Category: Linux

minikube (Kubernetes Development)

If you want to develop something for kubernetes, you may need to run minikube. This can be done on our linux installations, the following commands should start a working “kubernetes cluster” on your installation:

mkdir ~/bin/

wget https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64 -O ~/bin/minikube
chmod 755 ~/bin/minikube

cd ~/bin/
./minikube config set rootless true
./minikube config set driver podman
./minikube config set container-runtime containerd

./minikube start --cni calico

After minikube has started you can check all running pods with the following:

minikube kubectl -- get pods -A

You can also install kubectl and helm in your ~/bin if you like:

cd ~/bin/

curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"

export HELM_INSTALL_DIR=~/bin; export USE_SUDO=false; curl https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3 | bash

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Linux (Evolution) local mail archive

This describes how to create a local folder in which you can move emails, which will still be available in the evolution mail client. So the mails will be removed from the mailserver and saved into a folder, which you have to backup.

Requirements:

  • You already use evolution as your mail client
  • You make backups of your local files and folders

First create a folder in the filesystem, which will hold your mails:

Now open evolution and start adding a new mail account:

This account will be your local archive, so you can give it a meaningfull name, ex. “Local Archive”. As for the email address you can type in a non existing one, i suggest “archive@local”, this names will help to identify it in evolution later:

After hitting “Next” choose “Standard Unix mbox spool directory” as Server type:

For the “Spool Directory” choose the folder you have created above:

On the next page activate the following:

Choose “None” as the “Server Type”:

“Next” it will ask you for the name which will appear in evolution:

Now you have the new account:

You need to create a folder now to put your mails into:

For example you can create a new one each year:

Now you can move mails from your account into this folder, they will be saved on your filesystem, so don’t forget to regulary make a backup.

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Howto use docker at D-MATH

To use docker at D-MATH is to use podman -> https://podman.io/

With podman you can use all docker commands just write podman instead of docker in the command, all the parameter stay the same.

With podman we are able to provide a possibility that a user without administrative rights can download and run docker images.

Example 1

The following example will run the latest docker image of alpine linux (https://hub.docker.com/_/alpine).

podman run -ti -v $(pwd):/home/test alpine:latest

The parameter

  • -v $(pwd):/home/test

is very helpful, this will add the current folder you are in now, to the container at /home/test. If you have seLinux activated you need to add a Z:

  • -v $(pwd):/home/test:Z

Example 2

The following example shows howto run a more complicated docker image named fenics and transfer files.

First open a terminal and go into the folder which you want to have accessable in the docker image.

mkdir -p ~/Documents/mydata
cd ~/Documents/mydata

Now run the container with the following parameters:

podman run -ti -p 127.0.0.1:8000:8000 -v $(pwd):/home/fenics/shared -w /home/fenics/shared quay.io/fenicsproject/stable:current

This will connect you to the container.

But the docker image of the fenicsproject will log you in a user fenics, this user will not have access to the data in ~/Documents/mydata.

With podman the user root in the container will have access to your files.

So you need to become root inside the container to have access:

sudo su -

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Linux Environment Modules at the D-MATH

With Environment Modules or simply called Modules it is possible to dynamically expand the active user environment and to remove it again without closing the shell.

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Tensorflow

On our Linux devices we are providing a Python Tensorflow Module ready to use that is accessible trough a Linux Environment Module. With the command “module” you have the possibility to add Tensorflow in many different versions. By default the newest is chosen. Read more

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