On 07/19/2013 05:36 PM, Boris Pavlovic wrote:
> Sandy,
> 
> I don't think that we have such problems here.
> Because scheduler doesn't pool compute_nodes. 
> The situation is another compute_nodes notify scheduler about their
> state. (instead of updating their state in DB)
> 
> So for example if scheduler send request to compute_node, compute_node
> is able to run rpc call to schedulers immediately (not after 60sec).
> 
> So there is almost no races.

There are races that occur between the eventlet request threads. This is
why the scheduler has been switched to single threaded and we can only
run one scheduler.

This problem may have been eliminated with the work that Chris Behrens
and Brian Elliott were doing, but I'm not sure.

But certainly, the old approach of having the compute node broadcast
status every N seconds is not suitable and was eliminated a long time ago.

> 
> 
> Best regards,
> Boris Pavlovic
> 
> Mirantis Inc. 
> 
> 
> 
> On Sat, Jul 20, 2013 at 12:23 AM, Sandy Walsh <sandy.wa...@rackspace.com
> <mailto:sandy.wa...@rackspace.com>> wrote:
> 
> 
> 
>     On 07/19/2013 05:01 PM, Boris Pavlovic wrote:
>     > Sandy,
>     >
>     > Hm I don't know that algorithm. But our approach doesn't have
>     > exponential exchange.
>     > I don't think that in 10k nodes cloud we will have a problems with 150
>     > RPC call/sec. Even in 100k we will have only 1.5k RPC call/sec.
>     > More then (compute nodes update their state in DB through conductor
>     > which produce the same count of RPC calls).
>     >
>     > So I don't see any explosion here.
> 
>     Sorry, I was commenting on Soren's suggestion from way back (essentially
>     listening on a separate exchange for each unique flavor ... so no
>     scheduler was needed at all). It was a great idea, but fell apart rather
>     quickly.
> 
>     The existing approach the scheduler takes is expensive (asking the db
>     for state of all hosts) and polling the compute nodes might be do-able,
>     but you're still going to have latency problems waiting for the
>     responses (the states are invalid nearly immediately, especially if a
>     fill-first scheduling algorithm is used). We ran into this problem
>     before in an earlier scheduler implementation. The round-tripping kills.
> 
>     We have a lot of really great information on Host state in the form of
>     notifications right now. I think having a service (or notification
>     driver) listening for these and keeping an the HostState incrementally
>     updated (and reported back to all of the schedulers via the fanout
>     queue) would be a better approach.
> 
>     -S
> 
> 
>     >
>     > Best regards,
>     > Boris Pavlovic
>     >
>     > Mirantis Inc.
>     >
>     >
>     > On Fri, Jul 19, 2013 at 11:47 PM, Sandy Walsh
>     <sandy.wa...@rackspace.com <mailto:sandy.wa...@rackspace.com>
>     > <mailto:sandy.wa...@rackspace.com
>     <mailto:sandy.wa...@rackspace.com>>> wrote:
>     >
>     >
>     >
>     >     On 07/19/2013 04:25 PM, Brian Schott wrote:
>     >     > I think Soren suggested this way back in Cactus to use MQ
>     for compute
>     >     > node state rather than database and it was a good idea then.
>     >
>     >     The problem with that approach was the number of queues went
>     exponential
>     >     as soon as you went beyond simple flavors. Add Capabilities or
>     other
>     >     criteria and you get an explosion of exchanges to listen to.
>     >
>     >
>     >
>     >     > On Jul 19, 2013, at 10:52 AM, Boris Pavlovic
>     <bo...@pavlovic.me <mailto:bo...@pavlovic.me>
>     >     <mailto:bo...@pavlovic.me <mailto:bo...@pavlovic.me>>
>     >     > <mailto:bo...@pavlovic.me <mailto:bo...@pavlovic.me>
>     <mailto:bo...@pavlovic.me <mailto:bo...@pavlovic.me>>>> wrote:
>     >     >
>     >     >> Hi all,
>     >     >>
>     >     >>
>     >     >> In Mirantis Alexey Ovtchinnikov and me are working on nova
>     scheduler
>     >     >> improvements.
>     >     >>
>     >     >> As far as we can see the problem, now scheduler has two
>     major issues:
>     >     >>
>     >     >> 1) Scalability. Factors that contribute to bad scalability
>     are these:
>     >     >> *) Each compute node every periodic task interval (60 sec
>     by default)
>     >     >> updates resources state in DB.
>     >     >> *) On every boot request scheduler has to fetch information
>     about all
>     >     >> compute nodes from DB.
>     >     >>
>     >     >> 2) Flexibility. Flexibility perishes due to problems with:
>     >     >> *) Addiing new complex resources (such as big lists of complex
>     >     objects
>     >     >> e.g. required by PCI Passthrough
>     >     >>
>     >    
>     https://review.openstack.org/#/c/34644/5/nova/db/sqlalchemy/models.py)
>     >     >> *) Using different sources of data in Scheduler for example
>     from
>     >     >> cinder or ceilometer.
>     >     >> (as required by Volume Affinity Filter
>     >     >> https://review.openstack.org/#/c/29343/)
>     >     >>
>     >     >>
>     >     >> We found a simple way to mitigate this issues by avoiding
>     of DB usage
>     >     >> for host state storage.
>     >     >>
>     >     >> A more detailed discussion of the problem state and one of
>     a possible
>     >     >> solution can be found here:
>     >     >>
>     >     >>
>     >    
>     
> https://docs.google.com/document/d/1_DRv7it_mwalEZzLy5WO92TJcummpmWL4NWsWf0UWiQ/edit#
>     >     >>
>     >     >>
>     >     >> Best regards,
>     >     >> Boris Pavlovic
>     >     >>
>     >     >> Mirantis Inc.
>     >     >>
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