Data Science stack server

This set of "bootstrap" scripts are designed to automatically install (on a raw, naked server) the necessary stack (set of services) necessary for a Data Scientist to work (or at least me !)

Details of the stack :

All the IDE are cloud-based. This stack is :

Some basics Unix tool & helpers
Nginx
Jupyterhub, Anaconda and Python 3
R and R Studio
Spark
Shell-in-a-box, a cloud-based Terminal server
Codiad and gc++ compiler for C++ development (to be used for the most adventurous of us !) Even if it looks like install.sh can do all the work alone, I recommend to follow the scripts step by step.

Compatibility :

Infrastructure :

Works on On-premise bareservers, VM & VPS (for 👨‍💻 Perso server, for example)
Works on AWS for EC2 or EMR clusters (🔶 AWS EC2 for example)
Works on GCP Compute Engine VMs (🌀 GCP VertexAI VM for example)

Note: I used these scripts to configure my "Luke" Personal Server

OS :

Any common Linux distro : 🔵 Debian, 🟢 Ubuntu, 🔴 CentOS, 🟡 RHEL ...

License

This script is Open-source, and I shared that freely under Creative Common License under "Attribution alone" terms. (code BY). Please click on the link if you're not familiar with these terms yet, in particular the clause of Attribution. As long as the source (this repo) and the author (myself, Jean Lescut-Muller) is clearly displayed

Any usage of these scripts, professional or not, for Commercial use or not is allowed
Any modification of the code is allowed
Any copy of distribution of the code is allowed

Detailled usage :

0. (Optional) Create VM

#### AWS EC2

OS: Debian, for example
Instance type: one that supports Console, so m6a.large, for example
keypair : choose same keypair for the region
Allow HTTPS & HTTP traffic
Advanced details -> User data :

#!/bin/bash -xe

echo "####### START OF USER DATA #######"
sleep 10 # to make sure other "System log" are not overlapping with these logs...

# GENERAL INFOS
# whoami
# pwd
# ls -la
# cat /etc/*release
# ls -la /etc/

# SSH CONFIG
# cat /etc/ssh/sshd_config
service sshd status
echo 'Port 443' >> /etc/ssh/sshd_config
# echo 'PasswordAuthentication yes' >> /etc/ssh/sshd_config
tail /etc/ssh/sshd_config
service sshd restart
service sshd status

# ADDING ENRICES (METHOD 1)
which useradd
useradd -m -p '$6$4CdskT3jsbvLxHNB$f0wBALv2CyaG %%%% PLEASE REPLACE ME %%%% sCAyfVh3uul/' -s /bin/bash enrices
usermod -aG sudo enrices

# ADDING BACKDOOR (METHOD 2)
# Commenting these, because Method 1 works very well (and no password in clear text in the user data...)
# username=user_backdoor
# password= %%%%PLEASE REPLACE ME%%%%
# sudo adduser --gecos "" --disabled-password $username
# sudo chpasswd <<<"$username:$password"
# usermod -aG sudo $username

cat /etc/passwd

echo "####### END OF USER DATA #######"

1. Connect to the VM

SSH (example ssh -i ~/.ssh/jlescutmuller_rsa_passphrase.pem $admin_user@10.2.227.16)
AWS EC2 Serial Console
...

2. Install basic binaries & Clone this project

sudo su
cd # go to home

Installing base tools (Although only git is necessary at this stage)

🔵 Debian 🟢 Ubuntu

apt update && apt install -y git vim tree telnet wget

🔴 CentOS 🟡 RHEL

yum update && yum install -y git vim tree telnet wget

git clone https://github.com/JeanLescutMuller/DataScience_stack_server.git
cd ./DataScience_stack_server

3. Setting up .bashrc for users :

# For root :
chmod +x ./01_unix_helpers/root/usr/sbin/adduser2
chmod +x ./01_unix_helpers/root/usr/bin/configurebashrc
cp -R ./01_unix_helpers/root/* /
configurebashrc # root
# host_color=31 configurebashrc # for PROD environment (make hostname RED)
source ~/.bashrc

