Datadog LLM Observability natively supports OpenTelemetry GenAI Semantic Conventions

As generative AI workloads increase, engineering and platform teams are adopting OpenTelemetry (OTel) to standardize observability by providing a unified pipeline for telemetry data across applications, infrastructure, and AI systems. OpenTelemetry GenAI Semantic Conventions offer a standardized schema to track and analyze AI workloads, making them measurable and interoperable across frameworks. Datadog has integrated native support for these conventions, allowing seamless instrumentation of LLM applications that can be analyzed within Datadog LLM Observability without additional code modifications. This integration enables teams to forward GenAI spans directly to Datadog, ensuring that data governance policies are maintained while providing comprehensive visibility into AI performance, quality, and cost metrics across various providers and models. By mapping GenAI attributes to Datadog's schema, teams can analyze token usage, latency, and cost, correlating AI data with broader application performance metrics. The platform also supports experimentation with agentic applications, offering tools to iterate and refine AI systems efficiently.

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