How to Use Jupyter Notebook on AWS

4 min readJan 21, 2019

Motivation:

Jupyter Notebook is a popular choice to run machine learning algorithms and deep learning models. It’s convenient to use it on the local machine after installing Anaconda (see Getting Started With Jupyter Notebook for Python). But the requirement for more computing resources on Amazon EMR as part of my project in the distributed system class asks me to securely access Jupyter Notebooks on the cloud. Another advantage to do so is that with such a public jupyter notebook, all the group members can co-work on the same notebook together.

General Steps:

Launch an AWS instance from EC2 console.

Create an IAM user or use the existing user.
Create an instance
Access the instance with ssh

2. Set up configurations to use Jupyter Notebook

Install Anaconda 3
Configure Jupyter server in order to use it through EC2 and connect with SSH from your local computer via your browser.

3. Access Jupyter Notebook from local through the browser

Detailed Step by Step:

Launch an AWS instance from EC2 console

Create an IAM user or use the existing user.

AWS Identity and Access Management (IAM) enables you to securely control access to AWS services and resources for your users.

The user should have the group of EC2FullAccess

2. Go to the Amazon EC2 page and change the location to some cheaper regions like Oregon. Launch an “Amazon Linux 2 AMI (HVM), SSD Volume Typ” instance. For now, just choose t2.micro (free) to have a try. Leave the first five steps default and create a new security group or an existing group at the sixth step. Make sure the security group includes the following rules.

A security group is a set of firewall rules that control the traffic for your instance. On this page, you can add rules to allow specific traffic to reach your instance.

3. Then you should see this security key option, choose an existing key pair or create a new pair.

The PEM file is a key that AWS will check when you try to access (or SSH) into your EC2 instance from your local computer’s terminal.

4. Log to your instance using ssh with public IP.

ssh -i ~/temp/xxx.pem ec2-user@54.218.135.102

Set up configurations to use Jupyter Notebook

Install Anaconda3 with:

wget https://repo.continuum.io/archive/Anaconda3-4.4.0-Linux-x86_64.shbash Anaconda3-4.4.0-Linux-x86_64.sh

Try conda in the terminal to see whether the path has been automatically added to PATH. If you get “-bash: conda: command not found”, please find about how to export Anaconda to your instance’s path in .bashrc. So that you can use the commands of Anaconda conveniently.

2. Configure Jupyter server in order to use it through EC2 and connect with SSH from your local computer via your browser.

Create a default config file:

jupyter notebook --generate-config

Create SSL certificates for https so that our browser can trust our jupyter server:

- mkdir certs
- cd certs
- sudo openssl req -x509 -nodes -days 365 -newkey rsa:1024 -keyout mycert.pem -out mycert.pem

Configure Jupyter

- cd ~/.jupyter/
- vi jupyter_notebook_config.py

Insert this at the beginning of the document:

c = get_config()
# Kernel config
c.IPKernelApp.pylab = ‘inline’ # if you want plotting support always in your notebook
# Notebook config
c.NotebookApp.certfile = u’/home/ec2-user/certs/mycert.pem’ #location of your certificate file
c.NotebookApp.ip = ‘*’
c.NotebookApp.open_browser = False #so that the ipython notebook does not opens up a browser by default
# Set the port to 8888, the port we set up in the AWS EC2 set-up
c.NotebookApp.port = 8888