Add annotations.
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#!/usr/bin/python3
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'''
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Monitor for Docklet
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Description:Monitor system for docklet will collect data on resources usages and status of vnode
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and phyiscal machines. And master can fetch these data and then show them on the web page.
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Besides, Monitor will also bill the vnodes according to their resources usage amount.
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Design:Monitor mainly consists of three parts: Collectors, Master_Collector and Fetchers.
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1.Collectors will collect data every two seconds on each worker. And 'Container_Collector' will
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collect data of containers(vnodes), while 'Collector' will collect data of physical machines.
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2.'Master_Collector' only runs on Master. It fetches the data on workers every two seconds by rpc
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and stores them in the memory of Master.
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3.Fetchers are classes that Master will use them to fetch specific data in the memory and then show
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them on the web. 'Container_Fetcher' is the class to fetch the containers data in 'monitor_vnodes',
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while 'Fetcher' is the class to fetch the data of physical machines in 'monitor_hosts'.
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'''
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import subprocess,re,os,etcdlib,psutil,math,sys
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import time,threading,json,traceback,platform
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import env
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@ -10,30 +27,69 @@ from log import logger
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from httplib2 import Http
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from urllib.parse import urlencode
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a_cpu = 500
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b_mem = 1000000
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c_disk = 4000
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# billing parameters
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a_cpu = 500 # seconds
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b_mem = 1000000 # MB
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c_disk = 4000 # MB
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monitor_hosts = {}
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# major dict to store the monitoring data
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# only use on Master
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# monitor_hosts: use workers' ip addresses as first key.
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# second key: cpuinfo,diskinfo,meminfo,osinfo,cpuconfig,running,containers,containerslist
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# 1.cpuinfo stores the cpu usages data, and it has keys: user,system,idle,iowait
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# 2.diskinfo stores the disks usages data, and it has keys: device,mountpoint,total,used,free,percent
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# 3.meminfo stores the memory usages data, and it has keys: total,used,free,buffers,cached,percent
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# 4.osinfo stores the information of operating system,
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# and it has keys: platform,system,node,release,version,machine,processor
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# 5.cpuconfig stores the information of processors, and it is a list, each element of list is a dict
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# which stores the information of a processor, each element has key: processor,model name,
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# core id, cpu MHz, cache size, physical id.
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# 6.running indicates the status of worker,and it has two values: True, False.
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# 7.containers store the amount of containers on the worker.
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# 8.containers store a list which consists of the names of containers on the worker.
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moitor_hosts = {}
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# monitor_vnodes: use the names of vnodes(containers) as first key.
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# second key: cpu_use,mem_use,disk_use,basic_info,quota
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# 1.cpu_use has keys: val,unit,hostpercent
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# 2.mem_use has keys: val,unit,usedp
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# 3.disk_use has keys: device,mountpoint,total,used,free,percent
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# 4.basic_info has keys: Name,State,PID,IP,RunningTime,billing,billing_this_hour
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# 5.quota has keys: cpu,memeory
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monitor_vnodes = {}
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# major dict to store the monitoring data on Worker
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# only use on Worker
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# workerinfo: only store the data collected on current Worker,
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# has the first keys same as the second keys in monitor_hosts.
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workerinfo = {}
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# workercinfo: only store the data collected on current Worker,
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# has the first keys same as the second keys in monitor_vnodes.
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workercinfo = {}
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# only use on worker
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containerpids = []
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pid2name = {}
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G_masterip = ""
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# only use on worker
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laststopcpuval = {}
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laststopruntime = {}
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lastbillingtime = {}
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increment = {}
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lastbillingtime = {}
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# increment has keys: lastcputime,memincrement.
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# record the cpu val at last billing time and accumulate the memory usages during this billing hour.
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increment = {}
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# send http request to master
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def request_master(url,data):
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global G_masterip
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header = {'Content-Type':'application/x-www-form-urlencoded'}
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http = Http()
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[resp,content] = http.request("http://"+G_masterip+url,"POST",urlencode(data),headers = header)
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logger.info("response from master:"+content.decode('utf-8'))
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# The class is to collect data of containers on each worker
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class Container_Collector(threading.Thread):
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def __init__(self,test=False):
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global workercinfo
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threading.Thread.__init__(self)
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self.thread_stop = False
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self.interval = 2
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self.billingtime = 3600
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self.interval = 2
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self.billingtime = 3600 # billing interval
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self.test = test
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self.cpu_last = {}
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self.cpu_quota = {}
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self.mem_quota = {}
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self.cores_num = int(subprocess.getoutput("grep processor /proc/cpuinfo | wc -l"))
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containers = self.list_container()
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for container in containers:
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for container in containers: # recovery
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if not container == '':
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try:
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vnode = VNode.query.get(container)
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laststopcpuval[container] = 0
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laststopruntime[container] = 0
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return
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# list containers on this worker
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def list_container(self):
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output = subprocess.check_output(["sudo lxc-ls"],shell=True)
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output = output.decode('utf-8')
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containers = re.split('\s+',output)
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return containers
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# get running time of a process, return seconds
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def get_proc_etime(self,pid):
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fmt = subprocess.getoutput("ps -A -opid,etime | grep '^ *%d ' | awk '{print $NF}'" % pid).strip()
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if fmt == '':
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seconds = int(parts[1])
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return ((days * 24 + hours) * 60 + minutes) * 60 + seconds
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# compute the billing val this running hour
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# if isreal is True, it will also make users' beans decrease to pay for the bill.
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@classmethod
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def billing_increment(cls,vnode_name,isreal=True):
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global increment
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