Simon Krenger

I like to use the Prometheus node_exporter to get metrics about my hardware. However some hardware (such as my X300M-STX mainboard) exposes sensors with some rather nonsensical values:

[..]
node_hwmon_temp_celsius{chip="platform_nct6775_656",sensor="temp13"} 49.75
node_hwmon_temp_celsius{chip="platform_nct6775_656",sensor="temp15"} 3.892313987e+06
node_hwmon_temp_celsius{chip="platform_nct6775_656",sensor="temp16"} 3.892313987e+06
[..]

To ignore such values, node_exporter only allowed the exclusion of complete chips / devices using --collector.hwmon.chip-exclude. However, in newer versions of node_exporter you’ll be able to exclude (or explicitly include) single sensors on a sensor-level using the following command line option:

--collector.hwmon.sensor-exclude="platform_nct6775_656;temp1[5,6]"

The argument is a regex that is matched against the device name and the sensor. Separate the chip name and the sensor name using “;“.

As my little home server I have an Asrock DeskMini X300 with an AMD Ryzen 7 5700G (16 cores) and 64GB of memory. A nice low powered home server to play around with. Out of the box, the DeskMini comes with one 1 Gbit network interface (a Realtek chipset). Since most of my devices are connected via WiFi anyway, this was more than enough until now. But then, modernity arrived in my part of the world and we now have 10Gbit fiber internet, great!

10Gbit internet sounds awesome, however devices connected via WiFi will only ever see a real-world maximum of around 700 Mbits/sec via WiFi 6. But maybe my little DeskMini could use all that 10Gbit? Unfortunately, the DeskMini motherboard does not have any of the usual PCIe expansion slots apart from SATA and M.2 slots. So I decided to try the “IOCREST M.2 to Single 10G Ethernet Network Adapter (IO-M2F107-GLAN)” adapter (AliExpress link here), to see if that would work.

NVIDIA provides the Linux4Tegra (L4T) distribution as an image for use with the NVIDIA Jetson Nano. However, once you upgrade the whole system, strange problems will pop up, one of which I have described here: NVIDIA Docker “permission denied: unknown.” on Jetson Nano.

When applying a popular solution described here by adding a new repository to your L4T installation, this will result in interesting error messages such as the following when trying to run L4T-ML containers:

docker run  --rm --runtime nvidia -it nvcr.io/nvidia/l4t-ml:r32.7.1-py3 python3 -c "import torch"

[..]
libcurand.so.10: cannot open shared object file: No such file or directory

I recently bought an NVIDIA Jetson Nano Developer Kit to fiddle around with things like MicroShift or TensorFlow. The board is typically used with L4T (Linux for Tegra) based on Ubuntu 18.04. Fedora can also be installed, although not all drivers (for example for the GPU) are available yet. So after properly updating the system with the latest packages, when starting a container using the nvidia runtime, I got the following error:

docker run -it --rm --runtime nvidia --network host nvcr.io/nvidia/l4t-ml:r32.6.1-py3
[..]
docker: Error response from daemon: failed to create shim: OCI runtime create failed: container_linux.go:380: starting container process caused: error adding seccomp filter rule for syscall clone3: permission denied: unknown.

When working with JSON data, I typically use jq to mangle the data. I keep this post as a reference for myself on how to remove an element from a JSON list or array using jq.

Given we have the following array:

$ echo '{"hello": "world", "myarray": ["a", "b", "c"]}' | jq
{
  "hello": "world",
  "myarray": [
    "a",
    "b",
    "c"
  ]
}

To remove an element from the array, use the del function with the select function to select a single element:

jq 'del(.myarray[] | select(. == "b"))'

So when applying this to the above array, we can remove “b” from the array like so:

$ echo '{"hello": "world", "myarray": ["a", "b", "c"]}' | jq 'del(.myarray[] | select(. == "b"))'
{
  "hello": "world",
  "myarray": [
    "a",
    "c"
  ]
}

As you may know, Docker Desktop on macOS runs a Linux VM in the background to run containers on macOS (since containers are a Linux concept). However, that VM is well hidden from view and you typically only interact with it when you start Docker Desktop or when you need to clean up images in the VM itself.

