Quotas is Django application that provides generic implementation of quotas tracking functionality:
- Store and query resource limits and usages for project, customer or any other model.
- Aggregate quota usage in object hierarchies.
- Aggregate historical data for charting and analysis.
Define quota fields
Quotas are typically implemented on a per-model basis.
Model with quotas should inherit
QuotaModelMixin and define
Quotas class consists of set of quota fields. Consider the following example:
1 2 3 4 5 6 7 8 9 10
As you can see, Tenant model defines quota fields for number of virtual CPU cores, amount of RAM and storage.
Change object quotas usage and limit
To edit objects quotas use:
set_quota_limit- replace old quota limit with new one
set_quota_usage- replace old quota usage with new one
add_quota_usage- add value to quota usage
Do not edit quotas manually, because this will break quotas in objects ancestors.
Please note that aggregated usage is not stored in the database. Instead usage deltas are saved. The main reason behind it is to avoid deadlocks when multiple requests are trying to update the same quota for customer or project simultaneously.
Check if quota exceeded
To check if any of object quotas exceeded, use
validate_quota_change method of object with quotas.
This method receive dictionary of quotas usage deltas and returns errors if one or more quotas of object exceeded.
Sort objects by quotas with django_filters.FilterSet
QuotaFilterMixin and follow next steps to enable ordering by quotas.
-quotas__limit to filter meta
order_by attribute if you want to order by quotas limits. Ordering can be done only by one quota at a time.
Workflow for quota allocation
In order to prevent bugs when multiple simultaneous requests are performed, the following workflow is used.
1) As soon as we know what quota will be used we increase its usage.
It is performed in serializers' save or update method.
If quota usage becomes over limit, validation error is raised.
Consider for example
InstanceFlavorChangeSerializer in OpenStack plugin.
2) If backend API call for resource provision fails, frontend quota usage is not modified. Instead it is assumed that quota pulling is triggered either by user or by cron.
3) Quota usage is decreased only when backend API call for resource deletion succeeds.
Consider for example
delete_volume backend method in OpenStack plugin.