Search Results: "ag"

1 June 2025

Ben Hutchings: FOSS activity in May 2025

Guido G nther: Free Software Activities May 2025

Another short status update of what happened on my side last month. Larger blocks besides the Phosh 0.47 release are on screen keyboard and cell broadcast improvements, work on separate volume streams, the switch of phoc to wlroots 0.19.0 and effort to make Phosh work on Debian's upcoming stable release (Trixie) out of the box. Trixie will ship with Phosh 0.46, if you want to try out 0.47 you can fetch it from Debian's experimental suite. See below for details on the above and more: phosh phoc phosh-mobile-settings phosh-osk-stub / stevia phosh-tour phosh-osk-data pfs xdg-desktop-portal-phosh phrog phosh-debs meta-phosh feedbackd feedbackd-device-themes gmobile GNOME calls Debian ModemManager osmo-cbc gsm-cell-testing mobile-broadband-provider-info Cellbroadcastd phosh-site pipewire wireplumber python-dbusmock Bugs Reviews This is not code by me but reviews on other peoples code. The list is (as usual) slightly incomplete. Thanks for the contributions! Help Development If you want to support my work see donations. Comments? Join the Fediverse thread

Emmanuel Kasper: ARM64 desktop as daily driver

I have bought myself an expensive ARM64 workstation, the System 76 Thelio Astra that I intend to use as my main desktop computer for the next 15 years, running Debian. The box is basically a server motherboard repurposed in a good desktop chassis. In Europe it seems you can order similar ready systems here. The hardware is well supported by Debian 12 and Debian testing.I had some initial issues with graphics, due to the board being designed for a server use, but I am solving these as we go. Annoyances I got so far:
  • When you power on the machine using the power supply switch, you have to wait for the BMC to finished its startup sequence, before the front power button does anything. As starting the BMC can take 90 seconds, I thought initially the machine was dead on arrival.
  • The default graphical output is redirected to the BMC Serial over LAN, which means if you want to install Debian using an attached display you need to force the output on the attached display passing console=tty0 as an installer parameter.
  • Finally the Xorg Nouveau driver does not work with the Nvidia A400 GPU I got with the machine. After passing nodemodeset as a kernel parameter, I can force Xorg to use an unaccelerated framebuffer, which at least displays something. I passed this parameter to the installer, so that I could install in graphical mode. The driver from Nvidia works, but I d like very much to get Nouveau running.
Ugly point
  • A server mother board we said. This mean there is NO suspend to RAM, you have to power off if you don t want to keep the machine on all the time. As the boot sequence is long (server board again) I am pondering setting a startup time in the UEFI firmware to turn the box on at specific usage time.
Good points
  • The firmware of the machine is a standard EFI, which means you can use the debian arm64 installer on an USB stick straight away, without any kind of device tree / bootloader fiddling.
  • The 3 Nics, Wifi, bluetooth were all recognized on first boot.
  • I was afraid the machine would be loud. However it is quiet, you hear the humming of a fan, but it is quieter than most desktops I owned, from the Atari TT to an all in one Lenovo M92z I used for 10 years. I am certainly not a hardware and cooling specialist, but meseems the quietness comes from slow rotating but very large fans.
  • Due the clean design of Linux and Debian, thousands of packages working correctly on ARM64, starting with the Gnome desktop environment and Firefox.
  • The documentation from system76 is fine, their Ubuntu 20.04 setup guide was helpful to understand the needed parameters mentioned above.
Update: The display is working correctly with the nouveau driver after installing the non-free Nvidia firmware. See the Debian wiki.

31 May 2025

Paul Wise: FLOSS Activities May 2025

Focus This month I didn't have any particular focus. I just worked on issues in my info bubble.

Changes

Issues
  • Crash/privacy/security issue in liferea
  • Usability in glab

Sponsors All work was done on a volunteer basis.

Russell Coker: Links May 2025

Christopher Biggs gave an informative Evrything Open lecture about voice recognition [1]. We need this on Debian phones. Guido wrote an informative blog post about booting a custom Android kernel on a Pixel 3a [2]. Good work in writing this up, but a pity that Google made the process so difficult. Interesting to read about an expert being a victim of a phishing attack [3]. It can happen to anyone, everyone has moments when they aren t concentrating. Interesting advice on how to leak to a journalist [4]. Brian Krebs wrote an informative article about the ways that Trump is deliberately reducing the cyber security of the US government [5]. Brian Krebs wrote an interesting article about the main smishng groups from China [6]. Louis Rossmann (who is known for high quality YouTube videos about computer repair) made an informative video about a scammy Australian company run by a child sex offender [7]. The Helmover was one of the wildest engineering projects of WW2, an over the horizon guided torpedo that could one-shot a battleship [8]. Interesting blog post about DDoSecrets and the utter failure of the company Telemessages which was used by the US government [9]. Jonathan McDowell wrote an interesting blog post about developing a free software competitor to Alexa etc, the listening hardware costs $13US per node [10]. Noema Magazine published an insightful article about Rewilding the Internet, it has some great ideas [11].

Antoine Beaupr : Traffic meter per ASN without logs

Have you ever found yourself in the situation where you had no or anonymized logs and still wanted to figure out where your traffic was coming from? Or you have multiple upstreams and are looking to see if you can save fees by getting into peering agreements with some other party? Or your site is getting heavy load but you can't pinpoint it on a single IP and you suspect some amoral corporation is training their degenerate AI on your content with a bot army? (You might be getting onto something there.) If that rings a bell, read on.

TL;DR: ... or just skip the cruft and install asncounter:
pip install asncounter
Also available in Debian 14 or later, or possibly in Debian 13 backports (soon to be released) if people are interested:
apt install asncounter
Then count whoever is hitting your network with:
awk ' print $2 ' /var/log/apache2/*access*.log   asncounter
or:
tail -F /var/log/apache2/*access*.log   awk ' print $2 '   asncounter
or:
tcpdump -q -n   asncounter --input-format=tcpdump --repl
or:
tcpdump -q -i eth0 -n -Q in "tcp and tcp[tcpflags] & tcp-syn != 0 and (port 80 or port 443)"   asncounter --input-format=tcpdump --repl
Read on for why this matters, and why I wrote yet another weird tool (almost) from scratch.

