Comparison

MLflow AI Platform vs Langfuse: Open Source Agent Evals & Observability

MLflow AI Platform and Langfuse: Open Source Agent Evals & Observability both land on Depends.

MLflow AI Platform

Depends

Confidence: Medium

Buy if you have engineers to self-host, integrate, and patch security issues within days . the free core is deep and vendor-neutral.

Depends

Confidence: Low

Buy if you ship LLM apps to production and need tracing, prompt management, and evals in one place; skip if you don't build AI features.

MLflow AI Platform versus Langfuse: Open Source Agent Evals & Observability
Compare	MLflow AI Platform	Langfuse: Open Source Agent Evals & Observability
Verdict	Depends	Depends
Best for	Teams shipping LLM apps and agents	Teams shipping LLM apps to production
Who it's not for	Teams wanting zero-ops, hosted observability	Teams not building LLM-powered products
Privacy	Active threat: critical SSRF flaw CVE-2026-64849 under exploitation and added to CISA's KEV catalog; patch self-hosted deployments immediately.^⁹	No known public vulnerabilities found in the sources reviewed.¹⁵
Support quality	No support evidence found	No support-quality evidence found
Public sentiment	User feedback in the sources is sparse; one Reddit thread shows buyers weighing MLflow against Langfuse for agent observability.¹²	No independent user reviews surfaced in reviewed sources; all claims are vendor-published adoption and feature statements.¹⁴
Biggest gotcha	CVE-2026-64849 SSRF is actively exploited and on CISA KEV . patch before internet exposure^⁹	Free tier caps at 50k observations/month; high-volume agents outgrow it fast, costs scale with volume¹⁴