Define, run, and scale custom LLM-as-a-judge evaluations in Datadog
Datadog | The Monitor blog

Define, run, and scale custom LLM-as-a-judge evaluations in Datadog


Summary

Datadog's LLM Observability tools help users monitor and improve the performance of their Large Language Model (LLM) prompts. It allows tracking key metrics like cost, latency, and token usage, enabling comparison of different prompts and identification of areas for optimization. Ultimately, this leads to more efficient and cost-effective LLM applications.
Read the Original Article

This article originally appeared on Datadog | The Monitor blog.

Read Full Article on Original Site

Popular from Datadog | The Monitor blog

1
DASH 2026: Guide to Datadog’s newest announcements
DASH 2026: Guide to Datadog’s newest announcements

Datadog | The Monitor blog Jun 9, 2026 210 views

2
DASH 2026 Harnessing AI: Guide to Datadog’s newest announcements
DASH 2026 Harnessing AI: Guide to Datadog’s newest announcements

Datadog | The Monitor blog Jun 9, 2026 186 views

3
Datadog LLM Observability natively supports OpenTelemetry GenAI Semantic Conventions
4
Introducing Bits AI Dev Agent for Code Security
Introducing Bits AI Dev Agent for Code Security

Datadog | The Monitor blog Mar 26, 2026 109 views

5
Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog
Instrument and monitor Boomi integration flows with OpenTelemetry and Datadog

Datadog | The Monitor blog Apr 9, 2026 103 views