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Stack Overflow Dev Survey 2026

AI agent observability and security

Our analysis

Sentry leads at 26%, ahead of LangSmith at 17%. Established monitoring products may have an advantage as AI observability converges with conventional application monitoring.
AI agent observability and securityUsed · n = 2,277UsedAI agent observability and securitySentry26%LangSmith17%MLflow15%Langfuse15%Datadog LLM12%Weights & Biases11%Arize AI6%Braintrust6%DeepEval6%Respan6%Promptfoo5%Agenta5%Ragas5%Galileo AI5%Portkey5%LangWatch4%Helicone4%Humanloop4%PromptLayer4%Patronus AI4%HoneyHive4%Confident AI4%Traceloop4%Chamber4%Opik4%Future AGI4%Sentrial4%Athina AI3%Lunary3%Moda3%Ashr3%Parea AI3%2,277Data licensed under Open Database License (ODbL) 1.0
Used · n = 2,277
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Format

Question

Have you used any of the following tools for AI agent observability, prompts, or evals in the past year? Do you want to use any of the following in the next 6 months?
  • scale
  • Optional
  • v2026.1

Data

RespondentsPercent
Sentry59226.0%
LangSmith39317.3%
MLflow34715.2%
Langfuse34515.2%
Datadog LLM27111.9%
Weights & Biases24410.7%
Arize AI1335.8%
Braintrust1325.8%
DeepEval1315.8%
Respan1275.6%
Promptfoo1215.3%
Agenta1145.0%
Ragas1114.9%
Galileo AI1104.8%
Portkey1094.8%
LangWatch1014.4%
Helicone954.2%
Humanloop934.1%
PromptLayer924.0%
Patronus AI914.0%
HoneyHive904.0%
Confident AI863.8%
Traceloop863.8%
Chamber853.7%
Opik843.7%
Future AGI803.5%
Sentrial793.5%
Athina AI783.4%
Lunary773.4%
Moda763.3%
Ashr703.1%
Parea AI693.0%

Use this data

Response data is released under the ODbL 1.0, which asks that you attribute it.

Structured for code, with the question, the year and the source url alongside the numbers.

A formatted table, ready to paste into a document, an issue or a prompt.

Spreadsheet

.csv is a plain text format which most spreadsheet software can open.