[Int-area] Enhancing traceroute with contextual per-hop analysis (Traceroute Aurix)

Leonardo Melegassi <melegassi@catellix.com> Wed, 22 April 2026 22:05 UTC

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Date: Wed, 22 Apr 2026 19:04:55 -0300
From: Leonardo Melegassi <melegassi@catellix.com>
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Subject: [Int-area] Enhancing traceroute with contextual per-hop analysis (Traceroute Aurix)
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Hi all,



My name is Leonardo Melegassi, a network and telecommunications engineer and the creator of the Catellix project.



I have been working on a practical approach to extend traditional traceroute diagnostics, called "Traceroute Aurix", which is already implemented and running in real-world scenarios.



While tools such as traceroute and MTR provide path discovery and continuous measurements, they can be limited in exposing contextual behavior of each hop and overall route quality in a structured way.



Aurix focuses on building a more analytical and enriched view of the path by combining multiple dimensions of measurement and context.



In practical tests, the system is able to:



- Identify each hop with ASN and geolocation enrichment

- Measure per-hop minimum, average, and maximum latency, as well as jitter

- Evaluate the quality of each segment of the route

- Aggregate end-to-end metrics such as average latency, peak latency, and an overall quality score

- Detect route consistency based on response rate and packet loss behavior



Additionally, the approach includes:



- Route discovery

- IP metadata enrichment

- Correlation analysis across hops



In one test case, traditional traceroute did not clearly expose route instability, while Aurix highlighted latency variation and per-hop consistency, making the issue more evident.



The goal is to evolve network diagnostics from a purely descriptive output to a more analytical model that can support pattern identification, troubleshooting, and operational decision-making.



I would appreciate feedback from the community, particularly regarding:



- The relevance of this approach

- Possible overlap with existing tools or ongoing work

- Potential directions for experimentation or standardization



I would be happy to share technical details, sample outputs, or further data if there is interest.



Best regards, 

Leonardo Melegassi 

https://catellix.com