Launch Jupyter to the Cloud: an example of using Docker and Terraform
Cheuk Ting Ho (~Cheukting) |
There are lots of reasons using a cloud service is favorable, but how to make sure consistency between development and deployment? With Docker and Terraform, we can create the same environment on cloud easily. For example, we will deploy a Jupyter notebook on Google Cloud Platform using both tools.
In this talk, we will use a task: hiring a GPU on Google Cloud Platform to train neural network, as an example to show how an application can be deployed on a cloud platform with Docker and Terraform. The goal is to have Jupyter Notebook running in an environment with Tensorflow (GPU version) and other libraries installed on a Google Compute Engine.
First we will briefly explain what is Docker and what is Terraform for audiences who has no experience in either or both of them. Some basic concepts of both tools will also be covered. After that, we will walk-through each steps of the work flow, which includes designing and building a Docker image, setting up a pipeline on Github and Docker Hub, writing the Terrafrom code and the start up script, launching an instance. From that, audiences will have an idea of how both tools can be use together to deploy an app onto a cloud platform and what advantages each tool can bring in the process.
This talk is for people with no experience in application deployment on cloud service but would benefit form computational reproducibility and cloud service, potentially data scientists/ analysts or tech practitioners who didn’t have a software developing background. We will use an example that is simple but useful in data science to demonstrate basic usage of Docker and Terraform which would be beneficial to beginners who would like to simplify their work flow with those tools.
None, it's a beginner friendly talk.
Project source code on Github: https://github.com/Cheukting/GCP-GPU-Jupyter
After spending 5 years doing research in theoretical physics at Hong Kong University of Science and Technology, Cheuk has transferred her analytical and logical skills in natural science and built a career in data science. Cheuk is now a Data Scientist in Hotelbeds Groups which is one of the biggest worldwide wholesaler in travel business.
Cheuk constantly contributes to the community by giving AI and deep learning workshops, volunteering at Datakind for charities. At the same time participate open source projects like Pandas, Gensim and Dateutil. Cheuk has also been a guest speaker at University of Oxford and Queen Mary University of London, and various conferences including PyData Amsterdam, PyCon Israel and PyLondinium. Believing in gender equality, Cheuk is currently a co-organizer of AI club for Gender Minorities to support Tech Diversity and Inclusion.
Public speaker in technology, example of my talk on YouTube: https://www.youtube.com/watch?v=bQ2Qu63SYHw
Slide Share: https://www.slideshare.net/CheukTingHo/presentations
Speaker Bio: https://www.papercall.io/speakers/26654/