Keywords AI

Datadog LLM vs Promptfoo

Compare Datadog LLM and Promptfoo side by side. Both are tools in the Observability, Prompts & Evals category.

Quick Comparison

Datadog LLM
Datadog LLM
Promptfoo
Promptfoo
CategoryObservability, Prompts & EvalsObservability, Prompts & Evals
PricingEnterprise
Best ForEnterprise teams already using Datadog who want to add LLM monitoring
Websitedatadoghq.compromptfoo.dev
Key Features
  • LLM monitoring within Datadog platform
  • Unified APM + LLM observability
  • Automatic instrumentation
  • Cost and token tracking
  • Integration with existing Datadog dashboards
Use Cases
  • Unified monitoring for AI and traditional services
  • Enterprise LLM monitoring at scale
  • Correlating LLM performance with infrastructure
  • Compliance and audit logging
  • Large-scale production monitoring

When to Choose Datadog LLM vs Promptfoo

Datadog LLM
Choose Datadog LLM if you need
  • Unified monitoring for AI and traditional services
  • Enterprise LLM monitoring at scale
  • Correlating LLM performance with infrastructure
Pricing: Enterprise

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 Promptfoo

Promptfoo is an open-source tool for testing and evaluating LLM prompts. It lets developers define test cases, run them against multiple models, compare outputs side-by-side, and catch regressions before deployment. Supports custom scoring functions, red-teaming, and CI/CD integration for automated prompt testing.

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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