It is possible to limit the number of concurrent running jobs for a worker class
by using the
The worker must implement three methods:
perform_work: The concern implements the usual
performmethod and calls
perform_workif there’s any available capacity.
remaining_work_count: Number of jobs that have work to perform.
max_running_jobs: Maximum number of jobs allowed to run concurrently.
class MyDummyWorker include ApplicationWorker include LimitedCapacity::Worker def perform_work(*args) end def remaining_work_count(*args) 5 end def max_running_jobs 25 end end
Additional to the regular worker, a cron worker must be defined as well to
backfill the queue with jobs. the arguments passed to
are passed to the
class ScheduleMyDummyCronWorker include ApplicationWorker include CronjobQueue def perform(*args) MyDummyWorker.perform_with_capacity(*args) end end
max_running_jobs at almost all times.
The cron worker checks the remaining capacity on each execution and it
schedules at most
max_running_jobs jobs. Those jobs on completion
re-enqueue themselves immediately, but not on failure. The cron worker is in
charge of replacing those failed jobs.
This concern disables Sidekiq retries, logs the errors, and sends the job to the dead queue. This is done to have only one source that produces jobs and because the retry would occupy a slot with a job to perform in the distant future.
We let the cron worker enqueue new jobs, this could be seen as our retry and
back off mechanism because the job might fail again if executed immediately.
This means that for every failed job, we run at a lower capacity
until the cron worker fills the capacity again. If it is important for the
worker not to get a backlog, exceptions must be handled in
the job should not raise.
The jobs are deduplicated using the
:none strategy, but the worker is not
This concern exposes three Prometheus metrics of gauge type with the worker class name as label: