Maple Reviews — Discover what people think of this product.

Maple is an open-source observability stack built around OpenTelemetry, giving engineering teams a single place to explore distributed traces, logs, and metrics with millisecond query speeds. Designed for modern microservices, it lets you follow every request across APIs, databases, and background jobs while keeping full context from span attributes to service health.

With Maple, you can quickly identify latency regressions, error spikes, and infrastructure bottlenecks using high-cardinality queries and AI-powered diagnostics. Its interface brings together service maps, trace waterfalls, log streams, and metric charts so you can move from a failing endpoint to the exact log line and database query in a few clicks.

Key capabilities include:

• OpenTelemetry-native ingestion across every supported language and framework
• Unified traces, logs, and metrics with consistent semantic conventions
• Regex-powered search over logs and spans for precise incident analysis
• AI agents that generate queries and summarize production issues

By standardizing on OpenTelemetry and open formats, Maple helps teams avoid vendor lock-in while still getting a fast, intuitive observability experience. Whether you’re running Kubernetes microservices or scaling a monolith, Maple gives you the visibility needed to ship changes confidently and resolve production incidents faster.