Jupyter Notebook Server with AWS EC2 and AWS VPC

Build a Cloud Server to run your Jupyter Notebooks

Created byJustin Mitchel

Last updated 4/2019

English

English [Auto],

What you'll learn

Launching a live Jupyter Server on an AWS EC2 instance
Building a custom AWS VPC from Scratch
Setup an Ubuntu server to run a Jupyter Notebook
Securely run Jupyter in the Cloud

Course content

4 sections • 14 lectures • 1h 20m total length

What we're going to build5:20
Launch cloud-based Jupiter notebooks on AWS EC2 within a VPC, create password-secured access, and manage multiple instances with scalable resources and public IP access.
Getting Started1:43
Configure a jupyter notebook server on AWS EC2 and VPC by following a step-by-step guide. Start by creating an AWS account and logging into the AWS Management Console.

A first step2:16
Set up an accessible Jupyter notebook server on AWS EC2 by launching a free-tier t2.micro instance, configuring a custom VPC as your virtual data center.
Your new VPC4:49
Create a VPC from scratch to form a private cloud with a least privileged default and a 10.0.0.0/16 CIDR block for scalable IP addressing.
Create a Public Subnet5:24
Create a public subnet in your VPC to enable internet access for EC2 instance, using a /28 CIDR block for 16 addresses (11 available) in US East 1 (North Virginia).
Our First EC2 Instance4:41
Launch your first EC2 instance in a VPC subnet with auto assign public IP, and learn how least privilege prevents internet access.
An Internet Connect VPC4:02
Create a VPC with a 10.0.0.0/16 CIDR and a public subnet. Attach an internet gateway and update the routing to enable internet access for EC2 instances.

Provision the EC2 Instance9:06
Provision an AWS EC2 t2.micro instance in your Jupiter VPC, configure a bootstrap script, install Python, Jupiter, engine x web server, and secure SSH access with a security group.
SSH into EC2 Instance4:43
Learn to ssh into an AWS EC2 Jupiter server from Mac or Windows using a private key and the correct AMI user; verify installations with the bootstrap script.
Jupyter Configuration7:48
Configure a Jupyter notebook on an AWS EC2 instance. Generate the config, secure with a password, set the allowed origin, and adjust security group rules for remote access.
Nginx Configuration7:34
Configure nginx as a reverse proxy for a Jupyter notebook on an AWS EC2 instance by creating a server block in sites-available and linking it to sites-enabled, then reload nginx.
Setup Supervisor4:47
Configure supervisor to run a jupyter notebook as a background service on an ec2 instance, with auto-start, auto-restart, and log management, and verify its running status.

Elastic IP8:25
Allocate and attach an Elastic IP to an EC2 instance to preserve its address across restarts, create an AMI backup of the Jupyter notebook server, and relaunch with consistent configuration.
Reusability with AMI and Wrap up9:57
Create and reuse an AMI image from a running EC2 instance to launch on-demand Jupiter notebook instances with different configurations, manage elastic IPs, and terminate unused resources.

Requirements

Some Python and/or Command Line experience
Interest in cloud computing

Description

One of the challenges of writing programs is having the ability to pick up where you left off. Jupyter Notebooks do this very well because they allow for interactive running of code, keep results in memory, and empower data scientists and programmers everywhere to build interesting things.

Jupyter is an interactive notebook which allows you to run code right inside the notebook. This is good for many reasons:

Notebooks, like actual books, can be shared easily
While running a notebook, the "state", is remembered: run some code and it' remembers the results of that code
Notebooks easily layout the process of a given program into a story-like progression that anyone can pick up and use.

If you've never worked with Jupyter Notebooks before, I highly recommend that you do.

This course is about bringing Jupyter Notebooks to the AWS Cloud. We'll be preparing a AWS Virtual Private Cloud, Subnets, Internet Gateways, Route Tables, and more so that we can provision AWS EC2 instances securely and effectively.

Once we have an EC2 instance, we can configure nginx, supervisor, and Jupyter so we can run it automatically on a public IP address... check out the first video for more on this.

Who this course is for:

Data Scientists looking to control their Jupyter notebook experience
Data Scientists looking for "pick up where you left off" usage of a jupyter notebook
Pythonistas looking to get into Data Science.

Jupyter Notebook Server with AWS EC2 and AWS VPC

What you'll learn

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Course content

Introduction2 lectures • 7min

AWS VPC5 lectures • 21min

AWS EC2 & Jupyter Configuration5 lectures • 34min

Final Steps2 lectures • 18min

Requirements

Description

Who this course is for: