Introduction

Maple is an open-source observability platform for traces, logs, and metrics, built on OpenTelemetry.

Maple is an open-source observability platform that gives you full visibility into your distributed systems. Explore traces, logs, and metrics in a single unified interface — no vendor lock-in, no proprietary agents.

Traces

Visualize requests as they flow through your services with a full flamegraph and span hierarchy view. Drill into individual spans to see attributes, events, and errors. Maple automatically detects service-to-service dependencies and renders them as an interactive service map.

Logs

Search and filter logs across all your services. Logs are automatically correlated with traces — click a log line to jump to the exact trace and span that produced it.

Metrics

Track throughput, error rates, and latency across services with real-time charts. Maple automatically detects probability-based sampling and extrapolates accurate throughput numbers from sampled data.

Service Map

See how your services connect at a glance. The service map shows call rates, error rates, and latency between services, making it easy to spot bottlenecks and failing dependencies.

AI-Powered Queries

Ask questions about your system in natural language using Maple’s MCP integration. Diagnose errors, find slow traces, and explore service health without writing queries.

Getting Started

Sign up at app.maple.dev or self-host on your own infrastructure
Point your OpenTelemetry SDK at Maple’s ingest endpoint
Start exploring in the dashboard

The fastest path: run maple-onboard in Claude Code (or Codex / Cursor with the skill installed) and it’ll walk every service in the repo, install OpenTelemetry, wire traces / logs / metrics, and verify the bootstrap end-to-end.

maple-onboard

Or set up by hand. The recommended shape is to inline the endpoint and ingest key in your bootstrap source — the ingest key is project-scoped and write-only (Sentry-DSN-shaped), so source-level configuration removes a class of “OTel didn’t start because env vars weren’t set” deploy failures. See the per-language guides for exact code.

If you’d rather use the standard OpenTelemetry environment variables, those work too:

export OTEL_EXPORTER_OTLP_ENDPOINT="https://ingest.maple.dev"
export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Bearer YOUR_API_KEY"
export OTEL_SERVICE_NAME="my-service"

Follow our language-specific guides:

Effect SDK — official Maple SDK for Effect apps
Node.js Instrumentation — Express, Fastify, Hono
Next.js Instrumentation — App Router, Pages Router, middleware
Python Instrumentation — FastAPI and Django
Go Instrumentation
Rust Instrumentation — bridged to the tracing crate
Java Instrumentation — zero-code with the Java agent
C# / .NET Instrumentation
Kotlin Instrumentation — Ktor and Spring Boot

For details on required attributes and data conventions, see OpenTelemetry Conventions.