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Home Page: https://docs.k3ai.in/
License: Apache License 2.0
k3ai microwebsite repository
Home Page: https://docs.k3ai.in/
License: Apache License 2.0
I was under the impression most things would take 3 lines or less, but so far this is what I've tried without success. Please help! :-) I love what you've done so far and if I can POC it would like to see how I can leverage it for making the ops easier for data scientists.
#!/bin/bash
# k3ai installer
echo "Installing kubectl, k9s, docker, k3s, and k3ai."
# install docker
sudo apt update
sudo apt install apt-transport-https ca-certificates curl software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu focal stable"
sudo apt update
apt-cache policy docker-ce
sudo apt install docker-ce
sudo systemctl status docker
sudo usermod -aG docker $USER
exec $SHELL
sudo mkdir -p /etc/systemd/system/docker.service.d/
cat << EOF | sudo tee /etc/systemd/system/docker.service.d/proxy.conf
[Service]
Environment="HTTP_PROXY=${HTTPS_PROXY}"
Environment="HTTPS_PROXY=${https_proxy}"
Environment="NO_PROXY=localhost,127.0.0.1,::1,.internal.domain.com"
EOF
# install kubectl
cd /tmp
curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
sudo install -o root -g root -m 0755 kubectl /usr/local/bin/kubectl
# install k9s
curl -LO "https://github.com/derailed/k9s/releases/download/v0.24.9/k9s_Linux_x86_64.tar.gz"
tar -xvf k9s*.tar.gz
sudo install -o root -g root -m 0755 k9s /usr/local/bin/k9s
# install k3s
#curl -sfL https://get.k3s.io | sh -
#k3s kubectl get node
# install k3ai
curl -fL "https://get.k3ai.in" -o k3ai.tar.gz
tar -xvzf k3ai.tar.gz
sudo install -o root -g root -m 0755 k3ai /usr/local/bin/k3ai
echo "DONE. You can now proceed with the init steps here:"
echo " https://docs.k3ai.in/examples/hello-home"
echo "If the above installation or next init steps fail, ensure you have set both"
echo " http_proxy and https_proxy variables, then rerun this script and"
echo " they will be configured for docker."
echo "Also make sure you have performed `docker login` for dockerhub."
Then
k3ai init --local k3s
or
k3ai init --confing ~/.k3ai/config.yaml
with all the other parts except k3s commented out.
I also tried installing k3s as noted above (commented out).
I'm still getting the follow errors in output:
me@k3ai:~$ k3ai init --config .k3ai/config.yaml
☑️ Checking requirements for local deployment...
☑️ Installing infrastructure for local deployment...
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0Warning: Failed to create the file /home/nick_reith/k3s: Is a directory
3 24986 3 791 0 0 1557 0 0:00:16 --:--:-- 0:00:16 1557
curl: (23) Failed writing body (0 != 791)
chmod: cannot access './home/me/k3s': No such file or directory
mv: cannot stat './home/me/k3s': No such file or directory
[1] 17364
☑️ Infrastructure ready, proceeding to plugins installation (if any)...
☑️ Add Plugins to local deployment...
fork/exec bin/sh: no such file or directory
fork/exec bin/sh: no such file or directory
☑️ Plugins added to local deployment...
🎉 Local deployment completed, have fun with k3ai!
To use K3ai copy the following line: 🦾
➡️ export KUBECONFIG=/etc/rancher/k3s/k3s.yaml
Thank you again for using K3ai, don't forget to check our docs at 🗺️ https://docs.k3ai.in
nick_reith@k3ai:~$ k3ai apply jupyter-minimal
Plugin YAML content: [{https://raw.githubusercontent.com/kf5i/k3ai-plugins/main/common/jupyter/base/deployment.yaml file}], name: jupyter-minimal
Unable to connect to the server: Service Unavailable
Unable to connect to the server: Service Unavailable
Unable to connect to the server: Service Unavailable
2021/05/12 02:33:13 Error during create: exit status 1
A roadmap section that links to a Github project where contributors may insert their own ideas and features request.
I'm pretty sure that:
In another tab of your browser open the Kubeflow UI (http://:8888
should be
In another tab of your browser open the Kubeflow UI (http://:8080)
k3ai apply -f kubeflow-pipelines-traefik
should be
k3ai apply -g kubeflow-pipelines-traefik
I'm still starting out with K3AI but I think the logic of the init subcommand could use some improvement.
It seems like if you run k3ai init
when there is no config.yaml file, it creates the file and nothing else.
If you run the command after there is a config.yaml file, it applies the configuration described in the file.
If that's correct, it seems a little unusual to me. Have you thought of maybe rolling the cluster creation into the apply
subcommand?
Perhaps in that way you could use the invocation of init
to create the file if it doesn't exist, plus it could summarize what the resulting cluster config would be in all cases. That would lend itself to more consistent behaviour of init
.
Again, I'm still in the beginning stages of working with K3AI so some of this might only be valuable as a view into one person's rookie-mistakes.
It seems like there are four different paths a user could take when it comes to the underlying K8s cluster:
It seems that this could be described with the k3ai init
options of:
We need to document the new WSL flag and how a user may use k3ai withing WSL.
Need a video also.
As per :
https://github.com/kf5i/k3ai/issues/18
kf5i/k3ai#20
We need to add Contributing guidelines to the K3ai repos:
A page on why we developed k3ai and what problem we try to solve so folks from the AI community may decide to contribute to the project
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