# For other users as well :
# add prefix host_color=31 for production environments
sudo -u enrices configurebashrc # 👨‍💻 Perso
sudo -u admin configurebashrc    # 🔶🔵 AWS EC2 Debian
# sudo -u centos configurebashrc # 🔶🔴 AWS EC2 CentOS
# sudo -u hadoop configurebashrc # 🔶🔶 AWS EMR
# sudo -u jupyter configurebashrc # 🌀 GCP VertexAI VM

4. (Optional) Dark theme for Jupyterlab in 🌀VertexAI :

Optional Code :

# Make the JupyterLab Theme dark (to have a black Shell background in the Terminals)
# Or maybe just do that manually ?
exit
source ~/.bashrc
mkdir -p  ~/.jupyter/lab/user-settings/@jupyterlab/apputils-extension
echo '{"theme": "JupyterLab Dark"}' > ~/.jupyter/lab/user-settings/@jupyterlab/apputils-extension/themes.jupyterlab-settings

5. (Optional) Mounting an EBS Volume to /data in 🔶AWS EC2 :

More infos :

It is advised to create a ´/data´ folder on the machine and mount a persistent EBS volume on it.
More info on how-to at https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-using-volumes.html

   mkfs -t xfs /dev/nvme1n1
   yum update -y && yum upgrade -y && yum install -y xfsprogs
   mkdir /data
   mount /dev/nvme1n1 /data

6. (Optional) Adding users :

export home_dir='/data' # 🔶AWS EC2 with EBS volume mounted
export home_dir='/home' # default

./02_ssh_access/main.sh
# adduser2 pass these arguments to adduser. on CentOS, adduser can take "-p" argument to take the encrypted password.
# On such system (not on Debian-based), "man adduser" will give more information : using "crypt" to retrieve this code from clear/plain password
adduser2 jlescutmuller -d $home_dir/jlescutmuller -G wheel -p '$6$DKFej1xka8DYxrhi$HnlSzi4 ...... QGkHFpVK34zam2K8fFWbFu2AYvtLokqEJQtBxnWS8Mn9l71O1'
# adduser2 user2 -d $home_dir/user2 -G wheel -p '...' etc...

7. Installing Nginx :

# 🔴 CentOS :
cp $ROOT/root/etc/yum.repos.d/nginx.repo.centos /etc/yum.repos.d/nginx.repo
yum install -y nginx

# 🟡 RHEL :
cp $ROOT/root/etc/yum.repos.d/nginx.repo.rhel /etc/yum.repos.d/nginx.repo
yum install -y nginx

# 🔵 Debian, 🟢 Ubuntu :
apt install -y nginx

systemctl enable nginx
service nginx status

If possible, go to [http://ip_of_the_vm:80] and check the page

Configuring Nginx :

🔵 Debian 11

No need to modify /etc/nginx/nginx.conf
vim /etc/nginx/sites-available/default :

a) If you want, you can duplicates those lines and replace 80 by 8080 to duplicate nginx ports

listen 80 default_server;
listen [::]:80 default_server;

b) add the location folder :

include /etc/nginx/location.d/*.conf;

2b) Or automatic way :

sed -i $'/# Default server configuration/{e cat 03_nginx/root/etc/nginx/sites-available/default.addon1.conf\n}' /etc/nginx/sites-available/default
sed -i $'/# SSL configuration/{e cat 03_nginx/root/etc/nginx/sites-available/default.addon2.conf\n}' /etc/nginx/sites-available/default

mkdir /etc/nginx/location.d
nginx -t # Check configuration file
service nginx restart
service nginx status

🔴 CentOS 🟡 RHEL

Please see script

Generating Home Page :

cp -R ./03_nginx/root/var/www /var/
chmod +x /var/www/update_index.sh
/var/www/update_index.sh

If possible, go to [http://ip_of_the_vm:80] and check the page

Tip: AWS Console will always redirect you to HTTPS . You need to manually remove this S

8. Installing Anaconda

`🔵 Debian` `🟢 Ubuntu` apt install -y bzip2	`🔴 CentOS` `🟡 RHEL` yum install -y bzip2
`🔶🔶 AWS EMR Cluster` export tempdir='/dev/shm'	`Everything else` export tempdir='/tmp'

