Maple
Open-source observability platform built on OpenTelemetry. Collect, visualize, and analyze distributed traces, logs, and metrics with AI-powered diagnostics for faster incident resolution.
Maple is an open-source alternative to:
Maple is an open-source observability platform designed for modern applications. Built on OpenTelemetry and powered by ClickHouse, it enables teams to collect, visualize, and analyze distributed traces, logs, and metrics with sub-second query performance.
Key Features
- Unified Observability: Collect and correlate traces, logs, and metrics from all services in one platform
- AI-Powered Diagnostics: Leverage AI agents to automatically analyze incidents and propose fixes
- Real-Time Incident Response: Follow requests end-to-end with complete context and correlated data
- Service Catalog & Maps: Visualize live request flows and service dependencies
- Error Tracking: Group errors by type with trends, affected services, and sample traces
- Metrics & Dashboards: Customizable dashboards for request rate, error rate, and latency percentiles
- Alerting with Context: Receive alerts with attached traces, logs, and relevant context
- MCP Server Integration: First-class MCP support for AI agents to interact with your observability data
Tech / Self-Hosting
Maple is open-source and can be self-hosted. The platform is built on OpenTelemetry standards and uses ClickHouse for high-performance data storage and querying. Local deployment is available as a single binary for easy setup and management.