RIPE Atlas: Hurricane Sandy and How the Internet Routes Around Damage
• 13 min read
In this article we look at some of the effects Hurricane Sandy had on the Internet data plane, as we can see them in traceroutes done by RIPE Atlas.
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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.
• 13 min read
In this article we look at some of the effects Hurricane Sandy had on the Internet data plane, as we can see them in traceroutes done by RIPE Atlas.
• 3 min read
After causing lots of damage in the Caribbean, superstorm Sandy is having a devastating effect on the US East Coast. We looked at the RIPE Atlas network to find out what effects this superstorm has on the Internet. Below are some preliminary results of what we saw.
• 6 min read
At the recent RIPE Meeting, the question was raised whether Internet users would see significant filtering of AAAA DNS queries or replies. We used RIPE Atlas measurements to provide an answer to this question.
• 9 min read
IPv6 RIPEness helped in creating awareness and got people into action with regards to their first steps towards deploying IPv6 in the RIPE NCC service region. Up until now IPv6 RIPEness didn't measure actual IPv6 deployment. In this article we propose a measure (a "5th star"), which attempts to mea…
• 4 min read
Olympic fever didn't escape us here at the RIPE NCC!
• 9 min read
In this article I look at four different IPv6 destinations in different BGP set-ups and how these are seen by RIPE Atlas probes. This reveals some differences in reachability for the different networks, likely due to BGP route filtering. We see roughly 1% out of ~500 RIPE Atlas probes that can't re…
• 2 min read
Now that World IPv6 Launch is weeks behind us it's interesting to look at what long-lasting effects it had.
• 10 min read
We've enabled RIPE NCC members to do IPv6-traceroutes from all RIPE Atlas probes to IPv6 destinations. Until now they could get the raw analysis results (text/JSON representations of traceroute results) for analysis. In this article we present a first experimental analysis and visualisation of the …
• 7 min read
Following on from last year's during World IPv6 Day, we again looked at relative performance of IPv4 and IPv6 from the measurements we conducted. In this article we describe the methodology and the show the results of these measurements.
• 3 min read
With the introduction of a new firmware version for RIPE Atlas probes, the structure of the measurement results will be changing. Anyone making use of the raw results is advised to read about these upcoming changes and to subscribe to our RSS feed or subscribe to our mailing list to be notified of …
• 7 min read
Last week, the Network Traffic, Measurement and Analysis Conference (TMA) took place in Maynooth, Ireland. A full week was scheduled, featuring a PhD school across Monday and Tuesday, the Mobile Network Measurements (MNM) workshop on Tuesday, and the main conference from Wednesday to Friday. We wer…
• 6 min read
In this article we present a prototype web portal, which demonstrates the deployment of RIPE Atlas probes within eyeball networks based on Internet user population estimates per Autonomous System Number (ASN) per country.
• 9 min read
BGP routing table growth is one of the major Internet scaling issues, and prefix deaggregation is thought to be a major contributor to table growth. In this work we quantify the fragmentation of the routing table by the type of IP prefix. We observe that the proportion of deaggregated prefixes has …
• 11 min read
Please find below the third part of our technical services update. This time we're focusing on our research activities and a number of tools we are developing.
• 9 min read
Last month we covered the 2015 leap second ahead of the insertion of a leap second at the very end of 2016. As stated previously, leap seconds can trigger poorly-tested code paths; leap second handling always unearths bugs and issues. This one was no exception!
• 7 min read
In this article, we give one example of the possible communities that are now easier to build around RIPE Atlas probes. With the tagging of similar probes, existing communities can use additional tools for creating and analysing RIPE Atlas measurements, such as "IXP Country Jedi", to create their o…
• 8 min read
We look into why dynamic addresses change and find ISPs that renumber periodically, most commonly every 24 hours or a multiple of 24 hours. We also find that outages influence address changes.
• 8 min read
This article is intended to make RIPE Atlas users aware of ethical issues that could arise when using RIPE Atlas. We do not intend to propose any new formal processes or procedures to address the relevant ethical issues, but we do want to encourage members of the RIPE Atlas community to consider th…
• 6 min read
We used a number of RIPE NCC tools and data sets to take a quick look at the recent DDoS attack on Dyn’s infrastructure. We wanted to see if this could be found in the data produced by the RIPE Atlas community.
This RIPE Labs article has good information on how to avoid effects from unknown attributes showing up at your BGP routers: https://labs.ripe.net/author/berislav_todorovic/bgp-path-attribute-filtering-a-powerful-tool-to-mitigate-alien-attributes/
“Hi Emile, I remember attribute 28 showing up in several previous studies. Interesting to see it causing a problem this time! As bgpdump maintainer, I'd ask you to check out v1.6.2 or higher, since 2020 there is a '-u' flag to output unknown attributes in the short (-m) mode (helpfully submitted by Italo Cunha) - it may make your future parsing life much easier :) Kind regards, Colin”
Thanks Colin, I didn't know, and this would have speeded up my analysis if I had!
Code for looking into AS Adjacency changes is available here: https://github.com/emileaben/as-neighbour-diff
Code on how to create graphs like Figure 1 ( ie. BGP view of how networks in a country interconnect ) is available here: https://github.com/InternetHealthReport/country-as-hegemony-viz
NOG Alliance is helping out network operators in Ukraine: https://nogalliance.org/our-task-forces/keep-ukraine-connected/
An effort related to keeping Urkanian servers/websites online by the Dutch Cloud Community: https://dutchcloudcommunity.nl/community/cloud4ukraine/
We got a request for the HHI scores for other countries. I've put these in a small repo on github together with the code that generated this. repo: https://github.com/emileaben/hhi-eyeballs HHI scores for 2022-03-07 are available here: https://raw.githubusercontent.com/emileaben/hhi-eyeballs/main/eyeball-hhi.2022-03-07.csv
“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 :) )
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