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It’s been over 6 years since my last post comparing 3G data plans in Australia.
I’m currently using Aldi Mobile [1]. They have a $15 package which gives 3G of data and unlimited calls and SMS in Australia for 30 days, and a $25 package that gives 20G of data and unlimited international calls to 15 unspecified countries (presumably the US and much of the EU). It’s on the Telstra network so has good access all around Australia. I’m on the grandfathered $20 per 30 days plan which gives me more than 3G of data (not sure how much but I need more than 3G) while costing less than the current offer of $25.
| Telco |
Cost |
Data |
Network |
Calling |
| Aldi |
$15/30 days |
3G |
Telstra |
Unlimited National |
| Aldi |
$25/30 days |
20G |
Telstra |
Unlimited International |
| Dodo [2] |
$5/month |
none |
Optus |
Unlimited National + Unlimited International SMS |
| Moose [3] |
$8.80/month |
1G |
Optus |
300min national calls + Unlimited National SMS |
| AmaySIM [4] |
$10/month |
2G |
Optus |
Unlimited National |
| Kogan [5] |
$135/year |
100G |
Vodafone |
Unlimited National |
| Kogan |
$180/year |
180G |
Vodafone |
Unlimited National |
| Dodo |
$20/month |
12G |
Optus |
Unlimited National + Unlimited International SMS + 100mins International talk |
In the above table I put Aldi at the top because Telstra has the best network. If you want to use a mobile phone anywhere in Australia then Telstra is the best choice. If you only care about city areas then the other networks are usually good enough. The rest of the services are in order of price, cheapest first. For every service I only mentioned the offerings that are price competitive.
I didn’t list the offerings that are larger than these. There are offerings of 300G/year or more, but most people don’t need them. Every service in this table has more expensive offerings with more data.
Please inform me in the comments of any services I missed.
The G-Force Wikipedia page says that humans can survive 20G horizontally “eyes in” for up to 10 seconds and 10G for 1 minute.
An accelerator of 14G for 10 seconds (well below the level that’s unsafe) gives a speed of mach 4 and an acceleration distance of just under 7km. Launching a 100 metric ton spacecraft in that way would require 14MW at the end of the launch path plus some extra for the weight of the part that contains magnets which would be retrieved by parachute. 14MW is a small fraction of the power used by a train or tram network and brown-outs of the transit network is something that they deal with so such a launch could be powered by diverting power from a transit network. The Rocky Mountains in the US peak at 4.4KM above sea level, so a magnetic launch that starts 2.6KM below sea level and extends the height of the Rocky Mountains would do.
A speed of mach 4 vertically would get a height of 96Km if we disregard drag, that’s almost 1/4 of the orbital altitude of the ISS. This seems like a more practical way to launch humans into space than a space elevator.
The Mass Driver page on Wikipedia documents some of the past research on launching satellites that way, with shorter launch hardware and significantly higher G forces.
Business Insider has an informative article about the way that Google users can get locked out with no apparent reason and no recourse [1]. Something to share with clients when they consider putting everything in “the cloud”.
Vice has an interestoing article about people jailbreaking used Teslas after Tesla has stolen software licenses that were bought with the car [2].
The Atlantic has an interesting article titled This Article Won’t Change Your Mind [3]. It’s one of many on the topic of echo chambers but has some interesting points that others don’t seem to cover, such as regarding the benefits of groups when not everyone agrees.
Inequality.org has lots of useful information about global inequality [4].
Jeffrey Goldberg has an insightful interview with Barack Obama for the Atlantic about the future course of American politics and a retrospective on his term in office [5].
A Game Designer’s Analysis Of QAnon is an insightful Medium article comparing QAnon to an augmented reality game [6]. This is one of the best analysis of QAnon operations that I’ve seen.
Decrypting Rita is one of the most interesting web comics I’ve read [7]. It makes good use of side scrolling and different layers to tell multiple stories at once.
PC Mag has an article about the new features in Chrome 87 to reduce CPU use [8]. On my laptop I have 1/3 of all CPU time being used when it is idle, the majority of which is from Chrome. As the CPU has 2 cores this means the equivalent of 1 core running about 66% of the time just for background tabs. I have over 100 tabs open which I admit is a lot. But it means that the active tabs (as opposed to the plain HTML or PDF ones) are averaging more than 1% CPU time on an i7 which seems obviously unreasonable. So Chrome 87 doesn’t seem to live up to Google’s claims.
The movie Bad President starring Stormy Daniels as herself is out [9]. Poe’s Law is passe.
