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From "Vladimir (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (AURORA-1948) Adding instances leads to constraints conflict
Date Thu, 21 Sep 2017 18:07:00 GMT

    [ https://issues.apache.org/jira/browse/AURORA-1948?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16175215#comment-16175215
] 

Vladimir commented on AURORA-1948:
----------------------------------

[~wfarner] Thanks for the comments. Sure, it a bigger task than just a bug. It means that
the current scaling functionality has some limitations (you can not change the initial constraints
without rerunning the whole job), but on the other hand the fix to this is a separate big
thing which would probably involve some redesign.

> Adding instances leads to constraints conflict
> ----------------------------------------------
>
>                 Key: AURORA-1948
>                 URL: https://issues.apache.org/jira/browse/AURORA-1948
>             Project: Aurora
>          Issue Type: Story
>          Components: Scheduler
>            Reporter: Vladimir
>            Priority: Minor
>
> Problem: 
> When scaling instances (adding more instances) there could be a constraint conflict.
> Example:
> Let's say you have a mesos cluster with 3 racks. You want to deploy a service and create
aurora job with the "rack" constraint "limit" set to 1. So basically it means that no more
than 1 instance per rack. The job has number of instances set to 2, for example. The deployment
will succeed and user would get 2 instances running on 2 different racks. 
> Next user would like to scale it to 4 instances by adding 2 more instances. In this case
if user won't update the rack constraint (set limit to 2 or larger), the update job would
fail showing "Limit not satisfied: rack". If user would modify the constraints, then the regular
Job update would be involved which would add new instances but also update the existing ones
(rolling deploy). 
> Proposal:
> The proposal is to be able to update the constraints while adding new instances in order
to satisfy the limits and be sure that the currently running instances won't be redeployed.
> So in my example, when scaling up we can recalculate the rack limit on our end, update
it's value in the job config, update number of instances and start job update. Aurora would
leave 2 currently running instances as they are and only add two new instances making sure
that the new constraints are satisfied..



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