Let's Deploy your Bioinformatics Jupyterhub Cluster on AWS
Bioinformatics analyses requires varied computational resources, and sometimes you need real time data visualization. You need to be able to create plots, filter data tables, along with your own in house tools and dashboards.
The Problem
Maybe you have been working on a single server and that you've outgrown, or maybe you are manually bringing EC2 server instances up and down based on demand, or you want to future proof your business or startup.
The SolutionWe will work together in order to create a Jupyterhub luster with your needs in mind.
- Create a managed Jupyterhub Cluster with your needs in mind. I can integrate with existing infrastructure, or create a new cluster with Kubernetes.
- Do your users prefer R and RStudio Server? No problem! Use Jupyterhub as a central authentication server to spawn other services.
- Configure mounted EFS storage available to not only your cluster, but to any AWS resource. This includes HPC clusters, ML workflows, EC2 instances, etc.
- Configure users and groups to restrict access to certain files, just as you would on any file system.
- Give your users access to any number of software environments, and let them create their own.
- Create SOPs and documentation portals.
Once you have the base Jupyterhub Infrastructure up and running you can begin to scale with multiple web services.
- Create dashboards with Dash or RShiny to give custom views of your datasets and analyses.
- Power Computer Vision infrastructure for Machine Learning Workflows.
Your Jupyterhub cluster can integrate with a number of different services. If you already have compute infrastructure in the way of an HPC cluster, you can instruct your servers to run there with Spawners.