Background and manual work This is a tool I've been dreaming of for a long, long time. Back in 2006, at Koumbit a colleague had setup TAS ("Traffic Accounting System", " " in Russian, apparently), a collection of Perl script that would do per-IP accounting. It was pretty cool: it would count bytes per IP addresses and, from that, you could do analysis. But the project died, and it was kind of bespoke. Fast forward twenty years, and I find myself fighting off bots at the Tor Project (the irony...), with our GitLab suffering pretty bad slowdowns (see issue tpo/tpa/team#41677 for the latest public issue, the juicier one is confidential, unfortunately). (We did have some issues caused by overloads in CI, as we host, after all, a fork of Firefox, which is a massive repository, but the applications team did sustained, awesome work to fix issues on that side, again and again (see tpo/applications/tor-browser#43121 for the latest, and tpo/applications/tor-browser#43121 for some pretty impressive correlation work, I work with really skilled people). But those issues, I believe were fixed.) So I had the feeling it was our turn to get hammered by the AI bots. But how do we tell? I could tell something was hammering at the costly /commit/ and (especially costly) /blame/ endpoint. So at first, I pulled out the trusted awk, sort uniq -c sort -n tail pipeline I am sure others have worked out before:
awk ' print $1 ' /var/log/nginx/*.log   sort   uniq -c   sort -n   tail -10
For people new to this, that pulls the first field out of web server log files, sort the list, counts the number of unique entries, and sorts that so that the most common entries (or IPs) show up first, then show the top 10. That, other words, answers the question of "which IP address visits this web server the most?" Based on this, I found a couple of IP addresses that looked like Alibaba. I had already addressed an abuse complaint to them (tpo/tpa/team#42152) but never got a response, so I just blocked their entire network blocks, rather violently:
for cidr in 47.240.0.0/14 47.246.0.0/16 47.244.0.0/15 47.235.0.0/16 47.236.0.0/14; do 
  iptables-legacy -I INPUT -s $cidr -j REJECT
done
That made Ali Baba and his forty thieves (specifically their AL-3 network go away, but our load was still high, and I was still seeing various IPs crawling the costly endpoints. And this time, it was hard to tell who they were: you'll notice all the Alibaba IPs are inside the same 47.0.0.0/8 prefix. Although it's not a /8 itself, it's all inside the same prefix, so it's visually easy to pick it apart, especially for a brain like mine who's stared too long at logs flowing by too fast for their own mental health. What I had then was different, and I was tired of doing the stupid thing I had been doing for decades at this point. I had recently stumbled upon pyasn recently (in January, according to my notes) and somehow found it again, and thought "I bet I could write a quick script that loops over IPs and counts IPs per ASN". (Obviously, there are lots of other tools out there for that kind of monitoring. Argos, for example, presumably does this, but it's a kind of a huge stack. You can also get into netflows, but there's serious privacy implications with those. There are also lots of per-IP counters like promacct, but that doesn't scale. Or maybe someone already had solved this problem and I just wasted a week of my life, who knows. Someone will let me know, I hope, either way.)

ASNs and networks A quick aside, for people not familiar with how the internet works. People that know about ASNs, BGP announcements and so on can skip. The internet is the network of networks. It's made of multiple networks that talk to each other. The way this works is there is a Border Gateway Protocol (BGP), a relatively simple TCP-based protocol, that the edge routers of those networks used to announce each other what network they manage. Each of those network is called an Autonomous System (AS) and has an AS number (ASN) to uniquely identify it. Just like IP addresses, ASNs are allocated by IANA and local registries, they're pretty cheap and useful if you like running your own routers, get one. When you have an ASN, you'll use it to, say, announce to your BGP neighbors "I have 198.51.100.0/24" over here and the others might say "okay, and I have 216.90.108.31/19 over here, and I know of this other ASN over there that has 192.0.2.1/24 too! And gradually, those announcements flood the entire network, and you end up with each BGP having a routing table of the global internet, with a map of which network block, or "prefix" is announced by which ASN. It's how the internet works, and it's a useful thing to know, because it's what, ultimately, makes an organisation responsible for an IP address. There are "looking glass" tools like the one provided by routeviews.org which allow you to effectively run "trace routes" (but not the same as traceroute, which actively sends probes from your location), type an IP address in that form to fiddle with it. You will end up with an "AS path", the way to get from the looking glass to the announced network. But I digress, and that's kind of out of scope. Point is, internet is made of networks, networks are autonomous systems (AS) and they have numbers (ASNs), and they announced IP prefixes (or "network blocks") that ultimately tells you who is responsible for traffic on the internet.

Introducing asncounter So my goal was to get from "lots of IP addresses" to "list of ASNs", possibly also the list of prefixes (because why not). Turns out pyasn makes that really easy. I managed to build a prototype in probably less than an hour, just look at the first version, it's 44 lines (sloccount) of Python, and it works, provided you have already downloaded the required datafiles from routeviews.org. (Obviously, the latest version is longer at close to 1000 lines, but it downloads the data files automatically, and has many more features). The way the first prototype (and later versions too, mostly) worked is that you feed it a list of IP addresses on standard input, it looks up the ASN and prefix associated with the IP, and increments a counter for those, then print the result. That showed me something like this:
root@gitlab-02:~/anarcat-scripts# tcpdump -q -i eth0 -n -Q in "(udp or tcp)"   ./asncounter.py --tcpdump                                                                                                                                                                          
tcpdump: verbose output suppressed, use -v[v]... for full protocol decode                                                                
listening on eth0, link-type EN10MB (Ethernet), snapshot length 262144 bytes                                                             
INFO: collecting IPs from stdin, using datfile ipasn_20250523.1600.dat.gz                                                                
INFO: loading datfile /root/.cache/pyasn/ipasn_20250523.1600.dat.gz...                                                                   
INFO: loading /root/.cache/pyasn/asnames.json                       
ASN     count   AS               
136907  7811    HWCLOUDS-AS-AP HUAWEI CLOUDS, HK                                                                                         
[----]  359     [REDACTED]
[----]  313     [REDACTED]
8075    254     MICROSOFT-CORP-MSN-AS-BLOCK, US
[---]   164     [REDACTED]
[----]  136     [REDACTED]
24940   114     HETZNER-AS, DE  
[----]  98      [REDACTED]
14618   82      AMAZON-AES, US                                                                                                           
[----]  79      [REDACTED]
prefix  count                                         
166.108.192.0/20        1294                                                                                                             
188.239.32.0/20 1056                                          
166.108.224.0/20        970                    
111.119.192.0/20        951              
124.243.128.0/18        667                                         
94.74.80.0/20   651                                                 
111.119.224.0/20        622                                         
111.119.240.0/20        566           
111.119.208.0/20        538                                         
[REDACTED]  313           
Even without ratios and a total count (which will come later), it was quite clear that Huawei was doing something big on the server. At that point, it was responsible for a quarter to half of the traffic on our GitLab server or about 5-10 queries per second. But just looking at the logs, or per IP hit counts, it was really hard to tell. That traffic is really well distributed. If you look more closely at the output above, you'll notice I redacted a couple of entries except major providers, for privacy reasons. But you'll also notice almost nothing is redacted in the prefix list, why? Because all of those networks are Huawei! Their announcements are kind of bonkers: they have hundreds of such prefixes. Now, clever people in the know will say "of course they do, it's an hyperscaler; just ASN14618 (AMAZON-AES) there is way more announcements, they have 1416 prefixes!" Yes, of course, but they are not generating half of my traffic (at least, not yet). But even then: this also applies to Amazon! This way of counting traffic is way more useful for large scale operations like this, because you group by organisation instead of by server or individual endpoint. And, ultimately, this is why asncounter matters: it allows you to group your traffic by organisation, the place you can actually negotiate with. Now, of course, that assumes those are entities you can talk with. I have written to both Alibaba and Huawei, and have yet to receive a response. I assume I never will. In their defence, I wrote in English, perhaps I should have made the effort of translating my message in Chinese, but then again English is the Lingua Franca of the Internet, and I doubt that's actually the issue.

