今天跟踪了下openstack 资源的一个统计情况，记录下
1.节点资源统计在compute_notes表中
2.利用update_available_resource函数读取系统 /proc/meminfo中的总共资源以及可用的资源，算出已经使用的资源（这些值跟实例是没多大关系的，完全是系统值）
3.关键的属性 free_ram_mb free_disk_gb 的值是会随实例的创建和删除进行加减的。
update_available_resource调用db.compute_node_update
调用_adjust_compute_node_values_for_utilization
def _adjust_compute_node_values_for_utilization(context, values, session):
service_ref = service_get(context, values['service_id'], session=session)
host = service_ref['host']
ram_mb = values['memory_mb']
disk_gb = values['local_gb']
values.update(_get_host_utilization(context, host, ram_mb, disk_gb))
根据实例表进行统计
def _get_host_utilization(context, host, ram_mb, disk_gb):
"""Compute the current utilization of a given host."""
instances = instance_get_all_by_host(context, host)
vms = len(instances)
free_ram_mb = ram_mb - FLAGS.reserved_host_memory_mb
free_disk_gb = disk_gb - (FLAGS.reserved_host_disk_mb * 1024)
work = 0
for instance in instances:
free_ram_mb -= instance.memory_mb
free_disk_gb -= instance.root_gb
free_disk_gb -= instance.ephemeral_gb
if instance.vm_state in [vm_states.BUILDING, vm_states.REBUILDING,
vm_states.MIGRATING, vm_states.RESIZING]:
work += 1
return dict(free_ram_mb=free_ram_mb,
free_disk_gb=free_disk_gb,
current_workload=work,
running_vms=vms)
通过Capacity_notifier 中的nodify实现，每次实例操作的时候都会去更新。
例如删除实例：
if ended and event == 'delete':
vms = -1
payload = message.get('payload', {})
free_ram_mb = payload.get('memory_mb', 0)
free_disk_gb = payload.get('disk_gb', 0)
LOG.debug("EventType=%(event_type)s -> host %(host)s: "
"ram %(free_ram_mb)d, disk %(free_disk_gb)d, "
"work %(work)d, vms%(vms)d" % locals())
db.api.compute_node_utilization_update(context.get_admin_context(), host,
free_ram_mb_delta=free_ram_mb, free_disk_gb_delta=free_disk_gb,
work_delta=work, vm_delta=vms)