Metrics
Built-in Metrics for your queues.
BullMQ provides a simple metrics gathering functionality that allows you to track the performance of your queues. Workers can count the number of jobs they have processed per minute and store this data in a list inside Redis so that it can be queried later.
You enable it on the worker settings by specifying how many data points you want to keep, which basically are counters of the number of jobs that have been processed either completed or failed during 1 minute intervals.
As the metrics are aggregated in 1 minute intervals, using the recommended duration of 2 weeks of data should take a very small amount of total space, just around 120Kb of RAM per queue. The metrics will dispose older data points automatically so this RAM consumption will never increase after it reaches the maximum number of data points.
Check in this example how to enable metrics on a worker:
You need to use the same setting on all your workers to get consistent metrics.
In order to query the metrics, use the getMetrics
method on the Queue
class. You can choose to gather the metrics for the completed or failed jobs:
Let's analyze what data we are getting back. First we have the meta
field. The prevTS
and prevCount
subfields are used internally by the metrics system and should not be used, however you can use thecount
subfield to get a total number for all completed or failed jobs, this counter is not just the number of completed jobs in the given interval, but since the queue started processing jobs.
The query also returns a data
field which is an array where every position in the array represents 1 minute of time and has the total number of jobs that completed (or failed) in that minute.
Note that the getMetrics
method also accepts a start
and end
argument (0
and -1
by default), that you can use if you want to implement pagination.
Read more:
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