---
title: "How Jaeger is evolving to trace AI agents with OpenTelemetry"
url: https://daily.dev/posts/how-jaeger-is-evolving-to-trace-ai-agents-with-opentelemetry-wbwtfypo7
source_url: https://www.cncf.io/blog/2026/05/26/how-jaeger-is-evolving-to-trace-ai-agents-with-opentelemetry
type: article
source: "CNCF"
published: 2026-05-26T11:02:55.928Z
updated: 2026-05-26T11:03:19.033Z
tags: ["devops", "ai-agents", "observability", "opentelemetry"]
reading_time: 6
upvotes: 4
comments: 0
language: en
---

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# How Jaeger is evolving to trace AI agents with OpenTelemetry

**[CNCF](https://daily.dev/sources/cncf)** · 6 min read · 4 upvotes · 0 comments

## Summary

Jaeger is evolving in two phases to handle AI workloads. First, Jaeger v2 rebuilt its core around the OpenTelemetry Collector, natively ingesting OTLP to unify metrics, logs, and traces. Second, the project is integrating Model Context Protocol (MCP), Agent Client Protocol (ACP), and Agent–User Interaction Protocol (AG-UI) to enable collaboration between engineers and AI agents during incident debugging. A new backend ACP layer translates natural-language queries into deterministic trace queries, supporting both cloud LLMs and local SLMs for data privacy. The UI is being updated with a streaming assistant powered by AG-UI. Additionally, Jaeger is adding visualization support for OpenTelemetry GenAI semantic conventions, covering RAG pipelines, agentic systems, embedding latency, and token usage tracking.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.cncf.io/blog/2026/05/26/how-jaeger-is-evolving-to-trace-ai-agents-with-opentelemetry>

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---

Tags: [#devops](https://daily.dev/tags/devops), [#ai-agents](https://daily.dev/tags/ai-agents), [#observability](https://daily.dev/tags/observability), [#opentelemetry](https://daily.dev/tags/opentelemetry)

[View this post on daily.dev](https://daily.dev/posts/how-jaeger-is-evolving-to-trace-ai-agents-with-opentelemetry-wbwtfypo7)