On 04/15/2014 06:03 AM, Jiangying (Jenny) wrote:
Sorry, I'm not quite clear about it yet.
I'm trying to find a way that heat controls the flow but not the nova
scheduler.
Heat doesn't control flow. Heat expects a scheduler is built into
whatever service it is consuming for resource management, if the
resource is constrained for some reason (such as limited memory, disk,
cpu resources available for consumption). This is why something like a
storage system (cinder) has a scheduler, and Heat does not.
It makes zero sense to add scheduling to Heat - since the projects that
Heat consumes are in much better position to make decisions about which
resources get scheduled when and where.
Regards
-steve
*???:*Henrique Truta [mailto:henriquecostatr...@gmail.com]
*????:*2014?4?14?21:39
*???:*OpenStack Development Mailing List (not for usage questions)
*??:*Re: [openstack-dev] [heat][nova]dynamic scheduling
Hello!
I'm currently investigating both of these features you have mentioned,
specifically on the NEAT[1] and GANTT[2] projects, as you might see on
the last week discussion.
Do you have any further ideas about how and why this would work with Heat?
Thanks,
Henrique
[1] http://openstack-neat.org/ <http://openstack-neat.org/>
[2] https://github.com/openstack/gantt
2014-04-13 22:53 GMT-03:00 Jiangying (Jenny)
<jenny.jiangy...@huawei.com <mailto:jenny.jiangy...@huawei.com>>:
Hi,
there has been a heated discussion about dynamic scheduling last
week.(http://www.mail-archive.com/openstack-dev@lists.openstack.org/msg21644.html)
I am also interested in this topic. We believe that dynamic scheduling
consists of two parts: balancing computing capacity and optimizing
power consumption.
For balancing computing capacity, the ceilometer periodically monitors
distribution and usage of CPU and memory resources for hosts and
virtual machines. Based on the information, the scheduler calculates
the current system standard deviation metric and determines the system
imbalance by comparing it to the target. To resolve the imbalance, the
scheduler gives the suitable virtual machine migration suggestions to
nova. In this way, the dynamic scheduling achieves higher
consolidation ratios and deliver optimized performance for the virtual
machines.
For optimizing power consumption, we attempt to keep the resource
utilization of each host within a specified target range. The
scheduler evaluates if the goal can be reached by balancing the system
workloads. If the resource utilization of a host remains below the
target, the scheduler calls nova to power off some hosts. Conversely
the scheduler powers on hosts to absorb the additional workloads. Thus
optimizing power consumption offers an optimum mix of resource
availability and power savings.
As Chen CH Ji said, "nova is a cloud solution that aim to control
virtual / real machine lifecycle management the dynamic scheduling
mechanism is something like optimization of the cloud resource". We
think implementing the dynamic scheduling with heat may be a good attempt.
Do you have any comments?
Thanks,
Jenny
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