Maple is a fully OTel-native observability platform. Every signal — traces, logs, and metrics — flows through the open standard. No proprietary agents, no SDK lock-in.
OpenTelemetry is the CNCF open-source standard for collecting observability data from distributed systems. It provides a single, vendor-neutral set of APIs, SDKs, and tools to instrument your applications and export traces, logs, and metrics.
With support for every major language and framework, OTel has become the industry default for telemetry instrumentation — backed by contributions from hundreds of organizations.
Your instrumentation stays the same regardless of which backend you choose. Switch providers without touching application code.
Traces, logs, and metrics share a unified data model with correlated context. No stitching together separate tools.
Backed by the CNCF and hundreds of contributors. The spec evolves with real-world needs, not a single vendor's roadmap.
First-party SDKs for Go, Java, Python, JavaScript, .NET, Rust, and more. Auto-instrumentation available for most frameworks.
As the industry converges on OTel, your investment in instrumentation carries forward. No more rip-and-replace migrations.
Collectors, exporters, processors, and connectors — a full pipeline you can customize to match your infrastructure.
Send telemetry directly via OTLP/gRPC or OTLP/HTTP. No translation layers, no proprietary formats.
Maple understands and indexes OTel semantic conventions — HTTP, database, RPC, messaging — out of the box.
First-class support for traces, logs, and metrics. Each signal is stored, queried, and correlated natively.
Use the OpenTelemetry Collector to route, filter, and batch telemetry before sending it to Maple.
Works with every official OTel SDK. If it speaks OTLP, Maple can ingest it — no vendor-specific libraries required.
W3C Trace Context and Baggage propagation supported. Correlate spans, logs, and metrics across service boundaries.
Already using the OpenTelemetry Collector, auto-instrumentation agents, or OTel SDKs? Point your OTLP exporter at Maple and start seeing data immediately. No code changes, no new agents to deploy.
Maple fits into the OTel ecosystem as a backend — receiving, storing, and visualizing the telemetry your existing pipeline produces. Swap in Maple without disrupting your instrumentation.