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Relax hook-image-puller to make upgrades more reliable #1787

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consideRatio
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@consideRatio consideRatio commented Sep 23, 2020

This configuration makes the hook-image-awaiter start comparing the
number of scheduled image-puller pods with the number of ready
image-puller pods, instead of comparing the number of desired
image-puller pods with the ready number of image-puller pods, after a
duration of 10 seconds.

This helps anyone using the hook-image-puller to avoid failures
of running helm upgrade that can happen if a node is full packed with
pods and no more pods can be scheduled on it, because then the
image-awaiter would get stuck waiting forever on an image pulling pod
that never successfully schedules to do the actual pulling.


@yuvipanda I merged #1763 and created this as a followup to the review comment #1763 (comment) about sticking with the existing behavior until its been tested a while.

This configuration makes the hook-image-awaiter start comparing the
number of scheduled image-puller pods with the number of ready
image-puller pods, instead of comparing the number of desired
image-puller pods with the ready number of image-puller pods, after a
duration of 10 seconds.

This helps anyone using the hook-image-puller to avoid failures
of running `helm upgrade` that can happen if a node is full packed with
pods and no more pods can be scheduled on it, because then the
image-awaiter would get stuck waiting forever on an image pulling pod
that never successfully schedules to do the actual pulling.
@yuvipanda
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Awesome! I'll deploy current master in a day or so and we'll give it a couple weeks?

@consideRatio
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@yuvipanda deal, thanks! I love that you are an active user of the master branch, it really helps the development of a project to have those that use the tip of the master branch.

@consideRatio
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@yuvipanda OK to merge merge this prior to releasing 0.10.0-beta.1?

@yuvipanda yuvipanda merged commit dea5cf1 into jupyterhub:master Oct 2, 2020
@yuvipanda
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Thanks for waiting, @consideRatio!

@consideRatio
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@yuvipanda and @GeorgianaElena thank you for your review work on this feature! ❤️

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2 participants