Hi Scott,

How is this progressing? I am really looking forward to your online meetup 
about this! I've currently got a cluster deployed using the output 
of https://github.com/quinston/arangodb-kubernetes with some tweaks, but 
due to using the Deployment resource type I think there is possibility for 
data loss / I have the same issue you mentioned above with nodes appearing 
as disconnected.

It'd be really great if ArangoDB officially supported this like they do for 
the DC/OS deployment.

Regards,
Aaron


On Thursday, 11 May 2017 19:58:29 UTC+1, Scott B. wrote:
>
> Hi all,
>
> I currently maintain a GitHub project designed to get ArangoDB up and 
> running in Kubernetes.  I'm working on using StatefulSets + Persistent 
> Volume Claims, so that as nodes crash and come back, they still have all of 
> their same data.  I mostly have it all working, but I'm hoping some of you 
> who might be familiar with how it works on the DCOS/Mesos side might have 
> some answers for me.  Specifically, I have two problems I still need to 
> solve:
>
> 1.  When I scale down the number of coordinators or db servers, they 
> remain as part of the cluster, marked as "shutdown".  How do I permanently 
> remove a member from the cluster?  Assuming that can be done, does ArangoDB 
> then automatically shuffle the data around (assuming replication factor 
> >=2) to other cluster nodes?
> 2.  What happens when say, a DB node goes down, then comes back up several 
> minutes later?  Does it "catch-up" to the changes that have occurred 
> elsewhere in the cluster while it was dead?  Is it helpful or harmful that 
> it comes back with the data it had when it crashed?  What I mean by this 
> is, will the node simply discard all of the old data anyway, then rejoin 
> the cluster as a new node, and then let the rebalancing happen?  Or does 
> picking up where it left off and "catching-up" help things, since there is 
> less data to move around?  What about the data that was presumably 
> rebalanced to other nodes when this node went down?
>
> Any insights are greatly appreciated.
>

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