Perhaps take a look at this example:
https://github.com/akka/akka-distributed-workers-scala
It has recently been updated, and the guide is not published yet, but you
can build it yourself with:

sbt docs/paradox
open docs/target/paradox/site/main/index.html

Cheers,
Patrik

On Sat, Sep 9, 2017 at 9:31 PM, Dima Sabanin <[email protected]> wrote:

> Hi everyone,
>
> I'm building a system that should distribute CPU/RAM/IO intensive work
> between N+1 nodes.
>
> Work comes in as Jobs from Akka HTTP endpoint. Then it gets assigned to a
> worker
> on one of the available nodes, locally or remotely, ideally in a fair
> manner as to not overload any node.
> Nodes are added and removed from cluster dynamically.
>
> Important requirements are:
>
> * nodes can get overloaded (due to intensity of work), that's why there
> should be a limit of workers per node, either
> self-adjusting or manual
> * Akka HTTP endpoint should never block the clients, even if all the
> workers are busy. It should accept
> the Job and queue it for later processing.
> * nice to have: persisting of the Jobs that are in queue so that JVM
> restarts do not reset the queue.
>
> I would appreciate any help or advice. I've been battling this for a few
> days, but things I do either block the endpoint
> overload the nodes or not spread the work throughout the cluster. I'd love
> a clean slate advice on how this should be done
> the Akka way.
>
> Thank you!
>
> Best regards,
> Dima
>
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-- 

Patrik Nordwall
Akka Tech Lead
Lightbend <http://www.lightbend.com/> -  Reactive apps on the JVM
Twitter: @patriknw

-- 
>>>>>>>>>>      Read the docs: http://akka.io/docs/
>>>>>>>>>>      Check the FAQ: 
>>>>>>>>>> http://doc.akka.io/docs/akka/current/additional/faq.html
>>>>>>>>>>      Search the archives: https://groups.google.com/group/akka-user
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