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Fix failing workflows #502
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Bryan thought it could be something to do with memory, but the sizes of the images hasn't changed in a significant way since it started failing. I built jupyterlab-cpu locally from the main branch and it was just 7.74 GB |
We are almost always able to build RStudio (which weighs in at 9.2GB) and sometimes we can build JupyterLab-CPU (which weighs in at 7.57GB). JupyterLab-Pytorch is ~18GB. pagetbr@l-pagetbr-2:~/aaw-kubeflow-containers/output/rstudio$ docker images
REPOSITORY TAG IMAGE ID CREATED SIZE
rstudio latest 1a7696064cd2 3 hours ago 9.2GB
jupyterlab-cpu latest 1a0dfc4c6a1b 23 hours ago 7.57GB
jupyter/datascience-notebook ed2908bbb62e 3a31ab32404b 10 months ago 4.43GB |
I have created a JIRA ticket to track this issue: And I have posted an issue on the Github community message board: While I wait for the Github community to respond to my post, I have the following courses of action.
The following tickets are blocked by this issue: |
@vexingly discovered the version of Docker that Github Actions uses was updated right at the same time our builds started failing. RunnerFor the successful builds before August 04th 2023, we have the following image version:
And when the builds started failing, we have a new version of the runner (still based on Ubuntu 22.04):
DockerFor the older, successful runs:
The newer, failed runs:
This led us to investigate the changelog (https://docs.docker.com/engine/api/version-history/) and the epiphany came from
So we added
And now our builds are succeeding. |
#496 will have to be done next sprint. |
Some relevant information in --> #500 (comment)
I don't know what caused this, it doesnt seem to be the most recent changes Bryan did as I attempted reverting them but no difference
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