The Huawei and Facebook blocks Another aside, because this is my blog and I am not looking for a Pullitzer here. So I blocked Huawei from our GitLab server (and before you tear your shirt open: only our GitLab server, everything else is still accessible to them, including our email server to respond to my complaint). I did so 24h after emailing them, and after examining their user agent (UA) headers. Boy that was fun. In a sample of 268 requests I analyzed, they churned out 246 different UAs. At first glance, they looked legit, like:
Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36
Safari on a Mac, so far so good. But when you start digging, you notice some strange things, like here's Safari running on Linux:
Mozilla/5.0 (X11; U; Linux i686; en-US) AppleWebKit/534.3 (KHTML, like Gecko) Chrome/6.0.457.0 Safari/534.3
Was Safari ported to Linux? I guess that's.. possible? But here is Safari running on a 15 year old Ubuntu release (10.10):
Mozilla/5.0 (X11; Linux i686) AppleWebKit/534.24 (KHTML, like Gecko) Ubuntu/10.10 Chromium/12.0.702.0 Chrome/12.0.702.0 Safari/534.24
Speaking of old, here's Safari again, but this time running on Windows NT 5.1, AKA Windows XP, released 2001, EOL since 2019:
Mozilla/5.0 (Windows; U; Windows NT 5.1; en-CA) AppleWebKit/534.13 (KHTML like Gecko) Chrome/9.0.597.98 Safari/534.13
Really? Here's Firefox 3.6, released 14 years ago, there were quite a lot of those:
Mozilla/5.0 (Windows; U; Windows NT 6.1; lt; rv:1.9.2) Gecko/20100115 Firefox/3.6
I remember running those old Firefox releases, those were the days. But to me, those look like entirely fake UAs, deliberately rotated to make it look like legitimate traffic. In comparison, Facebook seemed a bit more legit, in the sense that they don't fake it. most hits are from:
meta-externalagent/1.1 (+https://developers.facebook.com/docs/sharing/webmasters/crawler)
which, according their documentation:
crawls the web for use cases such as training AI models or improving products by indexing content directly
From what I could tell, it was even respecting our rather liberal robots.txt rules, in that it wasn't crawling the sprawling /blame/ or /commit/ endpoints, explicitly forbidden by robots.txt. So I've blocked the Facebook bot in robots.txt and, amazingly, it just went away. Good job Facebook, as much as I think you've given the empire to neo-nazis, cause depression and genocide, you know how to run a crawler, thanks. Huawei was blocked at the web server level, with a friendly 429 status code telling people to contact us (over email) if they need help. And they don't care: they're still hammering the server, from what I can tell, but then again, I didn't block the entire ASN just yet, just the blocks I found crawling the server over a couple hours.

A full asncounter run So what does a day in asncounter look like? Well, you start with a problem, say you're getting too much traffic and want to see where it's from. First you need to sample it. Typically, you'd do that with tcpdump or tailing a log file:
tail -F /var/log/apache2/*access*.log   awk ' print $2 '   asncounter
If you have lots of traffic or care about your users' privacy, you're not going to log IP addresses, so tcpdump is likely a good option instead:
tcpdump -q -n   asncounter --input-format=tcpdump --repl
If you really get a lot of traffic, you might want to get a subset of that to avoid overwhelming asncounter, it's not fast enough to do multiple gigabit/second, I bet, so here's only incoming SYN IPv4 packets:
tcpdump -q -n -Q in "tcp and tcp[tcpflags] & tcp-syn != 0 and (port 80 or port 443)"   asncounter --input-format=tcpdump --repl
In any case, at this point you're staring at a process, just sitting there. If you passed the --repl or --manhole arguments, you're lucky: you have a Python shell inside the program. Otherwise, send SIGHUP to the thing to have it dump the nice tables out:
pkill -HUP asncounter
Here's an example run:
> awk ' print $2 ' /var/log/apache2/*access*.log   asncounter
INFO: using datfile ipasn_20250527.1600.dat.gz
INFO: collecting addresses from <stdin>
INFO: loading datfile /home/anarcat/.cache/pyasn/ipasn_20250527.1600.dat.gz...
INFO: finished reading data
INFO: loading /home/anarcat/.cache/pyasn/asnames.json
count   percent ASN AS
12779   69.33   66496   SAMPLE, CA
3361    18.23   None    None
366 1.99    66497   EXAMPLE, FR
337 1.83    16276   OVH, FR
321 1.74    8075    MICROSOFT-CORP-MSN-AS-BLOCK, US
309 1.68    14061   DIGITALOCEAN-ASN, US
128 0.69    16509   AMAZON-02, US
77  0.42    48090   DMZHOST, GB
56  0.3 136907  HWCLOUDS-AS-AP HUAWEI CLOUDS, HK
53  0.29    17621   CNCGROUP-SH China Unicom Shanghai network, CN
total: 18433
count   percent prefix  ASN AS
12779   69.33   192.0.2.0/24    66496   SAMPLE, CA
3361    18.23   None        
298 1.62    178.128.208.0/20    14061   DIGITALOCEAN-ASN, US
289 1.57    51.222.0.0/16   16276   OVH, FR
272 1.48    2001:DB8::/48   66497   EXAMPLE, FR
235 1.27    172.160.0.0/11  8075    MICROSOFT-CORP-MSN-AS-BLOCK, US
94  0.51    2001:DB8:1::/48 66497   EXAMPLE, FR
72  0.39    47.128.0.0/14   16509   AMAZON-02, US
69  0.37    93.123.109.0/24 48090   DMZHOST, GB
53  0.29    27.115.124.0/24 17621   CNCGROUP-SH China Unicom Shanghai network, CN
Those numbers are actually from my home network, not GitLab. Over there, the battle still rages on, but at least the vampire bots are banging their heads against the solid Nginx wall instead of eating the fragile heart of GitLab. We had a significant improvement in latency thanks to the Facebook and Huawei blocks... Here are the "workhorse request duration stats" for various time ranges, 20h after the block:
range mean max stdev
20h 449ms 958ms 39ms
7d 1.78s 5m 14.9s
30d 2.08s 3.86m 8.86s
6m 901ms 27.3s 2.43s
We went from two seconds mean to 500ms! And look at that standard deviation! 39ms! It was ten seconds before! I doubt we'll keep it that way very long but for now, it feels like I won a battle, and I didn't even have to setup anubis or go-away, although I suspect that will unfortunately come. Note that asncounter also supports exporting Prometheus metrics, but you should be careful with this, as it can lead to cardinal explosion, especially if you track by prefix (which can be disabled with --no-prefixes . Folks interested in more details should read the fine manual for more examples, usage, and discussion. It shows, among other things, how to effectively block lots of networks from Nginx, aggregate multiple prefixes, block entire ASNs, and more! So there you have it: I now have the tool I wish I had 20 years ago. Hopefully it will stay useful for another 20 years, although I'm not sure we'll have still have internet in 20 years. I welcome constructive feedback, "oh no you rewrote X", Grafana dashboards, bug reports, pull requests, and "hell yeah" comments. Hacker News, let it rip, I know you can give me another juicy quote for my blog. This work was done as part of my paid work for the Tor Project, currently in a fundraising drive, give us money if you like what you read.

