预备知识点:

1、vim.PerformanceManager.MetricId()    通过counter_id获取到metric_id

2、vim.PerformanceManager.QuerySpec()    通过对象、metric_id、起始时间进行装配

3、content.perfManager.QueryPerf()    通过QuerySpec获取对象的Statistics

4、content.perfManager.perfCounter   获取所有Performance Counter相关信息

示例1: 获取ESXI主机的网络利用率

from pyVim.connect import SmartConnectNoSSL, Disconnect
from pyVmomi import vim
from datetime import timedelta
import atexit def connect_vc(host, user, pwd, port):
si = SmartConnectNoSSL(host=host, user=user, pwd=pwd, port=port) # disconnect this thing
atexit.register(Disconnect, si)
return si def build_query(content, vc_time, counter_id, obj, interval):
metric_id = vim.PerformanceManager.MetricId(counterId=counter_id, instance="")
start_time = vc_time - timedelta(minutes=(interval + 1))
end_time = vc_time - timedelta(minutes=1)
query = vim.PerformanceManager.QuerySpec(intervalId=20,
entity=obj,
metricId=[metric_id],
startTime=start_time,
endTime=end_time)
perf_results = content.perfManager.QueryPerf(querySpec=[query])
if perf_results:
return perf_results
else:
pass def print_statistics(obj, content, vc_time, interval, perf_dict, ):
stat_interval = interval * 3 # There are 3per 20s samples in each minute # Network usage (Tx/Rx)
# statNetworkTx = BuildQuery(content, vchtime, (stat_check(perf_dict, 'net.usage.maximum')), obj, interval)
# networkTx = (float(sum(statNetworkTx[0].value[0].value) * 8 / 1024) / statInt)
# statNetworkRx = BuildQuery(content, vchtime, (stat_check(perf_dict, 'net.usage.minimum')), obj, interval)
# networkRx = (float(sum(statNetworkRx[0].value[0].value) * 8 / 1024) / statInt) # Network utilization (combined transmit-rates and receive-rates) during the interval = 145
network_usage = build_query(content, vc_time, stat_check(perf_dict, 'net.usage.average'), obj, interval)
try:
print('statNetworkThroughput:%sMB' % (round((((sum(network_usage[0].value[0].value)) / 1024) / stat_interval), 2))) except TypeError:
# 关机的ESXi主机无法获取到数据
pass def stat_check(perf_dict, counter_name):
"""通过performance counter名称获取counter id"""
counter_id = perf_dict[counter_name]
return counter_id def main():
username = 'administrator@vsphere.local'
password = 'xxxxxx'
vc_ip = '172.16.65.99'
vc_port = ''
statistics_interval_time = 10 # 分钟为单位
si = connect_vc(host=vc_ip, user=username, pwd=password, port=vc_port)
content = si.RetrieveContent() # Get vCenter date and time for use as baseline when querying for counters
vc_time = si.CurrentTime() # 获取所有performance counter,并放入字典中
perf_dict = {}
perf_list = content.perfManager.perfCounter
for counter in perf_list:
counter_full = "{}.{}.{}".format(counter.groupInfo.key, counter.nameInfo.key, counter.rollupType)
perf_dict[counter_full] = counter.key  # perf_dict包含了所有的perfCounter # 获取ESXi主机对象
container_view = content.viewManager.CreateContainerView(content.rootFolder, [vim.HostSystem], True) for obj in container_view.view:
print_statistics(obj, content, vc_time, statistics_interval_time, perf_dict) # Start program
if __name__ == "__main__":
main()

