Hi Patrik,

You are absolutely correct. I don't know what was going through my mind 
when I said that there are multiple instances of an entry running. Haven't 
been getting much sleep lately :/

As for my use-case, I'm trying to build a pipeline that takes in a data 
stream and processes it in different ways. Since the stream has to be 
running uninterrupted (and has to be able to recover on its own) I'm 
thinking of doing by using a singleton (to avoid automatic re-balancing and 
losing the data flow) or by using sharding but with my own implementation 
of a ShardAllocationStrategy like Martynas suggested.

After the stream come what I'll call the worker actors. Each worker is 
responsible for doing some change to each message (ie. finding sentiment, 
the author's gender, etc) in the data stream and passing it on. The workers 
will be using the pulling pattern and will be implemented as Processor. 
Each worker will contain a router pool of routees that do the actual 
processing while the worker itself serves as a coordinator. I'm going to be 
using RabbitMQ as the data-store that the stream writes to and the workers 
pull off of, process, and put back into different queues within Rabbit. 

For the workers, I was thinking of using sharding to be able to scale the 
system (as described in my first post where the routers would re-size 
themselves after the entry gets restarted from re-balancing) and for the 
high-availability that it offers. I considered using singletons except that 
they would probably create a bottleneck in my cluster since they would all 
be created on the oldest node of the cluster. Using roles wouldn't help 
that much because then that would limit what nodes the workers can run on 
which means that if all the nodes of a certain role go down, then I would 
lose that particular type of worker which in turn causes issues with 
RabbitMQ.

Does that help?

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