30 May 2025

Russell Coker: Service Setup Difficulties

Marco wrote a blog post opposing hyperscale systems which included We want to use an hyperscaler cloud because our developers do not want to operate a scalable and redundant database just means that you need to hire competent developers and/or system administrators. [1]. I previously wrote a blog post Why Clusters Usually Don t Work [2] and I believe that all the points there are valid today and possibly exacerbated by clusters getting less direct use as clustering is increasingly being done by hyperscale providers. Take a basic need, a MySQL or PostgreSQL database for example. You want it to run and basically do the job and to have good recovery options. You could set it up locally, run backups, test the backups, have a recovery plan for failures, maybe have a hot-spare server if it s really important, have tests for backups and hot-spare server, etc. Then you could have documentation for this so if the person who set it up isn t available when there s a problem they will be able to find out what to do. But the hyperscale option is to just select a database in your provider and have all this just work. If the person who set it up isn t available for recovery in the event of failure the company can just put out a job advert for person with experience on cloud company X and have them just immediately go to work on it. I don t like hyperscale providers as they are all monopolistic companies that do anti-competitive actions. Google should be broken up, Android development and the Play Store should be separated from Gmail etc which should be separated from search and adverts, and all of them should be separated from the GCP cloud service. Amazon should be broken up, running the Amazon store should be separated from selling items on the store, which should be separated from running a video on demand platform, and all of them should be separated from the AWS cloud. Microsoft should be broken up, OS development should be separated from application development all of that should be separated from cloud services (Teams and Office 365), and everything else should be separate from the Azure cloud system. But the cloud providers offer real benefits at small scale. Running a MySQL or PostgreSQL database for local services is easy, it s a simple apt command to install it and then it basically works. Doing backup and recovery isn t so easy. One could say just hire competent people but if you do hire competent people do you want them running MySQL databases etc or have them just click on the create mysql database option on a cloud control panel and then move on to more important things? The FreedomBox project is a great project for installing and managing home/personal services [3]. But it s not about running things like database servers, it s for a high level running mail servers and other things for the user not for the developer. The Debian packaging of Open Stack looks interesting [4], it s a complete setup for running your own hyper scale cloud service. For medium and large organisations running Open Stack could be a good approach. But for small organisations it s cheaper and easier to just use a cloud service to run things. The issue of when to run things in-house and when to put them in the cloud is very complex. I think that if the organisation is going to spend less money on cloud services than on the salary of one sysadmin then it s probably best to have things in the cloud. When cloud costs start to exceed the salary of one person who manages systems then having them spend the extra time and effort to run things locally starts making more sense. There is also an opportunity cost in having a good sysadmin work on the backups for all the different systems instead of letting the cloud provider just do it. Another possibility of course is to run things in-house on low end hardware and just deal with the occasional downtime to save money. Knowingly choosing less reliability to save money can be quite reasonable as long as you have considered the options and all the responsible people are involved in the discussion. The one situation that I strongly oppose is having hyper scale services setup by people who don t understand them. Running a database server on a cloud service because you don t want to spend the time managing it is a reasonable choice in many situations. Running a database server on a cloud service because you don t understand how to setup a database server is never a good choice. While the cloud services are quite resilient there are still ways of breaking the overall system if you don t understand it. Also while it is quite possible for someone to know how to develop for databases including avoiding SQL injection etc but be unable to setup a database server that s probably not going to be common, probably if someone can t set it up (a generally easy task) then they can t do the hard tasks of making it secure.

Russell Coker: Machine Learning Security

I just read an interesting blog post about ML security recommended by Bruce Schneier [1]. This approach of having 2 AI systems where one processes user input and the second performs actions on quarantined data is good and solves some real problems. But I think the bigger issue is the need to do this. Why not have a multi stage approach, instead of a single user input to do everything (the example given is Can you send Bob the document he requested in our last meeting? Bob s email and the document he asked for are in the meeting notes file ) you could have get Bob s email address from the meeting notes file followed by create a new email to that address and find the document etc. A major problem with many plans for ML systems is that they are based around automating relatively simple tasks. The example of sending an email based on meeting notes is a trivial task that s done many times a day but for which expressing it verbally isn t much faster than doing it the usual way. The usual way of doing such things (manually finding the email address from the meeting notes etc) can be accelerated without ML by having a recent documents access method that gets the notes, having the email address be a hot link to the email program (IE wordprocessor or note taking program being able to call the MUA), having a put all data objects of type X into the clipboard (where X can be email address, URL, filename, or whatever), and maybe optimising the MUA UI. The problems that people are talking about solving via ML and treating everything as text to be arbitrarily parsed can in many cases by solved by having the programs dealing with the data know what they have and have support for calling system services accordingly. The blog post suggests a problem of user fatigue from asking the user to confirm all actions, that is a real concern if the system is going to automate everything such that the user gives a verbal description of the problem and then says yes many times to confirm it. But if the user is at every step of the way pushing the process take this email address attach this file it won t be a series of yes operations with a risk of saying yes once too often. I think that one thing that should be investigated is better integration between services to allow working live on data. If in an online meeting someone says I ll work on task A please send me an email at the end of the meeting with all issues related to it then you should be able to click on their email address in the meeting software to bring up the MUA to send a message and then just paste stuff in. The user could then not immediately send the message and clicking on the email address again would bring up the message in progress to allow adding to it (the behaviour of most MUAs of creating a new message for every click on a mailto:// URL is usually not what you desire). In this example you could of course use ALT-TAB or other methods to switch windows to the email, but imagine the situation of having 5 people in the meeting who are to be emailed about different things and that wouldn t scale. Another thing for the meeting example is that having a text chat for a video conference is a standard feature now and being able to directly message individuals is available in BBB and probably some other online meeting systems. It shouldn t be hard to add a feature to BBB and similar programs to have each user receive an email at the end of the meeting with the contents of every DM chat they were involved in and have everyone in the meeting receive an emailed transcript of the public chat. In conclusion I think that there are real issues with ML security and something like this technology is needed. But for most cases the best option is to just not have ML systems do such things. Also there is significant scope for improving the integration of various existing systems in a non-ML way.

Utkarsh Gupta: FOSS Activites in May 2025

Here s my 68th monthly but brief update about the activities I ve done in the F/L/OSS world.

Debian
This was my 77th month of actively contributing to Debian. I became a DM in late March 2019 and a DD on Christmas 19! \o/ This month I ve just been sort of MIA, mostly because of a combination of the Canonical engineering sprints in Frankfurt, a bit of vacation in Italy, and then being sick. So didn t really get much done in Debian this month.

