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"Found built image, launching..." but the session is not launching

See original GitHub issue

Bug description

This morning I shared my Jupyter Book project on social media – all of the notebooks included in the book have Binder instances – but Binder is not launching for the notebooks. The build log says “Found built image, launching…” but the instance never launches. Maybe this is happening because more people than usual are trying to launch Binder instances? Any suggestions for fixing this issue would be much appreciated.

How to reproduce

  1. Go to https://melaniewalsh.github.io/Intro-Cultural-Analytics/Data-Analysis/Pandas-Basics-Part1.html
  2. Click on the Binder instance in the top right corner https://mybinder.org/v2/gh/melaniewalsh/Intro-Cultural-Analytics/master?urlpath=lab/tree/book/Data-Analysis/Pandas-Basics-Part1.ipynb
  3. See “Found built image, launching…”

Your personal set up

  • OS: MacOS 10
  • Logs
"Found built image, launching..."

Issue Analytics

  • State:closed
  • Created 3 years ago
  • Comments:5 (2 by maintainers)

github_iconTop GitHub Comments

1reaction
melaniewalshcommented, Jan 7, 2021

Thanks so much! These are great tips for optimizing the Binder launch time, and it’s good to know about the upgrade. I will take any further questions or discussion to the Discussion Forum! Cheers.

0reactions
betatimcommented, Jan 7, 2021

I think you might have been a victim of an upgrade of a dependency we use to talk to the Kubernetes API. At least I can’t find anything else that looks out of the ordinary.

To make launches faster there are two things you can investigate:

  1. not reference master/main but a tag. This way not every typo fix triggers a rebuild. Instead you can periodically move the tag (say once a week or so)
  2. investigate making your image smaller via something like https://github.com/binder-examples/minimal-dockerfile. Smaller images are faster to transfer over the network which is one of the main time sinks after building the image

(2) speeds up launches a bit but means you are going the manual route, so some of the “magic” of binder (actually repo2docker) is lost. However with the increased control you can shrink the image a lot. Maybe something to investigate once things are becoming stable and development of the book slows down a bit?

(If you are happy please close the issue to help keep things a bit tidy 😄 We should continue optimisation talk in the forum on https://discourse.jupyter.org as that is more discoverable and has more readers who have ideas)

Read more comments on GitHub >

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