Great! Thanks Jim.
I will later report our experience with conductor groups.
Belmiro CERN
On Tue, Nov 12, 2019 at 5:58 PM Jim Rollenhagen jim@jimrollenhagen.com wrote:
On Tue, Nov 12, 2019 at 11:38 AM Belmiro Moreira < moreira.belmiro.email.lists@gmail.com> wrote:
Dan Smith just point me the conductor groups that were added in Stein.
https://specs.openstack.org/openstack/nova-specs/specs/stein/implemented/iro... This is an interesting way to partition the deployment much better than the multiple nova-computes setup.
Just a note, they aren't mutually exclusive. You can run multiple nova-computes to manage a single conductor group, whether for HA or because you're using groups for some other construct (cells, racks, halls, network zones, etc) which you want to shard further.
// jim
Thanks, Belmiro CERN
On Tue, Nov 12, 2019 at 5:06 PM Belmiro Moreira < moreira.belmiro.email.lists@gmail.com> wrote:
Hi, using several cells for the Ironic deployment would be great however it doesn't work with the current architecture. The nova ironic driver gets all the nodes available in Ironic. This means that if we have several cells all of them will report the same nodes! The other possibility is to have a dedicated Ironic instance per cell, but in this case it will be very hard to manage a large deployment.
What we are trying is to shard the ironic nodes between several nova-computes. nova/ironic deployment supports several nova-computes and it will be great if the RT nodes cycle is sharded between them.
But anyway, this will also require speeding up the big lock. It would be great if a compute node can handle more than 500 nodes. Considering our use case: 15k/500 = 30 compute nodes.
Belmiro CERN
On Mon, Nov 11, 2019 at 9:13 PM Matt Riedemann mriedemos@gmail.com wrote:
On 11/11/2019 7:03 AM, Chris Dent wrote:
Or using separate processes? For the ironic and vsphere contexts, increased CPU usage by the nova-compute process does not impact on the workload resources, so parallization is likely a good option.
I don't know how much it would help - someone would have to actually test it out and get metrics - but one easy win might just be using a thread or process executor pool here [1] so that N compute nodes could be processed through the update_available_resource periodic task concurrently, maybe $ncpu or some factor thereof. By default make it serialized for backward compatibility and non-ironic deployments. Making that too highly concurrent could have negative impacts on other things running on that host, like the neutron agent, or potentially storming conductor/rabbit with a ton of DB requests from that compute.
That doesn't help with the scenario that the big COMPUTE_RESOURCE_SEMAPHORE lock is held by the periodic task while spawning, moving, or deleting an instance that also needs access to the big lock to update the resource tracker, but baby steps if any steps in this area of the code would be my recommendation.
[1]
https://github.com/openstack/nova/blob/20.0.0/nova/compute/manager.py#L8629
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Thanks,
Matt