Ubuntu
This was my 53rd month of actively contributing to Ubuntu. I joined Canonical to work on Ubuntu full-time back in February 2021. Whilst I can t give a full, detailed list of things I did (there s so much and some of it might not be public yet!), here s a quick TL;DR of what I did:

Debian (E)LTS
Debian Long Term Support (LTS) is a project to extend the lifetime of all Debian stable releases to (at least) 5 years. Debian LTS is not handled by the Debian security team, but by a separate group of volunteers and companies interested in making it a success. And Debian Extended LTS (ELTS) is its sister project, extending support to the buster, stretch, and jessie release (+2 years after LTS support). This was my 68th month as a Debian LTS and 55th month as a Debian ELTS paid contributor.
Due to a combination of the Canonical engineering sprints in Frankfurt, a bit of vacation in Italy, and then being sick, I was barely able to do (E)LTS work. So this month, I worked for only 1.00 hours for LTS and 0 hours for ELTS. I did the following things:
  • [LTS] Attended the hourly LTS meeting on IRC. Summary here.

Until next time.
:wq for today.

Reproducible Builds (diffoscope): diffoscope 297 released

The diffoscope maintainers are pleased to announce the release of diffoscope version 297. This version includes the following changes:
[ Will Hollywood ]
* Add a LZMA comparator and tests.
You find out more by visiting the project homepage.

29 May 2025

Dirk Eddelbuettel: #48: r2u Talk Re-Recorded

Welcome to post 48 in the R4 series, and to video 8 in this series. Last week I had the honour of giving the opening talk at the 11eme Rencontres R at the Universit de Mons in Belgium as an invited plenary talk. Big thanks again to Philippe Grosjean and Kathy Huet for the invitation, and for organising a lovely conference. Being the opening talk, we were still sorting out projector issues when I started so I forgot to set a timer, and consequently ran out of time like a newbie. It occured to me that I could simply re-record the talk in front of my slides just as I do for my STAT 447 students. So I sat down this morning and did this, and the video is now online:

The slides are available as well. For questions or other feedback, please consider using the r2u GitHub repo issues section.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. If you like this or other open-source work I do, you can now sponsor me at GitHub.

Dirk Eddelbuettel: RcppDate 0.0.6: New Upstream

RcppDate wraps the featureful date library written by Howard Hinnant for use with R. This header-only modern C++ library has been in pretty wide-spread use for a while now, and adds to C++11/C++14/C++17 what will is (with minor modifications) the date library in C++20. The RcppDate package adds no extra R or C++ code and can therefore be a zero-cost dependency for any other project; yet a number of other projects decided to re-vendor it resulting in less-efficient duplication. Oh well. C est la vie. This release syncs with upstream release 3.0.4 made yesterday which contains a few PRs (including one by us) for the clang++-20 changes some of which we already had in release 0.0.5. We also made a routine update to the continuous integration.

Changes in version 0.0.6 (2025-05-29)
  • Updated to upstream version 3.0.4

Courtesy of my CRANberries, there is also a diffstat report for the most recent release. More information is available at the repository or the package page.

This post by Dirk Eddelbuettel originated on his Thinking inside the box blog. If you like this or other open-source work I do, you can sponsor me at GitHub.

Arthur Diniz: Bringing Kubernetes Back to Debian

I ve been part of the Debian Project since 2019, when I attended DebConf held in Curitiba, Brazil. That event sparked my interest in the community, packaging, and how Debian works as a distribution. In the early years of my involvement, I contributed to various teams such as the Python, Golang and Cloud teams, packaging dependencies and maintaining various tools. However, I soon felt the need to focus on packaging software I truly enjoyed, tools I was passionate about using and maintaining. That s when I turned my attention to Kubernetes within Debian.

A Broken Ecosystem The Kubernetes packaging situation in Debian had been problematic for some time. Given its large codebase and complex dependency tree, the initial packaging approach involved vendorizing all dependencies. While this allowed a somewhat functional package to be published, it introduced several long-term issues, especially security concerns. Vendorized packages bundle third-party dependencies directly into the source tarball. When vulnerabilities arise in those dependencies, it becomes difficult for Debian s security team to patch and rebuild affected packages system-wide. This approach broke Debian s best practices, and it eventually led to the abandonment of the Kubernetes source package, which had stalled at version 1.20.5. Due to this abandonment, critical bugs emerged and the package was removed from Debian s testing channel, as we can see in the package tracker.

New Debian Kubernetes Team Around this time, I became a Debian Maintainer (DM), with permissions to upload certain packages. I saw an opportunity to both contribute more deeply to Debian and to fix Kubernetes packaging. In early 2024, just before DebConf Busan in South Korea, I founded the Debian Kubernetes Team. The mission of the team was to repackage Kubernetes in a maintainable, security-conscious, and Debian-compliant way. At DebConf, I shared our progress with the broader community and received great feedback and more visibility, along with people interested in contributing to the team. Our first tasks was to migrate existing Kubernetes-related tools such as kubectx, kubernetes-split-yaml and kubetail into a dedicated namespace on Salsa, Debian s GitLab instance. Many of these tools were stored across different teams (like the Go team), and consolidating them helped us organize development and focus our efforts.

De-vendorizing Kubernetes Our main goal was to un-vendorize Kubernetes and bring it up-to-date with upstream releases. This meant:
  • Removing the vendor directory and all embedded third-party code.
  • Trimming the build scope to focus solely on building kubectl, Kubernetes CLI.
  • Using Files-Excluded in debian/copyright to cleanly drop unneeded files during source imports.
  • Rebuilding the dependency tree, ensuring all Go modules were separately packaged in Debian.
We used uscan, a standard Debian packaging tool that fetches upstream tarballs and prepares them accordingly. The Files-Excluded directive in our debian/copyright file instructed uscan to automatically remove unnecessary files during the repackaging process:
$ uscan
Newest version of kubernetes on remote site is 1.32.3, specified download version is 1.32.3
Successfully repacked ../v1.32.3 as ../kubernetes_1.32.3+ds.orig.tar.gz, deleting 30616 files from it.
The results were dramatic. By comparing the original upstream tarball with our repackaged version, we can see that our approach reduced the tarball size by over 75%:
$ du -h upstream-v1.32.3.tar.gz kubernetes_1.32.3+ds.orig.tar.gz
14M	upstream-v1.32.3.tar.gz
3.2M	kubernetes_1.32.3+ds.orig.tar.gz
This significant reduction wasn t just about saving space. By removing over 30,000 files, we simplified the package, making it more maintainable. Each dependency could now be properly tracked, updated, and patched independently, resolving the security concerns that had plagued the previous packaging approach.

Dependency Graph To give you an idea of the complexity involved in packaging Kubernetes for Debian, the image below is a dependency graph generated with debtree, visualizing all the Go modules and other dependencies required to build the kubectl binary. kubectl-depgraph This web of nodes and edges represents every module and its relationship during the compilation process of kubectl. Each box is a Debian package, and the lines connecting them show how deeply intertwined the ecosystem is. What might look like a mess of blue spaghetti is actually a clear demonstration of the vast and interconnected upstream world that tools like kubectl rely on. But more importantly, this graph is a testament to the effort that went into making kubectl build entirely using Debian-packaged dependencies only, no vendoring, no downloading from the internet, no proprietary blobs.

