataBuff

databuff.ai

WebAPISelf-hosted
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Spec score 7.6 #29 of 56 in Runtime Monitoring Software

Spec sheet

Product
DataBuff describes itself as an open-source, AI-native OpenTelemetry APM for application performance monitoring and distributed tracing.Read 11 Oct 2026 · databuff.ai
Intended users
The product overview describes use cases including teams seeking quick APM deployment, conversational troubleshooting, and self-hosted AI operations capabilities.Read 11 Oct 2026 · databuff.ai
Deployment
The maker documents Docker and Kubernetes installation, with a recommended minimum of 8 CPU cores and 16 GB RAM for each installation guide.Read 11 Oct 2026 · databuff.ai
Integrations
External AI agents including Cursor and Claude Code can connect through MCP to call DataBuff APM tools.Read 11 Oct 2026 · databuff.ai
Security
The documented MCP MVP has no dedicated API token, and the guide recommends using an intranet, VPN, or reverse proxy.Read 11 Oct 2026 · databuff.ai
Support
The maker's partner page describes delivery playbooks, pre-sales assets, co-engineering support, and partner enablement for partners.Read 11 Oct 2026 · databuff.ai
Agent access
Cursor, Claude Code, and OpenClaw/AMC can connect as external agents through the MCP endpoint.Read 11 Oct 2026 · databuff.ai
AI analysis
Its AI can query traces, metrics, topology, and alerts, inspect services, and analyze incidents.Read 11 Oct 2026 · databuff.ai
AI features
Its AI platform can query metrics, traces, topology, and alerts in natural language, inspect services, and analyze incidents.Read 11 Oct 2026 · databuff.ai
AI setup
The installation guide says to enter an API key in Model Settings to enable AI.Read 11 Oct 2026 · databuff.ai
Alert notifications
DataBuff can send alert events as JSON HTTP POST requests to a configured webhook URL.Read 11 Oct 2026 · databuff.ai
APM features
The product includes distributed tracing, service metrics, automatically generated service topology, and alerting.Read 11 Oct 2026 · databuff.ai
Architecture
The product overview describes a three-component architecture of ingest, storage, and platform.Read 11 Oct 2026 · databuff.ai
External systems
The maker documents connecting external MCP services such as SkyWalking, Prometheus, and Zabbix to AI experts.Read 11 Oct 2026 · databuff.ai
Ingestion
DataBuff Ingest accepts OTLP traces, metrics, and logs over gRPC and HTTP.Read 11 Oct 2026 · databuff.ai
Login security
The open-source Web application uses a built-in seed account by default, and credentials can be overridden through environment variables.Read 11 Oct 2026 · databuff.ai
Monitoring
Its APM features include distributed traces, service metrics, service topology, and alerting.Read 11 Oct 2026 · databuff.ai
Pricing information
The opened maker pages describe DataBuff as open-source but do not state a product price or commercial plan.Read 11 Oct 2026 · databuff.ai
Requirements
The Docker installation guide recommends a host with 8 CPU cores and 16 GB RAM.Read 11 Oct 2026 · databuff.ai
Security limitation
The documented MCP endpoint has no dedicated API token in the described MVP, and the maker recommends restricting access with an intranet, VPN, reverse proxy, gateway, or firewall.Read 11 Oct 2026 · databuff.ai
Telemetry
It ingests OpenTelemetry data and supports SkyWalking alongside OTLP.Read 11 Oct 2026 · databuff.ai

Where Specifiction places it

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