
6to4 - Why is it so Bad?
In a previous article we measured that a large percentage of 6to4 connections fail. In this article we show our attempts to find out why these connections fail.
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I'm a system architect/research coordinator at the RIPE NCC, where I work in the science group. I'm a chemist by training, but have been working since 1998 on Internet related things, as a sysadmin, security consultant, web developer and researcher. I am interested in technology changes (like IPv6 deployment), Internet measurement, data analysis, data visualisation, sustainability and security. I'd like to bring research and operations closer together, ie. do research that is operationally relevant. When I'm not working I like to make music (electric guitar, bass and drums), do sports (swimming, (inline) skating, bouldering, soccer), and try to be a good parent.
In a previous article we measured that a large percentage of 6to4 connections fail. In this article we show our attempts to find out why these connections fail.
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“This is awesome work, thank you! Do you maybe have the script/notebooks/sources to reproduce this? This could be potential used for other countries.”
Hi Jenneth, The observable notebook we used for this is here: https://observablehq.com/@aguformoso/internet-outages-as-seen-by-ripe-atlas . It's a little rough around the edges, so it would be great if you could help improve it!
Thanks for your comment Maxime. I would love to see more analysis too, and the tool allows people to do this. Take for instance this thread on Twitter where Jason Livingood analyses the signals for the US: https://twitter.com/jlivingood/status/1245142990336688130 If others have analysis for specific countries they want to share it would be great to have them collected, for instance as comments to this RIPE Labs post!
“One may assume that, if some people delayed the changes, other people rushed in to adapt the networks to the increased load? Both behaviour may explain why the change rate is more or less the same?”
I think it would be interesting to dig into this data deeper indeed. I looked at splitting this out per country a bit, but could try figure out if there are trends in the sets of ASNs in this timeseries. Would you be willing to look at this? My colleague Vesna is doing a virtual hackathon around Internet and Corona ( https://labs.ripe.net/Members/becha/hackathons-in-the-time-of-corona ), I'd love it if we could collaborate around this. Let me or Vesna know, or hop on to the conf calls, Mon 2pm UTC ( 3pm Paris timezone :) )
“Ghost routes: https://www.sixxs.net/tools/grh/what/”
I've added a reference to the different names 'stuck routes' and 'ghost routes' for this phenomenon at the beginning of the post. Thanks for the pointer!
“Interested in repeating this analysis for 2018 world cup?”
Hi Dan, we have no plans of repeating this analysis this time. This type of signal is still there, see for instance https://twitter.com/search?q=%40ohohlfeld%20%23worldcup&src=typd for a couple of graphs that show the impact in various places.
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