Interesting summary of Parler, seems that it was designed by the Russians [10].
Wired has an interesting article about Indistinguishability Obfuscation, how to encrypt the operation of a program [11].
Joerg Jaspert wrote an interesting blog post about the difficulties packagine Rust and Go for Debian [12]. I think that the problem is many modern languages aren’t designed well for library updates. This isn’t just a problem for Debian, it’s a problem for any long term support of software that doesn’t involve transferring a complete archive of everything and it’s a problem for any disconnected development (remote sites and sites dealing with serious security. Having an automatic system for downloading libraries is fine. But there should be an easy way of getting the same source via an archive format (zip will do as any archive can be converted to any other easily enough) and with version numbers.
Version 2.0 of ZFS has been released, it’s now known as OpenZFS and has a unified release for Linux and BSD which is nice.
One new feature is persistent L2ARC (which means that when you use SSD or NVMe to cache hard drives that cache will remain after a reboot) is an obvious feature that was needed for a long time.
The Zstd compression invented by Facebook is the best way of compressing things nowadays, it’s generally faster while giving better compression than all other compression algorithms and it’s nice to have that in the filesystem.
The PAM module for encrypted home directories is interesting, I haven’t had a need for directory level encryption as block device encryption has worked well for my needs. But there are good use cases for directory encryption.
I just did a quick test of OpenZFS on a VM, the one thing it doesn’t do is let me remove a block device accidentally added to a zpool. If you have a zpool with a RAID-Z array and mistakenly add a new disk as a separate device instead of replacing a part of the RAID-Z then you can’t remove it. There are patches to allow such removal but they didn’t appear to get in to the OpenZFS 2.0.0 release.
For my use ZFS on Linux 0.8.5 has been working fairly well and apart from the inability to remove a mistakenly added device I haven’t had any problems with it. So I have no immediate plans to upgrade existing servers. But if I was about to install a new ZFS server I’d definitely use the latest version.
People keep asking about license issues. I’m pretty sure that Oracle lawyers have known about sites like zfsonlinux.org for years, the fact that they have decided not to do anything about it seems like clear evidence that it’s OK for me to keep using that code.
One of my workstations is running Debian/Unstable with KDE and SDDM on an AMD Radeon R7 260X video card. Recently it stopped displaying things correctly after a reboot, all the icons failed to display as well as many of the Qt controls. When I ran a KDE application from the command line I got the error “QSGTextureAtlas: texture atlas allocation failed, code=501“. Googling that error gave a blog post about a very similar issue in 2017 [1]. From that blog post I learned that I could stop the problem by setting MESA_EXTENSION_OVERRIDE=”-GL_EXT_bgra -GL_EXT_texture_format_BGRA8888″ in the environment. In a quick test I found that the environment variable setting worked, making the KDE apps display correctly and not report an error about a texture atlas.
I created a file ~/.config/plasma-workspace/env/bgra.sh with the following contents:
export MESA_EXTENSION_OVERRIDE="-GL_EXT_bgra -GL_EXT_texture_format_BGRA8888"
Then after the next login things worked as desired!
Now the issue is, where is the bug? GL, X, and the internals of KDE are things I don’t track much. I welcome suggestions from readers of my blog as to what the culprit might be and where to file a Debian bug – or a URL to a Debian bug report if someone has already filed one.
Update
When I run the game warzone2100 with this setting it crashes with the below output. So this Mesa extension override isn’t always a good thing, just solves one corner case of a bug.
$ warzone2100
/usr/bin/gdb: warning: Couldn't determine a path for the index cache directory.
27 ../sysdeps/unix/sysv/linux/wait4.c: No such file or directory.
No frame at level 0x7ffc3392ab50.
Saved dump file to '/home/etbe/.local/share/warzone2100-3.3.0//logs/warzone2100.gdmp-VuGo2s'
If you create a bugreport regarding this crash, please include this file.
Segmentation fault (core dumped)
Update 2
Carsten provided the REAL solution to this, run “apt remove libqt5quick5-gles” which will automatically install “libqt5quick5” which makes things work. Another workstation I run that tracks Testing had libqt5quick5 installed which was why it didn’t have the problem.
The system in question had most of KDE removed due to package dependency issues when tracking Unstable and when I reinstalled it I guess the wrong one was installed.
I’ve had a saga of getting 4K monitors to work well. My latest issue has been video playing, the dreaded mplayer error about the system being too slow. My previous post about 4K was about using DisplayPort to get more than 30Hz scan rate at 4K [1]. I now have a nice 60Hz scan rate which makes WW2 documentaries display nicely among other things.