Sometimes you’ll want to have a shell into that VM, but that turns out to be more complicated than I initially expected. There is however an easily accessible debug shell available.

• First, open a terminal and use socat to open the debug shell socket to the VM using the following command:

$ socat -d -d ~/Library/Containers/com.docker.docker/Data/debug-shell.sock pty,rawer

• socat will print the line “PTY is /dev/ttys010“, to which you can then connect to using screen on another terminal window:

$ screen /dev/ttys0xx

So that will look something like this:

$ socat -d -d ~/Library/Containers/com.docker.docker/Data/debug-shell.sock pty,rawer
2021/01/02 21:28:43 socat[23508] N opening connection to LEN=73 AF=1 "/Users/simon/Library/Containers/com.docker.docker/Data/debug-shell.sock"
2021/01/02 21:28:43 socat[23508] N successfully connected from local address LEN=16 AF=1 ""
2021/01/02 21:28:43 socat[23508] N successfully connected via
2021/01/02 21:28:43 socat[23508] N PTY is /dev/ttys010
2021/01/02 21:28:43 socat[23508] N starting data transfer loop with FDs [5,5] and [6,6]

$ screen /dev/ttys010
/ #
/ # uname -a
Linux docker-desktop 4.19.121-linuxkit #1 SMP Tue Dec 1 17:50:32 UTC 2020 x86_64 Linux

The VM is a very stripped down Alpine image with no package manager available, so you’ll have to make do with what is available.

Quit with CTRL-D, which will also close the socat socket. Thanks to Tatsushi for figuring it out in this GitHub Gist.

Getting training and exams done in 2020 has been challenging. After reaching my RHCE mid-February, I am now proud to say that I achieved my Red Hat Certified Architect in Infrastructure certification less than 9 months later.

To reach my RHCA, I took the following Red Hat exams. As you can see, it is OpenShift and Ansible all the way down:

• EX180 Red Hat Certified Specialist in Containers and Kubernetes
• EX280 Red Hat Certified Specialist in OpenShift Administration
• EX288 Red Hat Certified Specialist in OpenShift Application Development
• EX407 Red Hat Certified Specialist in Ansible Automation
• EX447 Red Hat Certified Specialist in Ansible Best Practices

Of course, the journey does not end here as there are quite a few interesting topics still to learn!

For my own container images, I often like to use the Fedora Container Images as the base image. This means I often use the “fedora:32” or “fedora-minimal:32” image when building my own images.

Yesterday, while playing around with an image based on the “fedora-minimal” image that then uses nginx and php-fpm, I came across this curious error:

Invalid date.timezone value 'UTC', we selected the timezone 'UTC' for now

Due to COVID-19, like many others I am currently working from home and as a result I took the chance to update my home office. Working with a small laptop screen for months is not optimal, so I went the ultra-wide route and got myself a Dell U3818DW monitor.

Since I did not find a lot of information about running this monitor with Linux, here is a quick overview. To summarize, everything works out-of-the-box.

Working for Red Hat certainly has its perks. One of them being that I have access to all the content from Red Hat University and I am able to take Red Hat exams for free. With these perks come of course some expectations. Customers expect a Red Hat TAM to be knowledgeable on a wide range of Red Hat products, even if they are not directly related to the function of the TAM.

The most common certifications for System Administrators and also for new TAMs are the Red Hat Certified System Administrator (RHCSA) and the Red Hat Certified Engineer (RHCE). So after passing my RHCSA exam in December 2019, I passed the exam EX294V8 to become a Red Hat Certified Engineer (RHCE) in mid-February. The next step is obviously to become a Red Hat Certified Architect (RHCA), in my case focussed on Cloud technologies such as OpenShift and Containerisation.

To prepare for the RHCE, I used Red Hat University Online courses (RH294) and also prepared using Tomas Nevars Ansible Sample Exam. As others have already noted, the RHCE for RHEL8 is a pure Ansible exam, so knowing your Ansible playbooks in and out will help you with the exam. The above courses and sample exam are great preparations for the exam itself.