Completed Platform Initiatives

As an instructor, I want to teach content that requires use of a not very powerful GPU some of the time. It’s integrated into my teaching syllabus, where there is a lot of CPU bound work and some GPU bound work. While I could bounce to a different tool that offers just GPUs (like Google Colab) that has its own set of compliance, pedagogy and UX problems that detract from my teaching and I don’t want my students to go through that.

As a student, I want to do all my course content in one familiar hub where I have access to similar tools and my home directory is the same over time for any particular course, without bouncing between different tools. I also don’t want to have to understand the differences between various GPUs, etc before I do my work, as I’m just doing light GPU work to understand fundamentals.

As a hub admin, I want to support my instructors using GPUs but without blowing through my budget entirely. I also want to give them any GPU access at all, in the face of limited GPU availability on many cloud providers today (in 2026)

As a JupyterHub admin, I want to control how much cloud spend my hub uses. One of the important components is how much resources people can use at a time. While JupyterHub lets me control that by restricting resource allocations to different groups, dask-gateway does not. So a user can intentionally or accidentally spin up a huge dask-gateway cluster and use all the cloud spend I have budgeted for a month in a few hours. As a first step measure to protect from this, I want to control who can access dask-gateway in my hub, so I can grant access only to people who have been vetted.

As an IT department at a large university, I would like to use Canvas as our single source of truth for all sorts of user management information (such as class enrollment, active status, etc). Since our JupyterHub is exclusively provided for student use, I would like to use Canvas as the source of authentication information for our JupyterHub.

As the leader of an organization that benefits from the broader scientific python ecosystem, I would like to find ways to contribute back on behalf of my institution. I know we benefit from capacity and smooth operations on mybinder.org, and I would like to put some money towards sustaining that. However, handling procurement and getting my institution to pay out a few hundred dollars consistently every month comes with very high overhead and not worth it. Since we have a contractual relationship with 2i2c, I would like to support mybinder.org through cloud spend through 2i2c.

As a volunteer member of the team running mybinder.org, I would like to run our infrastructure on a diverse set of cheap hosting providers. This gives us extra capacity but also resiliency, as a single provider kicking us out would not shut us down completely. Since we provide arbitrary code execution, we are prime targets for cryptominers and other forms of network abuse that hosting providers don’t like. Handling abuse reports from hosting providers is stressful, and if I knew that being kicked out (even temporarily) will not cause a full outage, I’ll be a lot less stressed.

As a student, I am expected to click links that are provided to me (through my LMS, course website, slack or other medium) that will launch a jupyter notebook pre-populated with content related to my assignment or class. This mostly works fine, and preserves any changes I make in my content, and am happy! But in some rare cases, it does not work, and throws me a scary black error box with messages about git that I don’t really understand. Usually reaching out to my TAs can fix this, but it causes me stress and lost time.

As a TA, I often have to use the JupyterHub admin interface to run git commands to fix errors faced by some students when using nbgitpuller to distribute materials. I would very much rather spend my time on helping them learn, so more automatic ways to handle errors here would save me a lot of time.

As a Jupyter Book maintainer, I want to be able to update our community-facing documentation independently from our user-facing documentation. I want those updates to be immediately available to our community members without waiting for release cycles to update. I also want to know where to go to update different kinds of documentation.

As a Jupyter Book community member and user, I want an easy-to-remember place to refer to for important community documentation. For anything with a single source of truth (e.g., an events calendar), I don’t want to have multiple versions of the same page available because it’s tied to multiple “versions” of software in ReadTheDocs.