示例2: 获取VM相关的performance

"""
Python program that generates various statistics for one or more virtual machines
A list of virtual machines can be provided as a comma separated list.
""" from __future__ import print_function
from pyVim.connect import SmartConnectNoSSL, Disconnect
from pyVmomi import vmodl, vim
from datetime import timedelta, datetime
import atexit def connect_vc(host, user, pwd, port):
si = SmartConnectNoSSL(host=host, user=user, pwd=pwd, port=port) # disconnect this thing
atexit.register(Disconnect, si)
return si def BuildQuery(content, vchtime, counterId, instance, vm, interval):
perfManager = content.perfManager
metricId = vim.PerformanceManager.MetricId(counterId=counterId, instance=instance)
startTime = vchtime - timedelta(minutes=(interval + 1))
endTime = vchtime - timedelta(minutes=1)
query = vim.PerformanceManager.QuerySpec(intervalId=20, entity=vm, metricId=[metricId], startTime=startTime,
endTime=endTime)
perfResults = perfManager.QueryPerf(querySpec=[query])
if perfResults:
return perfResults
else:
print('ERROR: Performance results empty. TIP: Check time drift on source and vCenter server')
print('Troubleshooting info:')
print('vCenter/host date and time: {}'.format(vchtime))
print('Start perf counter time : {}'.format(startTime))
print('End perf counter time : {}'.format(endTime))
print(query)
exit() def PrintVmInfo(vm, content, vchtime, interval, perf_dict, ):
statInt = interval * 3 # There are 3 20s samples in each minute
summary = vm.summary
disk_list = []
network_list = [] # Convert limit and reservation values from -1 to None
if vm.resourceConfig.cpuAllocation.limit == -1:
vmcpulimit = "None"
else:
vmcpulimit = "{} Mhz".format(vm.resourceConfig.cpuAllocation.limit)
if vm.resourceConfig.memoryAllocation.limit == -1:
vmmemlimit = "None"
else:
vmmemlimit = "{} MB".format(vm.resourceConfig.cpuAllocation.limit) if vm.resourceConfig.cpuAllocation.reservation == 0:
vmcpures = "None"
else:
vmcpures = "{} Mhz".format(vm.resourceConfig.cpuAllocation.reservation)
if vm.resourceConfig.memoryAllocation.reservation == 0:
vmmemres = "None"
else:
vmmemres = "{} MB".format(vm.resourceConfig.memoryAllocation.reservation) vm_hardware = vm.config.hardware
for each_vm_hardware in vm_hardware.device:
if (each_vm_hardware.key >= 2000) and (each_vm_hardware.key < 3000):
disk_list.append('{} | {:.1f}GB | Thin: {} | {}'.format(each_vm_hardware.deviceInfo.label,
each_vm_hardware.capacityInKB/1024/1024,
each_vm_hardware.backing.thinProvisioned,
each_vm_hardware.backing.fileName))
elif (each_vm_hardware.key >= 4000) and (each_vm_hardware.key < 5000):
network_list.append('{} | {} | {}'.format(each_vm_hardware.deviceInfo.label,
each_vm_hardware.deviceInfo.summary,
each_vm_hardware.macAddress)) #CPU Ready Average
statCpuReady = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'cpu.ready.summation')), "", vm, interval)
cpuReady = (float(sum(statCpuReady[0].value[0].value)) / statInt)
#CPU Usage Average % - NOTE: values are type LONG so needs divided by 100 for percentage
statCpuUsage = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'cpu.usage.average')), "", vm, interval)
cpuUsage = ((float(sum(statCpuUsage[0].value[0].value)) / statInt) / 100)
#Memory Active Average MB
statMemoryActive = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'mem.active.average')), "", vm, interval)
memoryActive = (float(sum(statMemoryActive[0].value[0].value) / 1024) / statInt)
#Memory Shared
statMemoryShared = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'mem.shared.average')), "", vm, interval)
memoryShared = (float(sum(statMemoryShared[0].value[0].value) / 1024) / statInt)