Upstream Version 1.32.3 and Beyond After nearly two years of work, we successfully uploaded version 1.32.3+ds of kubectl to Debian unstable. kubernetes/-/merge_requests/1 The new package also includes:
  • Zsh, Fish, and Bash completions installed automatically
  • Man pages and metadata for improved discoverability
  • Full integration with kind and docker for testing purposes

Integration Testing with Autopkgtest To ensure the reliability of kubectl in real-world scenarios, we developed a new autopkgtest suite that runs integration tests using real Kubernetes clusters created via Kind. Autopkgtest is a Debian tool used to run automated tests on binary packages. These tests are executed after the package is built but before it s accepted into the Debian archive, helping catch regressions and integration issues early in the packaging pipeline. Our test workflow validates kubectl by performing the following steps:
  • Installing Kind and Docker as test dependencies.
  • Spinning up two local Kubernetes clusters.
  • Switching between cluster contexts to ensure multi-cluster support.
  • Deploying and scaling a sample nginx application using kubectl.
  • Cleaning up the entire test environment to avoid side effects.
  • debian/tests/kubectl.sh

Popcon: Measuring Adoption To measure real-world usage, we rely on data from Debian s popularity contest (popcon), which gives insight into how many users have each binary installed. popcon-graph popcon-table Here s what the data tells us:
  • kubectl (new binary): Already installed on 2,124 systems.
  • golang-k8s-kubectl-dev: This is the Go development package (a library), useful for other packages and developers who want to interact with Kubernetes programmatically.
  • kubernetes-client: The legacy package that kubectl is replacing. We expect this number to decrease in future releases as more systems transition to the new package.
Although the popcon data shows activity for kubectl before the official Debian upload date, it s important to note that those numbers represent users who had it installed from upstream source-lists, not from the Debian repositories. This distinction underscores a demand that existed even before the package was available in Debian proper, and it validates the importance of bringing it into the archive.
Also worth mentioning: this number is not the real total number of installations, since users can choose not to participate in the popularity contest. So the actual adoption is likely higher than what popcon reflects.

Community and Documentation The team also maintains a dedicated wiki page which documents:
  • Maintained tools and packages
  • Contribution guidelines
  • Our roadmap for the upcoming Debian releases
https://debian-kubernetes.org

Looking Ahead to Debian 13 (Trixie) The next stable release of Debian will ship with kubectl version 1.32.3, built from a clean, de-vendorized source. This version includes nearly all the latest upstream features, and will be the first time in years that Debian users can rely on an up-to-date, policy-compliant kubectl directly from the archive. By comparing with upstream, our Debian package even delivers more out of the box, including shell completions, which the upstream still requires users to generate manually. In 2025, the Debian Kubernetes team will continue expanding our packaging efforts for the Kubernetes ecosystem. Our roadmap includes:
  • kubelet: The primary node agent that runs on each node. This will enable Debian users to create fully functional Kubernetes nodes without relying on external packages.
  • kubeadm: A tool for creating Kubernetes clusters. With kubeadm in Debian, users will then be able to bootstrap minimum viable clusters directly from the official repositories.
  • helm: The package manager for Kubernetes that helps manage applications through Kubernetes YAML files defined as charts.
  • kompose: A conversion tool that helps users familiar with docker-compose move to Kubernetes by translating Docker Compose files into Kubernetes resources.

Final Thoughts This journey was only possible thanks to the amazing support of the debian-devel-br community and the collective effort of contributors who stepped up to package missing dependencies, fix bugs, and test new versions. Special thanks to:
  • Carlos Henrique Melara (@charles)
  • Guilherme Puida (@puida)
  • Jo o Pedro Nobrega (@jnpf)
  • Lucas Kanashiro (@kanashiro)
  • Matheus Polkorny (@polkorny)
  • Samuel Henrique (@samueloph)
  • Sergio Cipriano (@cipriano)
  • Sergio Durigan Junior (@sergiodj)
I look forward to continuing this work, bringing more Kubernetes tools into Debian and improving the developer experience for everyone.

Arthur Diniz: Bringing Kubernetes Back to Debian

I ve been part of the Debian Project since 2019, when I attended DebConf held in Curitiba, Brazil. That event sparked my interest in the community, packaging, and how Debian works as a distribution. In the early years of my involvement, I contributed to various teams such as the Python, Golang and Cloud teams, packaging dependencies and maintaining various tools. However, I soon felt the need to focus on packaging software I truly enjoyed, tools I was passionate about using and maintaining. That s when I turned my attention to Kubernetes within Debian.

A Broken Ecosystem The Kubernetes packaging situation in Debian had been problematic for some time. Given its large codebase and complex dependency tree, the initial packaging approach involved vendorizing all dependencies. While this allowed a somewhat functional package to be published, it introduced several long-term issues, especially security concerns. Vendorized packages bundle third-party dependencies directly into the source tarball. When vulnerabilities arise in those dependencies, it becomes difficult for Debian s security team to patch and rebuild affected packages system-wide. This approach broke Debian s best practices, and it eventually led to the abandonment of the Kubernetes source package, which had stalled at version 1.20.5. Due to this abandonment, critical bugs emerged and the package was removed from Debian s testing channel, as we can see in the package tracker.

New Debian Kubernetes Team Around this time, I became a Debian Maintainer (DM), with permissions to upload certain packages. I saw an opportunity to both contribute more deeply to Debian and to fix Kubernetes packaging. In early 2024, just before DebConf Busan in South Korea, I founded the Debian Kubernetes Team. The mission of the team was to repackage Kubernetes in a maintainable, security-conscious, and Debian-compliant way. At DebConf, I shared our progress with the broader community and received great feedback and more visibility, along with people interested in contributing to the team. Our first tasks was to migrate existing Kubernetes-related tools such as kubectx, kubernetes-split-yaml and kubetail into a dedicated namespace on Salsa, Debian s GitLab instance. Many of these tools were stored across different teams (like the Go team), and consolidating them helped us organize development and focus our efforts.

De-vendorizing Kubernetes Our main goal was to un-vendorize Kubernetes and bring it up-to-date with upstream releases. This meant:
  • Removing the vendor directory and all embedded third-party code.
  • Trimming the build scope to focus solely on building kubectl, Kubernetes CLI.
  • Using Files-Excluded in debian/copyright to cleanly drop unneeded files during source imports.
  • Rebuilding the dependency tree, ensuring all Go modules were separately packaged in Debian.
We used uscan, a standard Debian packaging tool that fetches upstream tarballs and prepares them accordingly. The Files-Excluded directive in our debian/copyright file instructed uscan to automatically remove unnecessary files during the repackaging process:
$ uscan
Newest version of kubernetes on remote site is 1.32.3, specified download version is 1.32.3
Successfully repacked ../v1.32.3 as ../kubernetes_1.32.3+ds.orig.tar.gz, deleting 30616 files from it.
The results were dramatic. By comparing the original upstream tarball with our repackaged version, we can see that our approach reduced the tarball size by over 75%:
$ du -h upstream-v1.32.3.tar.gz kubernetes_1.32.3+ds.orig.tar.gz
14M	upstream-v1.32.3.tar.gz
3.2M	kubernetes_1.32.3+ds.orig.tar.gz
This significant reduction wasn t just about saving space. By removing over 30,000 files, we simplified the package, making it more maintainable. Each dependency could now be properly tracked, updated, and patched independently, resolving the security concerns that had plagued the previous packaging approach.

