OpenTelemetry

OpenTelemetry (OTel) is an open-source observability framework (observability) that provides standardized APIs, SDKs, and tooling for generating, collecting, and exporting telemetry data such as traces, metrics, and logs from applications and infrastructure.

• Unified specification and implementations for telemetry collection across traces, metrics, and logs (observability)
• Language-specific SDKs and APIs for instrumenting applications and services (application performance monitoring)
• Collector service for receiving, processing, and exporting telemetry data from multiple sources to multiple backends (observability pipeline)
• Context propagation and semantic conventions for consistent telemetry across distributed systems (distributed systems observability)
• Integration with CNCF projects and external backends via exporters and extensions (observability ecosystem)

More About Opentelemetry

OTel is an open-source observability framework (observability) under the Cloud Native Computing Foundation (CNCF) that defines a vendor-neutral approach to collecting telemetry data from cloud-native and traditional systems. It addresses the problem of fragmented instrumentation by providing a common set of APIs, SDKs, and protocols for traces, metrics, and logs, allowing enterprises to standardize how telemetry is generated and transmitted across heterogeneous environments.

The project supplies language-specific SDKs (application performance monitoring) that developers embed into services to generate telemetry such as distributed traces, metrics, and logs. These SDKs implement the OTel specification, including data models, context propagation, and semantic conventions. Context propagation (distributed systems observability) enables correlation of telemetry across service boundaries, which supports analysis of end-to-end request flows and cross-service performance behavior.

A central component of the ecosystem is the OpenTelemetry Collector (OTC) (observability pipeline), a vendor-agnostic service that receives telemetry via supported protocols, processes it, and exports it to one or more backends. The Collector can run as an agent, sidecar, or gateway and supports configurable pipelines for receiving, processing, and exporting data. Processors and exporters within the Collector framework allow data enrichment, filtering, batching, and routing to observability platforms, storage systems, or analytics tools.

OTel covers multiple telemetry types under one specification (observability), with support for distributed tracing, metrics, and logging. It defines semantic conventions (data modeling) for standardizing attribute names and structures for common technologies such as Hypertext Transfer Protocol (HTTP), messaging systems, databases, and infrastructure components. This standardization enables consistent interpretation of telemetry across tools and environments and simplifies integration with downstream analysis and monitoring systems.

In enterprise environments, OTel is used to instrument microservices, monoliths, serverless functions, and infrastructure components across on-premises (on-prem) and cloud platforms (enterprise observability). Organizations deploy SDKs in application code, configure the Collector as a central data pipeline, and connect it to one or more observability backends. This approach allows telemetry to be routed or migrated between vendors without changing instrumentation, aligned with the project’s vendor-neutral design.

The project interoperates with other CNCF and cloud-native technologies (cloud-native ecosystem) through integrations, receivers, and exporters. Its extensible architecture allows custom processors, exporters, and instrumentation libraries, so enterprises can adapt it to specific compliance, routing, or data-handling requirements. In technical taxonomies, OTel fits within observability and monitoring frameworks, application performance monitoring instrumentation, distributed tracing, and metrics and logging collection, providing a standardized telemetry foundation for diverse operational and analytics platforms.