#Memory Balloon
statMemoryBalloon = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'mem.vmmemctl.average')), "", vm, interval)
memoryBalloon = (float(sum(statMemoryBalloon[0].value[0].value) / 1024) / statInt)
#Memory Swapped
statMemorySwapped = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'mem.swapped.average')), "", vm, interval)
memorySwapped = (float(sum(statMemorySwapped[0].value[0].value) / 1024) / statInt)
#Datastore Average IO
statDatastoreIoRead = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'datastore.numberReadAveraged.average')),
"*", vm, interval)
DatastoreIoRead = (float(sum(statDatastoreIoRead[0].value[0].value)) / statInt)
statDatastoreIoWrite = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'datastore.numberWriteAveraged.average')),
"*", vm, interval)
DatastoreIoWrite = (float(sum(statDatastoreIoWrite[0].value[0].value)) / statInt)
#Datastore Average Latency
statDatastoreLatRead = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'datastore.totalReadLatency.average')),
"*", vm, interval)
DatastoreLatRead = (float(sum(statDatastoreLatRead[0].value[0].value)) / statInt)
statDatastoreLatWrite = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'datastore.totalWriteLatency.average')),
"*", vm, interval)
DatastoreLatWrite = (float(sum(statDatastoreLatWrite[0].value[0].value)) / statInt) #Network usage (Tx/Rx)
statNetworkTx = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'net.transmitted.average')), "", vm, interval)
networkTx = (float(sum(statNetworkTx[0].value[0].value) * 8 / 1024) / statInt)
statNetworkRx = BuildQuery(content, vchtime, (StatCheck(perf_dict, 'net.received.average')), "", vm, interval)
networkRx = (float(sum(statNetworkRx[0].value[0].value) * 8 / 1024) / statInt) print('networkRx:', networkRx)
print('networkTx:', networkTx)
print('\nNOTE: Any VM statistics are averages of the last {} minutes\n'.format(statInt / 3))
print('Server Name :', summary.config.name)
print('Description :', summary.config.annotation)
print('Guest :', summary.config.guestFullName)
if vm.rootSnapshot:
print('Snapshot Status : Snapshots present')
else:
print('Snapshot Status : No Snapshots')
print('VM .vmx Path :', summary.config.vmPathName)
try:
print('Virtual Disks :', disk_list[0])
if len(disk_list) > 1:
disk_list.pop(0)
for each_disk in disk_list:
print(' ', each_disk)
except IndexError:
pass
print('Virtual NIC(s) :', network_list[0])
if len(network_list) > 1:
network_list.pop(0)
for each_vnic in network_list:
print(' ', each_vnic)
print('[VM] Limits : CPU: {}, Memory: {}'.format(vmcpulimit, vmmemlimit))
print('[VM] Reservations : CPU: {}, Memory: {}'.format(vmcpures, vmmemres))
print('[VM] Number of vCPUs :', summary.config.numCpu)
print('[VM] CPU Ready : Average {:.1f} %, Maximum {:.1f} %'.format((cpuReady / 20000 * 100),
((float(max(
statCpuReady[0].value[
0].value)) / 20000 * 100))))
print('[VM] CPU (%) : {:.0f} %'.format(cpuUsage))
print('[VM] Memory : {} MB ({:.1f} GB)'.format(summary.config.memorySizeMB, (float(summary.config.memorySizeMB) / 1024)))
print('[VM] Memory Shared : {:.0f} %, {:.0f} MB'.format(
((memoryShared / summary.config.memorySizeMB) * 100), memoryShared))
print('[VM] Memory Balloon : {:.0f} %, {:.0f} MB'.format(
((memoryBalloon / summary.config.memorySizeMB) * 100), memoryBalloon))
print('[VM] Memory Swapped : {:.0f} %, {:.0f} MB'.format(
((memorySwapped / summary.config.memorySizeMB) * 100), memorySwapped))
print('[VM] Memory Active : {:.0f} %, {:.0f} MB'.format(
((memoryActive / summary.config.memorySizeMB) * 100), memoryActive))
print('[VM] Datastore Average IO : Read: {:.0f} IOPS, Write: {:.0f} IOPS'.format(DatastoreIoRead,
