This project will allow users to save their custom data analysis scripts in the Docker. So the main technologies will be used is Docker.
- Why did you and your team choose the technologies you did?
Not all users are comfortable to code in Jupiter Notebook or having the programming skills required to work with it. Docker serve such purpose that package the applications and their dependencies into a portable containerm so that the application can be run the same way across different environments.
- How will your project use them?
We plan to convert Jupiter Notebook codes inputted by users to Python scripts, and then pack Python scripts and its dependencis into Docker container image.
- What are their pros and cons?
Docker containers provide a consistent environment for applications to run in different environments, although they do have a learning curve and can be complex to configure.
- What were the alternatives?
Kubernetes may be an alternative tool to managing containerized applications, but Kubernetes containers are larger and consume more resources when deployed.
- What do you like or dislike about your system UI/UX?
We will be following the same UI style for the software. which is simple and clean. However, we will highlight important elements using color.
- What do you like or dislike about your server/backend system/API?
A button to trigger the Docker image will be added to UI. Backend includes a function to validate the .ipynb file. I think it will be proper meet the requimrent of this project.
- What do you like or dislike about your design modularity? Does it enable each of your to work independently?
The current modular design includes all necessary tasks that follow the flowchart as the users. Each of the team members has picked some individual tasks, so we can work independently and test integration at the end,
- Anything else
The marketing team from the sponsor company will be sending us the Docker image.