Keywords AI
Datadog LLM vs Traceloop
Compare Datadog LLM and Traceloop side by side. Both are tools in the Observability, Prompts & Evals category.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Enterprise | open-source |
| Best For | Enterprise teams already using Datadog who want to add LLM monitoring | Teams already using Datadog/Splunk wanting LLM observability |
| Website | datadoghq.com | traceloop.com |
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When to Choose Datadog LLM vs Traceloop
- Unified monitoring for AI and traditional services
- Enterprise LLM monitoring at scale
- Correlating LLM performance with infrastructure
About Datadog LLM
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.
About Traceloop
The OpenTelemetry standard for AI. Pipes LLM telemetry into Datadog, Splunk, or any OTel backend.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
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