Manila oversubscription enhancements¶
About allocated_capacity_gb and provisioned_capacity_gb, allocated_capacity_gb corresponds to shares_gb created on a storage pool via manila. provisioned_capacity_gb is equal to the sum of allocated_capacity_gb add shares_gb_created_manually (or another manila) on the same storage pool. It implies that provisioned_capacity_gb greater than or equal to allocated_capacity_gb. It is important for administrators to know these two values in order to obtain information about back-end allocated capacity.
For a storage backend that supports thin provisioning,The following describes the reported capacity information.
total_capacity_gb = Total physical disk capacity of the storage pool used by Manila.
free_capacity_gb = total_capacity_gb - Used physical disk capacity of the storage pool.
provisioned_capacity_gb = Total capacity allocated by all shares (include shares created manually or other manila) in the storage pool.
allocated_capacity_gb = Total capacity allocated by all shares created by current manila.
Problem One: Here’s an example. Storage pool pool_A physical disk capacity is 10G. There are four shares in this pool. Share A created by openstack O_A(current manila), share size is 5G. There is a 124MB file in this share. Share B created by openstack O_A(current manila), share size is 4G. There is a 0MB file in this share. Share C created by openstack O_B, share size is 3G. There is a 400MB file in this share. Share D created manually, share size is 2G. There is a 500MB file in this share.
The total physical capacity in use is 1G(124MB+0MB+400MB+500MB), the result is: total_capacity_gb = 10G free_capacity_gb = 9G provisioned_capacity_gb = 14G (5G+4G+3G+2G) allocated_capacity_gb = 9G (5G+4G, only share A and B is created by current manila)
In fact, the storage back end doesn’t know how many Manila services are using the storage pool or whether the administrator has manually created shares in the pool. So the allocated_capacity_gb reported by backend storage driver is not correct. Only provisioned_capacity_gb reported by backend storage driver is correct.
Currently, some drivers (inspur, huawei, netapp, qnap, zadara) report allocated_capacity_gb and some drivers (infinibox, hpe_3par, nexenta) report provisioned_capacity_gb, which is chaotic.
Problem Two: About scheduler service supports Active/Active HA, The consume_from_share function is executed each time a share is created or extend, in this function allocated_capacity_gb and free_capacity_gb must be updated. Let’s suppose 100 1gb shares are created, 50 of which are executed on node 1 and 30 on node 2 and 20 on node 3. Since allocated_capacity_gb is maintained in the memory of the scheduling service. As a result, the allocated_capacity_gb values of the three scheduling nodes are inconsistent. This is problematic. We need to calibrate allocated_capacity_gb periodically.
The administrator can view the capacity allocation of the back-end storage by allocated_capacity_gb and provisioned_capacity_gb.
Manila scheduler use provisioned_capacity_gb to filter and weigh back-end.
This spec proposes to:
allocated_capacity_gb reported by driver may be correct if the driver is capable of tracking it accurately, but allocated_capacity_gb calculated from database must be correct. So for uniformity, allocated_capacity_gb will use calculated by database rather than reported by driver.
we strongly recommend that the driver report provisioned_capacity_gb, if it is not reported, Manila is considered exclusive storage pool, will use allocated_capacity_gb as the provisioned_capacity_gb value.
for problem two, Add a periodic task in Manila Share to periodically collect allocated_capacity_gb statistics from the database and record it in self._allocated_capacity_gb(a member variable of class ShareManager). Read self._allocated_capacity_gb and update allocated_capacity_gb in share_stats[pools] when executing _report_driver_status. Because Manila doesn’t require very much real-time data for allocated_capacity_gb, Therefore, the interval of periodic tasks can be set to 5 minutes to reduce system and database pressure.
The current model is an alternative, however, the calculation occuring in the scheduler is problematic because it’s happening in each scheduler process for each backend and for each pool, which is inefficient and wrong
Data model impact¶
REST API impact¶
Other end user impact¶
we’d be removing a huge performance bottleneck from the scheduler service!
Other deployer impact¶
Drivers should update to report provisioned_capacity_gb instead of allocated_capacity_gb.
- Primary assignee:
Update share manager and scheduler’s host manager.
Update related documents.
Add the unit tests
The following OpenStack documentations will be updated to reflect this change:
OpenStack Contributor Guide