Using Unicorn Worker Killer to help reduce queue backlog on Heroku with Unicorn

In light of the update from Heroku CTO Adam Wiggins and having been part of the efforts to test the larger Dynos with Unicorn on Heroku I felt it necessary to share Unicorn Worker Killer; a tool we have found indispensable.

Based on configurable thresholds for memory and number of requests received it will kill off a Unicorn Worker. For those of you on Heroku this is valuable in that it then returns all the requests back to the Heroku random routing. While not an exact correlation between too many requests and memory size it does help keep individual workers from becoming too overloaded.

Add this to your Gemfile:

gem 'unicorn-worker-killer'

The gem suggests that you configure your `config.ru` file for the thresholds. This can be cumbersome on Heroku if you need to test out different settings.

Thankfully you can also control the thresholds via environment variables. In config.ru do:

max_request_min =  ENV['MAX_REQUEST_MIN'].to_i || 3072
max_request_max =  ENV['MAX_REQUEST_MAX'].to_i || 4096

# Max requests per worker
use Unicorn::WorkerKiller::MaxRequests, max_request_min, max_request_max

oom_min = ((ENV['OOM_MIN'].to_i || 192) * (1024**2))
oom_max = ((ENV['OOM_MAX'].to_i || 256) * (1024**2))

# Max memory size (RSS) per worker
use Unicorn::WorkerKiller::Oom, oom_min, oom_max

The run this on the heroku command line:

heroku config:add OOM_MAX=256 memory_limit_min =192 MAX_REQUEST_MIN=3072 MAX_REQUEST_MAX=4096 -a unicon-ttm-sandbox

That will add in the variables needed to control the thresholds. The example shows the defaults though we found dropping the OOM_MAX to 216 worked best