Datadog's LLM Observability extends its industry-leading APM platform to AI applications. It provides end-to-end tracing from LLM calls to infrastructure metrics, prompt and completion tracking, cost analysis, and quality evaluation—all integrated with Datadog's existing monitoring, logging, and alerting stack. Ideal for enterprises already using Datadog who want unified observability across traditional and AI workloads.
Phoenix is an open-source LLM observability and evaluation platform from Arize AI. It supports OpenTelemetry-based tracing across LLM and agent applications, with built-in evaluators, dataset management, and prompt playgrounds. Phoenix can be self-hosted with Docker or run via the Arize-hosted cloud version.
Core capabilities each platform advertises.
What each tool does well, and the limitations to keep in mind.
Pros
Cons
Pros
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Choose Datadog LLM if you wantChoose if you want
Choose Phoenix if you wantChoose if you want
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.
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