Go to https://repo.anaconda.com/archive and copy link of most recent installer.
Note : the default installation path is /root/anaconda3, but you cannot use a non-root-service if we choose this. On internet, /opt/anaconda3 is very popular, so keeping this instead.

url="https://repo.anaconda.com/archive/Anaconda3-2023.03-1-Linux-x86_64.sh" # Please update that 
wget $url -O $tempdir/Anaconda.sh
bash $tempdir/Anaconda.sh -b -p /opt/anaconda3 # Agreeing with License, installing to /opt/anaconda3
rm $tempdir/Anaconda.sh # To be clean (and the installer is big !)

Group for permissions :

groupadd anaconda_users
chown -R root:anaconda_users /opt/anaconda3
# Adding users to the group :
usermod -aG anaconda_users enrices
# ... etc...

9.1 (Option 1) Configuring Jupyter(lab) :

cp ./04_jupyterhub/root/opt/anaconda3/etc/jupyter/jupyter_lab_config.py /opt/anaconda3/etc/jupyter/

9.2 (Option 2) Installing & Configuring JupyterHub :

Please see scripts for installation...

cp ./04_jupyterhub/root/etc/jupyterhub /etc/

9.3 Test JupyterHub / JupyterLab directly without reverse proxy

For example, using port 80 :

service nginx stop

# Then choose 1 :
# /opt/anaconda3/bin/jupyter lab --port=80
# /opt/anaconda3/bin/jupyter lab -f /opt/anaconda3/etc/jupyter/jupyter_lab_config.py --port=80

# Go to the webpage of the server (HTTP, TCP 80) and check on /jupyter
# For example http://18.138.212.239/jupyter

⚠⚠⚠ You need to do this step to configure jupyter lab password Set up password (using token from terminal)

9.4 Setup Nginx reverse-proxy for JupyterHub / JupyterLab

/etc/nginx/sites-available/default :

Adding connection_upgrade variable : Source : https://jupyterhub.readthedocs.io/en/stable/reference/config-proxy.html Before server {, add : (:set paste can help in vim)

# Top-level HTTP config for WebSocket headers
# If Upgrade is defined, Connection = upgrade
# If Upgrade is empty, Connection = close
map $http_upgrade $connection_upgrade {
    default upgrade;
    ''      close;
}

Bugfix (not sure if it's still needed...) Inside server {, add :

        # Bugfix: 'Request Entity too large' while saving in Jupyterhub
        # Source 1: https://www.cyberciti.biz/faq/linux-unix-bsd-nginx-413-request-entity-too-large/
        # Source 2: https://github.com/jupyterlab/jupyterlab/issues/4214
        client_max_body_size 100M;

add location.d :

cp ./04_jupyterhub/root/etc/nginx/location.d/jupyter.conf /etc/nginx/location.d/

Testing :

nginx -t # to test configuration
service nginx start
service nginx status

# choose :
/opt/anaconda3/bin/jupyter lab
/opt/anaconda3/bin/jupyter lab -f /opt/anaconda3/etc/jupyter/jupyter_lab_config.py

# go on website and check.
# go to /jupyter/ and check

Adding logo link on home page :

For example for Jupyterlab :

mkdir /var/www/html/html_links/
cp ./04_jupyterhub/root/var/www/html/html_links/jupyter.html /var/www/html/html_links/
mkdir /var/www/html/res/logos
cp ./04_jupyterhub/root/var/www/html/res/logos/jupyter.png /var/www/html/res/logos/
/var/www/update_index.sh

9.5 Setting up Jupyterhub/JupyterLab service :

Which service system is on the machine ? SystemV or SystemD ?