But when running a 4K monitor on a 3.3GHz i5-2500 quad-core CPU I can’t get a FullHD video to display properly. Part of the process of decoding the video and scaling it to 4K resolution is too slow, so action scenes in movies lag. When running a 2560*1440 monitor on a 2.4GHz E5-2440 hex-core CPU with the mplayer option “-lavdopts threads=3” everything is great (but it fails if mplayer is run with no parameters). In doing tests with apparent performance it seemed that the E5-2440 CPU gains more from the threaded mplayer code than the i5-2500, maybe the E5-2440 is more designed for server use (it’s in a Dell PowerEdge T320 while the i5-2500 is in a random white-box system) or maybe it’s just because it’s newer. I haven’t tested whether the i5-2500 system could perform adequately at 2560*1440 resolution.
The E5-2440 system has an ATI HD 6570 video card which is old, slow, and only does PCIe 2.1 which gives 5GT/s or 8GB/s. The i5-2500 system has a newer ATI video card that is capable of PCIe 3.0, but “lspci -vv” as root says “LnkCap: Port #0, Speed 8GT/s, Width x16” and “LnkSta: Speed 5GT/s (downgraded), Width x16 (ok)”. So for reasons unknown to me the system with a faster PCIe 3.0 video card is being downgraded to PCIe 2.1 speed. A quick check of the web site for my local computer store shows that all ATI video cards costing less than $300 have PCI3 3.0 interfaces and the sole ATI card with PCIe 4.0 (which gives double the PCIe speed if the motherboard supports it) costs almost $500. I’m not inclined to spend $500 on a new video card and then a greater amount of money on a motherboard supporting PCIe 4.0 and CPU and RAM to go in it.
According to my calculations 3840*2160 resolution at 24bpp (probably 32bpp data transfers) at 30 frames/sec means 3840*2160*4*30/1024/1024=950MB/s. PCIe 2.1 can do 8GB/s so that probably isn’t a significant problem.
I’d been planning on buying a new video card for the E5-2440 system, but due to some combination of having a better CPU and lower screen resolution it is working well for video playing so I can save my money.
As an aside the T320 is a server class system that had been running for years in a corporate DC. When I replaced the high speed SAS disks with SSDs SATA disks it became quiet enough for a home workstation. It works very well at that task but the BIOS is quite determined to keep the motherboard video running due to the remote console support. So swapping monitors around was more pain than I felt like going through, I just got it working and left it. I ordered a special GPU power cable but found that the older video card that doesn’t need an extra power cable performs adequately before the cable arrived.
Here is a table comparing the systems.
|
2560*1440 works well |
3840*2160 goes slow |
| System |
Dell PowerEdge T320 |
White Box PC from rubbish |
| CPU |
2.4GHz E5-2440 |
3.3GHz i5-2500 |
| Video Card |
ATI Radeon HD 6570 |
ATI Radeon R7 260X |
| PCIe Speed |
PCIe 2.1 – 8GB/s |
PCIe 3.0 downgraded to PCIe 2.1 – 8GB/s |
Conclusion
The ATI Radeon HD 6570 video card is one that I had previously tested and found inadequate for 4K support, I can’t remember if it didn’t work at that resolution or didn’t support more than 30Hz scan rate. If the 2560*1440 monitor dies then it wouldn’t make sense to buy anything less than a 4K monitor to replace it which means that I’d need to get a new video card to match. But for the moment 2560*1440 is working well enough so I won’t upgrade it any time soon. I’ve already got the special power cable (specified as being for a Dell PowerEdge R610 for anyone else who wants to buy one) so it will be easy to install a powerful video card in a hurry.
I’ve been investigating the options for tracking system statistics to diagnose performance problems. The idea is to track all sorts of data about the system (network use, disk IO, CPU, etc) and look for correlations at times of performance problems. DataDog is pretty good for this but expensive, it’s apparently based on or inspired by the Etsy Statsd. It’s claimed that the gnocchi-statsd is the best implementation of the protoco used by the Etsy Statsd, so I decided to install that.
I use Debian/Buster for this as that’s what I’m using for the hardware that runs KVM VMs. Here is what I did:
# it depends on a local MySQL database
apt -y install mariadb-server mariadb-client
# install the basic packages for gnocchi
apt -y install gnocchi-common python3-gnocchiclient gnocchi-statsd uuid
In the Debconf prompts I told it to “setup a database” and not to manage keystone_authtoken with debconf (because I’m not doing a full OpenStack installation).
