为了网络的安全和业务的正常运作,持续注意网络的健康状况是最基本的工作,找出网络的错误,发现真正的原因需要清楚的知道网络的状态,本文介绍如何使用OpenFlow来取得相关的统计信息。
from operator import attrgetter
from ryu.app import simple_switch_13
from ryu.controller import ofp_event
from ryu.controller.handler import MAIN_DISPATCHER, DEAD_DISPATCHER
from ryu.controller.handler import set_ev_cls
from ryu.lib import hub
class SimpleMonitor(simple_switch_13.SimpleSwitch13):
def __init__(self, *args, **kwargs):
super(SimpleMonitor, self).__init__(*args, **kwargs)
self.datapaths = {}
self.monitor_thread = hub.spawn(self._monitor)#建立一个绿色线程,运行监控程序
#一般状态和连线中断状态,EventOFPStatureChange的信息类用来监测交换器的连线中断,会被触发在#Dathpath状态改变时
@set_ev_cls(ofp_event.EventOFPStateChange,
[MAIN_DISPATCHER, DEAD_DISPATCHER])
def _state_change_handler(self, ev):#通过判断当前状态从监测列表添加或移除当前datapath
datapath = ev.datapath
if ev.state == MAIN_DISPATCHER:
if not datapath.id in self.datapaths:
self.logger.debug('register datapath: %016x', datapath.id)
self.datapaths[datapath.id] = datapath
elif ev.state == DEAD_DISPATCHER:
if datapath.id in self.datapaths:
self.logger.debug('unregister datapath: %016x', datapath.id)
del self.datapaths[datapath.id]
def _monitor(self):
while True:
for dp in self.datapaths.values():
self._request_stats(dp)#每隔10s查询一次当前的监视datapath名单中的各个#datapath状况
hub.sleep(10)
def _request_stats(self, datapath):
self.logger.debug('send stats request: %016x', datapath.id)
ofproto = datapath.ofproto
parser = datapath.ofproto_parser
#向指定的datapath发送OFPFlowStatsRequest和OFPStatsResquest消息类实体,即对相关统计信息进行
#请求
req = parser.OFPFlowStatsRequest(datapath)
datapath.send_msg(req)
req = parser.OFPPortStatsRequest(datapath, 0, ofproto.OFPP_ANY)
datapath.send_msg(req)
#对FlowStatsReply消息的回复进行事件处理
@set_ev_cls(ofp_event.EventOFPFlowStatsReply, MAIN_DISPATCHER)
def _flow_stats_reply_handler(self, ev):
body = ev.msg.body
self.logger.info('datapath '
'in-port eth-dst '
'out-port packets bytes')
self.logger.info('---------------- '
'-------- ----------------- '
'-------- -------- --------')
#对各个优先级非0的流表项按接收端口和目的MAC地址进行排序后遍历
for stat in sorted([flow for flow in body if flow.priority == 1],
key=lambda flow: (flow.match['in_port'],
flow.match['eth_dst'])):
#对交换机的datapath.id,目的MAC地址,输出端口和包以及字节流量进行打印
self.logger.info('%016x %8x %17s %8x %8d %8d',
ev.msg.datapath.id,
stat.match['in_port'], stat.match['eth_dst'],
stat.instructions[0].actions[0].port,
stat.packet_count, stat.byte_count)
#对PortStatsReply消息的回复事件进行处理
@set_ev_cls(ofp_event.EventOFPPortStatsReply, MAIN_DISPATCHER)
def _port_stats_reply_handler(self, ev):
body = ev.msg.body
self.logger.info('datapath port '
'rx-pkts rx-bytes rx-error '
'tx-pkts tx-bytes tx-error')
self.logger.info('---------------- -------- '
'-------- -------- -------- '
'-------- -------- --------')
#根据端口号进行排序并遍历
for stat in sorted(body, key=attrgetter('port_no')):
#打印交换机id,端口号和接收及发送的包的数量字节数和错误数
self.logger.info('%016x %8x %8d %8d %8d %8d %8d %8d',
ev.msg.datapath.id, stat.port_no,
stat.rx_packets, stat.rx_bytes, stat.rx_errors,
stat.tx_packets, stat.tx_bytes, stat.tx_errors)
OFPFlowStatsRequest主要对交换机的流表的统计信息,可以使用table ID,output port,cookie值和match条件来缩限查找范围,本例中是取得所有的流表项。
OFPPortStats是用来取得关于交换器连接端口的统计信息。可以指定端口号这里使用OFPP_ANY目的就是取得连接端口的统计资料。
若要对统计信息进行分析,需要将msg信息转换成JSON格式进行输出,可通过以下代码进行生成
import json
# ...
self.logger.info('%s', json.dumps(ev.msg.to_jsondict(), ensure_ascii=True,
indent=3, sort_keys=True))
将打印出以下结果
{
"OFPFlowStatsReply": {
"body": [
{
"OFPFlowStats": {
"byte_count": 0,
"cookie": 0,
"duration_nsec": 680000000,
"duration_sec": 4,
"flags": 0,
"hard_timeout": 0,
"idle_timeout": 0,
"instructions": [
{
"OFPInstructionActions": {
"actions": [
{
"OFPActionOutput": {
"len": 16,
"max_len": 65535,
"port": 4294967293,
"type": 0
}
}
],
"len": 24,
"type": 4
}
}
],
"length": 80,
"match": {
"OFPMatch": {
"length": 4,
"oxm_fields": [],
"type": 1
}
},
"packet_count": 0,
"priority": 0,
"table_id": 0
}
},
{
"OFPFlowStats": {
"byte_count": 42,
"cookie": 0,
"duration_nsec": 72000000,
"duration_sec": 57,
"flags": 0,
"hard_timeout": 0,
"idle_timeout": 0,
"instructions": [
{
"OFPInstructionActions": {
"actions": [
{
"OFPActionOutput": {
"len": 16,
"max_len": 65509,
"port": 1,
"type": 0
}
}
],
"len": 24,
"type": 4
}
}
],
"length": 96,
"match": {
"OFPMatch": {
"length": 22,
"oxm_fields": [
{
"OXMTlv": {
"field": "in_port",
"mask": null,
"value": 2
}
},
{
"OXMTlv": {
"field": "eth_dst",
"mask": null,
"value": "00:00:00:00:00:01"
}
}
],
"type": 1
}
},
"packet_count": 1,
"priority": 1,
"table_id": 0
}
}
],
"flags": 0,
"type": 1
}
}
执行流量监控程序:
同样需要先执行miniet构建拓扑并打开5个xtem终端,也要设定OpenFlow版本为OpenFlow13.各个主机终端不必执行dump的端口监视命令。然后在控制器终端执行simple_montor_13.py的应用程序
ryu-manager --verbose simple_monitor_13.py
然后在host1终端向host2主机发送数据
ping -c1 10.0.0.2
封包的转发,Flow Entry的注册情况和统计资料开始发送变化
在Flow entry的统计信息中,只有进入接收端口的封包被match成功后才能计数,由两次握手可知两个流表项分别match了1,2次,故有两个封包。
Flow entry的统计信息和连接端口的统计信息不可混为一谈,Flow Entry的统计信息是记录match的entry所转发的统计信息,也就是被table-miss flow entry所触发的Packet-in消息以及Packet-out消息都没有被记录。