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License: GNU General Public License v3.0
Bootcamp for testing workflow execution backend service for CERN Analysis Preservation.
License: GNU General Public License v3.0
Include Redis
nodes inside actual cluster in order to use it from step-broker
and k8s-job-patch
Now raw requests are being sent to the k8s apiserver but ideally it would be better to choose a library that covers all the needed use cases. In case there is no such library, get the most mature/best documented/most active and make a PR adding the needed functionality.
Library | Contributors | Version | Jobs | Stream calls | In-cluster calls | Tests | Repo |
---|---|---|---|---|---|---|---|
pykube | 21 | 0.13.0 | x | x | x | x | link |
kube | 3 | 0.9.1 | - | x | x | - | link |
python-k8sclient | 11 | 0.3.0 | - | - | x | x | link |
python-kubernetes | 1 | 0.2 | - | - | x | - | link |
If the number of Jobs created exceeds the defined ResourceQuota
the waiting jobs are scheduled after a while even though there is available quota, it may be seconds, it may be minutes, but it affects the whole cluster. When Kubernetes "refresh its internal state" all the waiting jobs get executed.
Because of #3, #4 and the lack of a status notifying system for Jobs in Kubernetes(which conduced to #6) the decision of using Kubernetes has to be reconsidered.
This could lead to a potentially infinite number of restarts of a container, for instance, their execution may be stopped because a dependency can not be met anymore (broken link).
A workflow is composed by a set of steps which are mapped to k8s Jobs. In terms of workflows, the expected behaviour is that if a step fails a log is retrieved and the user gets a message saying that there was a problem, specifically in a certain step.
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