This gave a non-working configuration as it didn’t configure the MySQL database for the [indexer] section and the sqlite database that was configured didn’t work for unknown reasons. I filed Debian bug #971996 about this [1]. To get this working you need to edit /etc/gnocchi/gnocchi.conf and change the url line in the [indexer] section to something like the following (where the password is taken from the [database] section).
url = mysql+pymysql://gnocchi-common:PASS@localhost:3306/gnocchidb
To get the statsd interface going you have to install the gnocchi-statsd package and edit /etc/gnocchi/gnocchi.conf to put a UUID in the resource_id field (the Debian package uuid is good for this). I filed Debian bug #972092 requesting that the UUID be set by default on install [2].
Here’s an official page about how to operate Gnocchi [3]. The main thing I got from this was that the following commands need to be run from the command-line (I ran them as root in a VM for test purposes but would do so with minimum privs for a real deployment).
gnocchi-api
gnocchi-metricd
To communicate with Gnocchi you need the gnocchi-api program running, which uses the uwsgi program to provide the web interface by default. It seems that this was written for a version of uwsgi different than the one in Buster. I filed Debian bug #972087 with a patch to make it work with uwsgi [4]. Note that I didn’t get to the stage of an end to end test, I just got it to basically run without error.
After getting “gnocchi-api” running (in a terminal not as a daemon as Debian doesn’t seem to have a service file for it), I ran the client program “gnocchi” and then gave it the “status” command which failed (presumably due to the metrics daemon not running), but at least indicated that the client and the API could communicate.
Then I ran the “gnocchi-metricd” and got the following error:
2020-10-12 14:59:30,491 [9037] ERROR gnocchi.cli.metricd: Unexpected error during processing job
Traceback (most recent call last):
File "/usr/lib/python3/dist-packages/gnocchi/cli/metricd.py", line 87, in run
self._run_job()
File "/usr/lib/python3/dist-packages/gnocchi/cli/metricd.py", line 248, in _run_job
self.coord.update_capabilities(self.GROUP_ID, self.store.statistics)
File "/usr/lib/python3/dist-packages/tooz/coordination.py", line 592, in update_capabilities
raise tooz.NotImplemented
tooz.NotImplemented
At this stage I’ve had enough of gnocchi. I’ll give the Etsy Statsd a go next.
Update
Thomas has responded to this post [5]. At this stage I’m not really interested in giving Gnocchi another go. There’s still the issue of the indexer database which should be different from the main database somehow and sqlite (the config file default) doesn’t work.
I expect that if I was to persist with Gnocchi I would encounter more poorly described error messages from the code which either don’t have Google hits when I search for them or have Google hits to unanswered questions from 5+ years ago.
The Gnocchi systemd config files are in different packages to the programs, this confused me and I thought that there weren’t any systemd service files. I had expected that installing a package with a daemon binary would also get the systemd unit file to match.
The cluster features of Gnocchi are probably really good if you need that sort of thing. But if you have a small instance (EG a single VM server) then it’s not needed. Also one of the original design ideas of the Etsy Statsd was that UDP was used because data could just be dropped if there was a problem. I think for many situations the same concept could apply to the entire stats service.
If the other statsd programs don’t do what I need then I may give Gnocchi another go.
For the Linux Users of Victoria (LUV) I’ve run video conferences on Jitsi and BBB (see my previous post about BBB vs Jitsi [1]). One issue with video conferences is the bandwidth requirements.
The place I’m hosting my video conference server has a NBN link with allegedly 40Mb/s transmission speed and 100Mb/s reception speed. My tests show that it can transmit at about 37Mb/s and receive at speeds significantly higher than that but also quite a bit lower than 100Mb/s (around 60 or 70Mb/s). For a video conference server you have a small number of sources of video and audio and a larger number of targets as usually most people will have their microphones muted and video cameras turned off. This means that the transmission speed is the bottleneck. In every test the reception speed was well below half the transmission speed, so the tests confirmed my expectation that transmission was the only bottleneck, but the reception speed was higher than I had expected.
When we tested bandwidth use the maximum upload speed we saw was about 4MB/s (32Mb/s) with 8+ video cameras and maybe 20 people seeing some of the video (with a bit of lag). We used 3.5MB/s (28Mb/s) when we only had 6 cameras which seemed to be the maximum for good performance.
In another test run we had 4 people all sending video and the transmission speed was about 260KB/s.