Dependency Graph To give you an idea of the complexity involved in packaging Kubernetes for Debian, the image below is a dependency graph generated with debtree, visualizing all the Go modules and other dependencies required to build the kubectl binary. kubectl-depgraph This web of nodes and edges represents every module and its relationship during the compilation process of kubectl. Each box is a Debian package, and the lines connecting them show how deeply intertwined the ecosystem is. What might look like a mess of blue spaghetti is actually a clear demonstration of the vast and interconnected upstream world that tools like kubectl rely on. But more importantly, this graph is a testament to the effort that went into making kubectl build entirely using Debian-packaged dependencies only, no vendoring, no downloading from the internet, no proprietary blobs.

Upstream Version 1.32.3 and Beyond After nearly two years of work, we successfully uploaded version 1.32.3+ds of kubectl to Debian unstable. kubernetes/-/merge_requests/1 The new package also includes:
  • Zsh, Fish, and Bash completions installed automatically
  • Man pages and metadata for improved discoverability
  • Full integration with kind and docker for testing purposes

Integration Testing with Autopkgtest To ensure the reliability of kubectl in real-world scenarios, we developed a new autopkgtest suite that runs integration tests using real Kubernetes clusters created via Kind. Autopkgtest is a Debian tool used to run automated tests on binary packages. These tests are executed after the package is built but before it s accepted into the Debian archive, helping catch regressions and integration issues early in the packaging pipeline. Our test workflow validates kubectl by performing the following steps:
  • Installing Kind and Docker as test dependencies.
  • Spinning up two local Kubernetes clusters.
  • Switching between cluster contexts to ensure multi-cluster support.
  • Deploying and scaling a sample nginx application using kubectl.
  • Cleaning up the entire test environment to avoid side effects.
  • debian/tests/kubectl.sh

Popcon: Measuring Adoption To measure real-world usage, we rely on data from Debian s popularity contest (popcon), which gives insight into how many users have each binary installed. popcon-graph popcon-table Here s what the data tells us:
  • kubectl (new binary): Already installed on 2,124 systems.
  • golang-k8s-kubectl-dev: This is the Go development package (a library), useful for other packages and developers who want to interact with Kubernetes programmatically.
  • kubernetes-client: The legacy package that kubectl is replacing. We expect this number to decrease in future releases as more systems transition to the new package.
Although the popcon data shows activity for kubectl before the official Debian upload date, it s important to note that those numbers represent users who had it installed from upstream source-lists, not from the Debian repositories. This distinction underscores a demand that existed even before the package was available in Debian proper, and it validates the importance of bringing it into the archive.
Also worth mentioning: this number is not the real total number of installations, since users can choose not to participate in the popularity contest. So the actual adoption is likely higher than what popcon reflects.

Community and Documentation The team also maintains a dedicated wiki page which documents:
  • Maintained tools and packages
  • Contribution guidelines
  • Our roadmap for the upcoming Debian releases
https://debian-kubernetes.org

Looking Ahead to Debian 13 (Trixie) The next stable release of Debian will ship with kubectl version 1.32.3, built from a clean, de-vendorized source. This version includes nearly all the latest upstream features, and will be the first time in years that Debian users can rely on an up-to-date, policy-compliant kubectl directly from the archive. By comparing with upstream, our Debian package even delivers more out of the box, including shell completions, which the upstream still requires users to generate manually. In 2025, the Debian Kubernetes team will continue expanding our packaging efforts for the Kubernetes ecosystem. Our roadmap includes:
  • kubelet: The primary node agent that runs on each node. This will enable Debian users to create fully functional Kubernetes nodes without relying on external packages.
  • kubeadm: A tool for creating Kubernetes clusters. With kubeadm in Debian, users will then be able to bootstrap minimum viable clusters directly from the official repositories.
  • helm: The package manager for Kubernetes that helps manage applications through Kubernetes YAML files defined as charts.
  • kompose: A conversion tool that helps users familiar with docker-compose move to Kubernetes by translating Docker Compose files into Kubernetes resources.

Final Thoughts This journey was only possible thanks to the amazing support of the debian-devel-br community and the collective effort of contributors who stepped up to package missing dependencies, fix bugs, and test new versions. Special thanks to:
  • Carlos Henrique Melara (@charles)
  • Guilherme Puida (@puida)
  • Jo o Pedro Nobrega (@jnpf)
  • Lucas Kanashiro (@kanashiro)
  • Matheus Polkorny (@polkorny)
  • Samuel Henrique (@samueloph)
  • Sergio Cipriano (@cipriano)
  • Sergio Durigan Junior (@sergiodj)
I look forward to continuing this work, bringing more Kubernetes tools into Debian and improving the developer experience for everyone.

Debian XMPP Team: XMPP/Jabber Debian 13 Trixie News

Debian 13 "Trixie" full freeze has started 2025-05-17, so this is a good time to take a look at some of the features, that this release will bring. Here we will focus on packages related to XMPP, a.k.a. Jabber. XMPP is a universal communication protocol for instant messaging, push notifications, IoT, WebRTC, and social applications. It has existed since 1999, originally called "Jabber", it has a diverse and active developers community. Clients Servers Libraries Gateways/Transports Not in Trixie

28 May 2025

Clint Adams: Potted meat is viewed differently by different cultures

I've been working on a multi-label email classification model. It's been a frustrating slog, fraught with challenges, including a lack of training data. Labeling emails is labor-intensive and error-prone. Also, I habitually delete certain classes of email immediately after its usefulness has been reduced. I use a CRM-114-based spam filtering system (actually I use two different isntances of the same mailreaver config, but that's another story), which is differently frustrating, but I delete spam when it's detected or when it's trained. Fortunately, there's no shortage of incoming spam, so I can collect enough, but for other, arguably more important labels, they arrive infrequently. So, those labels need to be excluded, or the small sample sizes wreck the training feedback loop. Currently, I have ten active labels, and even though the point of this is not to be a spam filter, spam is one of the labels. Out of curiosity, I decided to compare the performance of my three different models, and to do so on a neutral corpus (in other words, emails that none of them had ever been trained on). I grabbed the full TREC 2007 corpus and ran inference. The results were unexpected in many ways. For example, the Pearson correlation coefficient between my older CRM-114 model and my newer CRM-114 was only about 0.78. I was even more surprised by how poorly all three performed. Were they overfit to my email? So, I decided to look at the TREC corpus for the first time, and lo and behold, the first spam-labeled email I checked was something I would definitely train all three models with as non-spam, but ham for CRM-114 and an entirely different label for my experimental model.
Posted on 2025-05-28
Tags:

