JMeybohm added a comment.

  > To be discussed with service ops:
  >
  > - Investigate and address the reasons why after a node failure k8s did not 
fulfill its promise of making sure that the rdf-streaming-updater deployment 
have 6 working replicas
  
  The problem was more that the node did not really fail (to it's complete 
extend). It was heavily overloaded (for an unknown reason) and that's 
potentially why containers/processed running there seemed dead. But from K8s 
perspective the Pods where still running and a new pod was scheduled as soon as 
I power cycled the node (e.g. K8s was able to detect a mismatch in desired end 
existing replicas).
  
  > - If the above is not possible could we mitigate this problem by 
over-allocating resources (increase the number of replicas) to the deployment 
to increase the chances of proper recovery if this situation happens again?
  
  If that makes sense from your POV you could do that ofc. I can't speak on how 
problematic this situation was compared to the potential waste of resources 
another pod means. But if the current workload is already maxing out the 
capacity of the 6 replicas you have, maybe bumping that to 7 might be smart 
anyways to account for peaks?
  
  In T301147#7821422 <https://phabricator.wikimedia.org/T301147#7821422>, 
@dcausse wrote:
  
  > @JMeybohm do you see any additional action items that would improve the 
resilience of k8s in such scenario?
  
  Unfortunately we don't have any data on what went wrong on the node. I think 
T277876 <https://phabricator.wikimedia.org/T277876> would be a step in the 
right direction but I also doubt it would have fully prevented this issue 
(ultimately I can't say).

TASK DETAIL
  https://phabricator.wikimedia.org/T301147

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