I don’t know how BBB manages the small versions of video streams. It might reduce the bandwidth when the display window is smaller.
I don’t know the resolutions of the cameras. When you start sending video in BBB you are prompted for the “quality” with “medium” being default. I don’t know how different camera hardware and different choices about “quality” affect bandwidth.
These tests showed that for the cameras we had available a small group of people video chatting a 100/40 NBN link (the fastest Internet link in Australia that’s not really expensive) a small group of people can be all sending video or a medium size group of people can watch video streams from a small group.
For meetings of the typical size of LUV meetings we won’t have a bandwidth problem.
There is one common case that I haven’t yet tested, where there is a single video stream that many people are watching. If 4 people are all sending video with 260KB/s transmission bandwidth then 1 person could probably send video to 4 for 65KB/s. Doing some simple calculations on those numbers implies that we could have 1 person sending video to 240 people without running out of bandwidth. I really doubt that would work, but further testing is needed.
I’ve tried setting up the Qemu (in this case KVM as it uses the Qemu code in question) 9P/Virtfs filesystem for sharing files to a VM. Here is the Qemu documentation for it [1].
VIRTFS="-virtfs local,path=/vmstore/virtfs,security_model=mapped-xattr,id=zz,writeout=immediate,fmode=0600,dmode=0700,mount_tag=zz"
VIRTFS="-virtfs local,path=/vmstore/virtfs,security_model=passthrough,id=zz,writeout=immediate,mount_tag=zz"
Above are the 2 configuration snippets I tried on the server side. The first uses mapped xattrs (which means that all files will have the same UID/GID and on the host XATTRs will be used for storing the Unix permissions) and the second uses passthrough which requires KVM to run as root and gives the same permissions on the host as on the VM. The advantages of passthrough are better performance through writing less metadata and having the same permissions in host and VM. The advantages of mapped XATTRs are running KVM/Qemu as non-root and not having a SUID file in the VM imply a SUID file in the host.
Here is the link to Bonnie++ output comparing Ext3 on a KVM block device (stored on a regular file in a BTRFS RAID-1 filesystem on 2 SSDs on the host), a NFS share from the host from the same BTRFS filesystem, and virtfs shares of the same filesystem. The only tests that Ext3 doesn’t win are some of the latency tests, latency is based on the worst-case not the average. I expected Ext3 to win most tests, but didn’t expect it to lose any latency tests.
Here is a link to Bonnie++ output comparing just NFS and Virtfs. It’s obvious that Virtfs compares poorly, giving about half the performance on many tests. Surprisingly the only tests where Virtfs compared well to NFS were the file creation tests which I expected Virtfs with mapped XATTRs to do poorly due to the extra metadata.
Here is a link to Bonnie++ output comparing only Virtfs. The options are mapped XATTRs with default msize, mapped XATTRs with 512k msize (I don’t know if this made a difference, the results are within the range of random differences), and passthrough. There’s an obvious performance benefit in passthrough for the small file tests due to the less metadata overhead, but as creating small files isn’t a bottleneck on most systems a 20% to 30% improvement in that area probably doesn’t matter much. The result from the random seeks test in passthrough is unusual, I’ll have to do more testing on that.
SE Linux
On Virtfs the XATTR used for SE Linux labels is passed through to the host. So every label used in a VM has to be valid on the host and accessible to the context of the KVM/Qemu process. That’s not really an option so you have to use the context mount option. Having the mapped XATTR mode work for SE Linux labels is a necessary feature.
Conclusion
The msize mount option in the VM doesn’t appear to do anything and it doesn’t appear in /proc/mounts, I don’t know if it’s even supported in the kernel I’m using.
The passthrough and mapped XATTR modes give near enough performance that there doesn’t seem to be a benefit of one over the other.
NFS gives significant performance benefits over Virtfs while also using less CPU time in the VM. It has the issue of files named .nfs* hanging around if the VM crashes while programs were using deleted files. It’s also more well known, ask for help with an NFS problem and you are more likely to get advice than when asking for help with a virtfs problem.
Virtfs might be a better option for accessing databases than NFS due to it’s internal operation probably being a better map to Unix filesystem semantics, but running database servers on the host is probably a better choice anyway.
Virtfs generally doesn’t seem to be worth using. I had hoped for performance that was better than NFS but the only benefit I seemed to get was avoiding the .nfs* file issue.
The best options for storage for a KVM/Qemu VM seem to be Ext3 for files that are only used on one VM and for which the size won’t change suddenly or unexpectedly (particularly the root filesystem) and NFS for everything else.
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