How is this different than extra_specs used by the filter scheduler?
http://docs.openstack.org/developer/nova/devref/filter_scheduler.html
I did some very old blueprints related to heterogeneous architectures that had
similar goals.
https://blueprints.launchpad.net/nova/+spec/heterogeneous-instance-types
Fully support the idea, but probably can adapt the existing functionality to
also target metric data.
—
Sent from Mailbox for iPad
On Wed, Jul 17, 2013 at 10:56 PM, Lu, Lianhao <lianhao...@intel.com>
wrote:
> Hi fellows,
> Currently we're implementing the BP
> https://blueprints.launchpad.net/nova/+spec/utilization-aware-scheduling. The
> main idea is to have an extensible plugin framework on nova-compute where
> every plugin can get different metrics(e.g. CPU utilization, memory cache
> utilization, network bandwidth, etc.) to store into the DB, and the
> nova-scheduler will use that data from DB for scheduling decision.
> Currently we adds a new table to store all the metric data and have
> nova-scheduler join loads the new table with the compute_nodes table to get
> all the data(https://review.openstack.org/35759). Someone is concerning about
> the performance penalty of the join load operation when there are many
> metrics data stored in the DB for every single compute node. Don suggested
> adding a new column in the current compute_nodes table in DB, and put all
> metric data into a dictionary key/value format and store the json encoded
> string of the dictionary into that new column in DB.
> I'm just wondering which way has less performance impact, join load with a
> new table with quite a lot of rows, or json encode/decode a dictionary with a
> lot of key/value pairs?
> Thanks,
> -Lianhao
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