The error 'bullmq memory leak' typically arises when excessive data is stored in the BullMQ queues without getting processed or removed. A few common causes for this are:
Insufficient Worker Processes: If there aren't enough workers to process jobs, they may pile up in the queue, consuming increasing amounts of memory.
Lack of Job Removal: Completed and failed job records might not be removed from the queue, causing unnecessary accumulation.
Delayed Jobs: These are jobs that are not ready to be processed immediately, and a notably large number of them may cause memory usage to increase over time.
Solution - Here's How To Resolve It
To resolve the memory leak issue in BullMQ, consider the following strategies:
Scale the Workers: Make sure you have sufficient worker processes to handle the incoming flow of jobs. You can use clustering or child processes to scale horizontally.
Remove Jobs After Completion: Implement auto-removal of completed and failed jobs from the queue by setting the 'removeOnComplete' and 'removeOnFail' options.
Monitor Delayed Jobs: Keep an eye on delayed jobs and limit their quantity if possible. Alternatively, consider using a priority queue for critical tasks to ensure they're handled even when many jobs are delayed.
Regular Monitoring and Auditing: Regularly monitor and audit your queues to identify unexpected behaviour like sudden memory spikes. Tools like Prometheus and Grafana can help with monitoring and visualizing queue performance.