Jonathan Dowland: Linux Mount Namespaces

I've been refreshing myself on the low-level guts of Linux container technology. Here's some notes on mount namespaces. In the below examples, I will use more than one root shell simultaneously. To disambiguate them, the examples will feature a numbered shell prompt: 1# for the first shell, and 2# for the second. Preliminaries Namespaces are normally associated with processes and are removed when the last associated process terminates. To make them persistent, you have to bind-mount the corresponding virtual file from an associated processes's entry in /proc, to another path1. The receiving path needs to have its "propogation" property set to "private". Most likely your system's existing mounts are mostly "public". You can check the propogation setting for mounts with
1# findmnt -o+PROPAGATION
We'll create a new directory to hold mount namespaces we create, and set its Propagation to private, via a bind-mount of itself to itself.
1# mkdir /root/mntns
1# mount --bind --make-private /root/mntns /root/mntns
The namespace itself needs to be bind-mounted over a file rather than a directory, so we'll create one.
1# touch /root/mntns/1
Creating and persisting a new mount namespace
1# unshare --mount=/root/mntns/1
We are now 'inside' the new namespace in a new shell process. We'll change the shell prompt to make this clearer
PS1='inside# '
We can make a filesystem change, such as mounting a tmpfs
inside# mount -t tmpfs /mnt /mnt
inside# touch /mnt/hi-there
And observe it is not visible outside that namespace
2# findmnt /mnt
2# stat /mnt/hi-there
stat: cannot statx '/mnt/hi-there': No such file or directory
Back to the namespace shell, we can find an integer identifier for the namespace via the shell processes /proc entry:
inside# readlink /proc/$$/ns/mnt
It will be something like mnt:[4026533646]. From another shell, we can list namespaces and see that it exists:
2# lsns -t mnt
        NS TYPE NPROCS   PID USER             COMMAND
 
4026533646 mnt       1 52525 root             -bash
If we exit the shell that unshare created,
inside# exit
running lsns again should2 still list the namespace, albeit with the NPROCS column now reading 0.
2# lsns -t mnt
We can see that a virtual filesystem of type nsfs is mounted at the path we selected when we ran unshare:
2# grep /root/mntns/1 /proc/mounts 
nsfs /root/mntns/1 nsfs rw 0 0
Entering the namespace from another process This is relatively easy:
1# nsenter --mount=/root/mntns/1
1# stat /mnt/hi-there
  File: /mnt/hi-there
 
More to come in future blog posts! References These were particularly useful in figuring this out:

  1. This feels really weird to me. At least at first. I suppose it fits with the "everything is a file" philosophy.
  2. I've found lsns in util-linux 2.38.1 (from 2022-08-04) doesn't list mount namespaces with no associated processes; but 2.41 (from 2025-03-18) does. The fix landed in 2022-11-08. For extra fun, I notice that a namespace can be held persistent with a file descriptor which is unlinked from the filesystem

Yves-Alexis Perez: Running autopkgtests locally

As a small addendum to the last post, here are the relevant commands #debci helpfully provided. First, you need to install the autopkgtest package, obviously:

# apt install autopkgtest Then you need to create a Debian virtual machine to run the tests (put the sid.raw wherever you prefer):

# autopkgtest-build-qemu sid /tmp/sid.raw Then you can run the tests themselves, using the just created virtual machine. The autopkgtest command can use the tests from various sources, using the last argument to the command. In my case what was the most helpful was to run the tests from my git clone (which uses gbp) so I could edit the tests directly. So I didn't give anything for testsrc (but . would work as well I guess).

$ autopkgtest -BU --add-apt-release=unstable --pin-packages=unstable=strongswan -- qemu /tmp/sid.raw --ram-size=4096 --cpus=1 Then I could play with the tests themselves, the number of CPU for the Qemu VM, and run everything in a loop.

Bits from Debian: Debian welcomes the 2025 GSOC contributors/students

GSoC logo We are very excited to announce that Debian has selected nine contributors to work under mentorship on a variety of projects with us during the Google Summer of Code. Here is a list of the projects and students, along with details of the tasks to be performed.
Project: Quality assurance and continuous integration for biological and medical applications inside Debian Deliverables of the project: Continuous integration tests for Debian Med applications lacking a test, Quality Assurance review and bug fixing if issues might be uncovered.
Project: Device-specific Tweaks Management Deliverables of the project: Analysis and discussion of the current state of device tweaks management in Debian and Mobian. Proposal for a unified, run-time approach. Packaging of this service and tweaks data/configuration for at least one device.
Project: Enhancing Debian packages with ROCm GPU acceleration Deliverables of the project: New Debian packages with GPU support. Enhanced GPU support within existing Debian packages. More autopackagetests running on the Debian ROCm CI.
Project: Make Debian for Raspberry Pi Build Again Deliverables of the project: Refreshing the set of daily-built images. Having the set of daily-built images become automatic again that is, go back to the promise of having it daily-built. Write an Ansible playbook/Chef recipe/Puppet whatsitsname to define a virtual serve and have it build daily. Do the (very basic!) hardware testing on several Raspberry computers. Do note, naturally, this will require having access to the relevant hardware.
Project: Package LLM Inference Libraries Deliverables of the project: Eventually I hope we can make vLLM into Debian archive, based on which we can deliver something for LLM inference out-of-the-box. If the amount of work eventually turns to be beyond my expectation, I'm still happy to see how far we can go towards this goal. If the amount of work required for vLLM is less than I expected, we can also look at something else like SGLang, another open source LLM inference library.
Project: Autopkgtests for the rsync package Deliverables of the project: Autopkgtests for the rsync package.
Project: Enhancing Salsa CI in Debian Deliverables of the project: More features, robustness, speed.
Congratulations and welcome to all the contributors! The Google Summer of Code program is possible in Debian thanks to the efforts of Debian Developers and Debian Contributors that dedicate part of their free time to mentor contributors and outreach tasks. Join us and help extend Debian! You can follow the contributors' weekly reports on the debian-outreach mailing-list, chat with us on our IRC channel or reach out to the individual projects' team mailing lists.

Bits from Debian: Debian Day 2025 - call for celebration

Each year on August the 16th, we celebrate the Debian Project Anniversary. Several communities around the world join us in celebrating "Debian Day" with local events, parties, or gatherings. So, how about celebrating the 32nd anniversary of the Debian Project in 2025 in your city? As the 16th of August falls on a Saturday this year, we believe it is great timing to gather people around your event. We invite you and your local community to organize a Debian Day by hosting an event with talks, workshops, a bug squashing party, or OpenPGP keysigning gathering, etc. You could also hold a meeting with others in the Debian community in a smaller social setting like a bar/pizzeria/cafeteria/restaurant to celebrate. In other words, any type of celebrating is valid! Remember to add your city to the Debian Day wiki page There is a list of Debian Local Groups around the world. If your city is listed, talk to them to organize DebianDay together. To inspire you and your local community, see some photos from 2023 and 2024 Let's use hashtags #DebianDay #DebianDay2025 on social media. debianday-logo

Next.

Previous.