High memory when delete object change middleware delete a large object changes #3468

New Issue

adam · 2025-12-29T18:29:22+01:00

adam commented

2025-12-29 18:29:22 +01:00

Originally created by @haminhcong on GitHub (Mar 12, 2020).

Environment

Python version: 3.6.9
NetBox version: 2.7.9

Steps to Reproduce

Create/update a large object number (100 000 objects) in a day
After 90 days run update some objects
Check memory usage

Expected Behavior

Netbox memory usage stable anytime.

Observed Behavior

When object changes number need to delete in retention_cycle is very high, in my case is 100 000 - 1 000 000 ObjectChange objects , object_change_delete process current used in netbox Middleware is not paging => leads to Netbox memory usage is very high when delete object change process run:

https://github.com/netbox-community/netbox/blob/develop/netbox/extras/middleware.py#L146

        if settings.CHANGELOG_RETENTION and random.randint(1, 100) == 1:
            cutoff = timezone.now() - timedelta(days=settings.CHANGELOG_RETENTION)
            purged_count, _ = ObjectChange.objects.filter(
                time__lt=cutoff
            ).delete()

a gunicorn worker normaly usage 100 MB RAM, when run this process, raise to 2 GB RAM and lead to VM memory error

I suggest paging this query to avoid memory high usage, and if needed, move this process to run in django rq worker to avoid http_timeout (default is 60 seconds in gunicorn). Somethings like this:

    cutoff = timezone.now() - timedelta(days=settings.CHANGELOG_RETENTION)
    offset = 0
    pagesize = 500
    obj_list_qs = ObjectChange.objects.filter(
        time__lt=cutoff
    )
    count = obj_list_qs.count()
    while offset < count:
        for objectchange in obj_list_qs[offset: offset + pagesize]:
            objectchange.delete()
        offset += pagesize

Originally created by @haminhcong on GitHub (Mar 12, 2020).  ### Environment * Python version: 3.6.9 * NetBox version: 2.7.9  ### Steps to Reproduce 1. Create/update a large object number (100 000 objects) in a day 2. After 90 days run update some objects 3. Check memory usage  ### Expected Behavior Netbox memory usage stable anytime.  ### Observed Behavior When object changes number need to delete in retention_cycle is very high, in my case is 100 000 - 1 000 000 ObjectChange objects , object_change_delete process current used in netbox Middleware is not paging => leads to Netbox memory usage is very high when delete object change process run: https://github.com/netbox-community/netbox/blob/develop/netbox/extras/middleware.py#L146 ```python if settings.CHANGELOG_RETENTION and random.randint(1, 100) == 1: cutoff = timezone.now() - timedelta(days=settings.CHANGELOG_RETENTION) purged_count, _ = ObjectChange.objects.filter( time__lt=cutoff ).delete() ``` a gunicorn worker normaly usage 100 MB RAM, when run this process, raise to 2 GB RAM and lead to VM memory error I suggest paging this query to avoid memory high usage, and if needed, move this process to run in django rq worker to avoid http_timeout (default is 60 seconds in gunicorn). Somethings like this: ```python cutoff = timezone.now() - timedelta(days=settings.CHANGELOG_RETENTION) offset = 0 pagesize = 500 obj_list_qs = ObjectChange.objects.filter( time__lt=cutoff ) count = obj_list_qs.count() while offset < count: for objectchange in obj_list_qs[offset: offset + pagesize]: objectchange.delete() offset += pagesize ```

adam added the pending closure label 2025-12-29 18:29:22 +01:00

adam closed this issue

2025-12-29 18:29:22 +01:00

adam commented

2025-12-29 18:29:23 +01:00

@stale[bot] commented on GitHub (Mar 26, 2020):

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. NetBox is governed by a small group of core maintainers which means not all opened issues may receive direct feedback. Please see our contributing guide.

@stale[bot] commented on GitHub (Mar 26, 2020): This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. NetBox is governed by a small group of core maintainers which means not all opened issues may receive direct feedback. Please see our [contributing guide](https://github.com/netbox-community/netbox/blob/develop/CONTRIBUTING.md).

adam commented

2025-12-29 18:29:23 +01:00

@stale[bot] commented on GitHub (Apr 2, 2020):

This issue has been automatically closed due to lack of activity. In an effort to reduce noise, please do not comment any further. Note that the core maintainers may elect to reopen this issue at a later date if deemed necessary.

@stale[bot] commented on GitHub (Apr 2, 2020): This issue has been automatically closed due to lack of activity. In an effort to reduce noise, please do not comment any further. Note that the core maintainers may elect to reopen this issue at a later date if deemed necessary.

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Reference: starred/netbox#3468