I went with celery/rabbitmq behind a load balancer running on the same image as 
my server.  I haven’t done any corner case testing, but so far it seems to 
scale up and down well after some tweaking on thresholds.  Doing this, rules 
out some of the smallest instances, as more memory is needed for each worker 
queue.  

Sent from my iPhone

> On Jan 15, 2019, at 8:29 PM, Jason <jjohns98...@gmail.com> wrote:
> 
> primarily because writes to db are expensive, and reads are less so but do 
> add load to an existing db.
> 
> besides, why not use the best tool for the job?  redis is much better at 
> read/write IO than dbs and functions perfectly well as a key-value store.  
> Rabbit is the gold standard for high availbility queue.
> 
> not saying you shouldn't use the db, but but when there are better options 
> that don't add extra load to an existing db infra that's already under 
> somewhat serious load
> 
> for example, my company regularly does full reindexes of all their content in 
> a solr search engine.  that can encompass somewhere in the neighborhood of 
> about 250k tasks and take 2.5-3 days to execute.  Do you _really_ want to 
> dump 250k records in your db in one go?  And another place I was at indexed 
> somewhere around 25M mirrored web pages, one page per task.  I would 
> definitely not wanted to have dumped all that in a db....
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