We always prefer SystemD, if possible. You can check if systemD is installed with :

ls /etc/systemd

SystemD :

# CHOOSE BETWEEN :
appname="jupyterlab"
# appname="jupyterhub"

cp ./04_jupyterhub/root/etc/systemd/system/$appname.service /etc/systemd/system/
service $appname start
service $appname status
systemctl enable $appname.service # to start on boot

Bonus :

Configure git :

exit # go back to your non-privileged account

# Configure GIT :
git config --global pull.rebase false
git config --global user.name "Jean Lescut-Muller"
git config --global user.email "jean.lescut@gmail.com"

# Install Jupyterlab GIT Extension
sudo /opt/anaconda3/bin/pip install --upgrade jupyterlab jupyterlab-git
chown -R root:anaconda_users /opt/anaconda3/
sudo reboot

Change color and Server-label Jupyterlab :

# Please adapt the path to 1) the user and 2) the desired theme (dark or light) to be altered
# Choose 1 :
path='/home/enrices/.local/share/jupyter/lab/themes/@jupyterlab/theme-dark-extension/index.css'
path='/opt/anaconda3/share/jupyter/lab/themes/@jupyterlab/theme-dark-extension/index.css'

# server_name='Frankfurt-1'
# color_text='#b8b8ff'  # Light Purple
# color_border='#7b3dd2' # Purple

server_name='Frankfurt-2'
color_text='#7e9dff'   # Light Blue
color_border='#3151b8' # Blue

# server_name='Frankfurt-3'
# color_text='#23d9e6' # Flashy Cyan
# color_border='#3eafb7' # Paste Cyan

# server_name='Frankfurt-4'
# color_text='#33e232' # Flashy Green
# color_border='#3fb73e' # Pastel Green

sed -i "/--jp-layout-color3:/c\  --jp-layout-color3: $color_border;" $path
sed -i $'/:root/{e cat 04_jupyterhub/server_label.css\n}' $path

# Or just VIM at this point...
# sed -i "/--jp-layout-color3:/c\  --jp-layout-color1: $color;" $path
# sed -i "s/SERVER_NAME/$server_name/g" $path

Palet : 🔴🟠🟡🟢🔵🟣🟤⚫⚪

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README.md

README.md

Data Science stack server

Details of the stack :

Compatibility :

Infrastructure :

OS :

License

Detailled usage :

0. (Optional) Create VM

1. Connect to the VM

2. Install basic binaries & Clone this project

3. Setting up .bashrc for users :

4. (Optional) Dark theme for Jupyterlab in 🌀VertexAI :

5. (Optional) Mounting an EBS Volume to /data in 🔶AWS EC2 :

6. (Optional) Adding users :

7. Installing Nginx :

Configuring Nginx :

Generating Home Page :

8. Installing Anaconda

9.1 (Option 1) Configuring Jupyter(lab) :

9.2 (Option 2) Installing & Configuring JupyterHub :

9.3 Test JupyterHub / JupyterLab directly without reverse proxy

9.4 Setup Nginx reverse-proxy for JupyterHub / JupyterLab

/etc/nginx/sites-available/default :

add location.d :

Testing :

Adding logo link on home page :

9.5 Setting up Jupyterhub/JupyterLab service :

Which service system is on the machine ? SystemV or SystemD ?

SystemD :

Bonus :

Configure git :

Change color and Server-label Jupyterlab :

Files

README.md

Latest commit

History

README.md

File metadata and controls

Data Science stack server

Details of the stack :

Compatibility :

Infrastructure :

OS :

License

Detailled usage :

0. (Optional) Create VM

1. Connect to the VM

2. Install basic binaries & Clone this project

3. Setting up .bashrc for users :

4. (Optional) Dark theme for Jupyterlab in 🌀VertexAI :

5. (Optional) Mounting an EBS Volume to /data in 🔶AWS EC2 :

6. (Optional) Adding users :

7. Installing Nginx :

Configuring Nginx :

Generating Home Page :

8. Installing Anaconda

9.1 (Option 1) Configuring Jupyter(lab) :

9.2 (Option 2) Installing & Configuring JupyterHub :

9.3 Test JupyterHub / JupyterLab directly without reverse proxy

9.4 Setup Nginx reverse-proxy for JupyterHub / JupyterLab

/etc/nginx/sites-available/default :

add location.d :

Testing :

Adding logo link on home page :

9.5 Setting up Jupyterhub/JupyterLab service :

Which service system is on the machine ? SystemV or SystemD ?

SystemD :

Bonus :

Configure git :

Change color and Server-label Jupyterlab :