DatastoreIoWrite))
print('[VM] Datastore Average Latency : Read: {:.0f} ms, Write: {:.0f} ms'.format(DatastoreLatRead,
DatastoreLatWrite))
print('[VM] Overall Network Usage : Transmitted {:.3f} Mbps, Received {:.3f} Mbps'.format(networkTx, networkRx))
print('[Host] Name : {}'.format(summary.runtime.host.name))
print('[Host] CPU Detail : Processor Sockets: {}, Cores per Socket {}'.format(
summary.runtime.host.summary.hardware.numCpuPkgs,
(summary.runtime.host.summary.hardware.numCpuCores / summary.runtime.host.summary.hardware.numCpuPkgs)))
print('[Host] CPU Type : {}'.format(summary.runtime.host.summary.hardware.cpuModel))
print('[Host] CPU Usage : Used: {} Mhz, Total: {} Mhz'.format(
summary.runtime.host.summary.quickStats.overallCpuUsage,
(summary.runtime.host.summary.hardware.cpuMhz * summary.runtime.host.summary.hardware.numCpuCores)))
print('[Host] Memory Usage : Used: {:.0f} GB, Total: {:.0f} GB\n'.format(
(float(summary.runtime.host.summary.quickStats.overallMemoryUsage) / 1024),
(float(summary.runtime.host.summary.hardware.memorySize) / 1024 / 1024 / 1024))) def StatCheck(perf_dict, counter_name):
counter_key = perf_dict[counter_name]
return counter_key def GetProperties(content, viewType, props, specType):
# Build a view and get basic properties for all Virtual Machines
objView = content.viewManager.CreateContainerView(content.rootFolder, viewType, True)
tSpec = vim.PropertyCollector.TraversalSpec(name='tSpecName', path='view', skip=False, type=vim.view.ContainerView)
pSpec = vim.PropertyCollector.PropertySpec(all=False, pathSet=props, type=specType)
oSpec = vim.PropertyCollector.ObjectSpec(obj=objView, selectSet=[tSpec], skip=False)
pfSpec = vim.PropertyCollector.FilterSpec(objectSet=[oSpec], propSet=[pSpec], reportMissingObjectsInResults=False)
retOptions = vim.PropertyCollector.RetrieveOptions()
totalProps = []
retProps = content.propertyCollector.RetrievePropertiesEx(specSet=[pfSpec], options=retOptions)
totalProps += retProps.objects
while retProps.token:
retProps = content.propertyCollector.ContinueRetrievePropertiesEx(token=retProps.token)
totalProps += retProps.objects
objView.Destroy()
# Turn the output in retProps into a usable dictionary of values
gpOutput = []
for eachProp in totalProps:
propDic = {}
for prop in eachProp.propSet:
propDic[prop.name] = prop.val
propDic['moref'] = eachProp.obj
gpOutput.append(propDic)
return gpOutput def main():
username = 'administrator@vsphere.local'
password = 'xxxxxx'
vc_ip = '172.16.65.99'
vc_port = ''
customization_spec_name = 'Ubuntu_Customization' si = connect_vc(host=vc_ip, user=username, pwd=password, port=vc_port) content = si.RetrieveContent()
# Get vCenter date and time for use as baseline when querying for counters
vchtime = si.CurrentTime() # Get all the performance counters
perf_dict = {}
perfList = content.perfManager.perfCounter
for counter in perfList:
counter_full = "{}.{}.{}".format(counter.groupInfo.key, counter.nameInfo.key, counter.rollupType)
perf_dict[counter_full] = counter.key retProps = GetProperties(content, [vim.VirtualMachine], ['name', 'runtime.powerState'], vim.VirtualMachine) #Find VM supplied as arg and use Managed Object Reference (moref) for the PrintVmInfo
for vm in retProps:
PrintVmInfo(vm['moref'], content, vchtime, 20, perf_dict)
break # Start program
if __name__ == "__main__":
main()

通过vSphere API获取对象Statistics的更多相关文章

  1. 利用腾讯企业邮箱开放API获取账户未读邮件数初探

    公司一直使用腾讯提供的免费企业邮箱服务,今天用管理员帐户登录后发现,原来现在腾讯的企业邮箱也开放了部分API 你可以通过开放接口实现以下功能: 数据同步 数据同步可以帮助你同步部门成员信息,你还可以创 ...

  2. JavaSE_ API常用对象 总目录(11~14)

    JavaSE学习总结第11天_开发工具 & API常用对象111.01 常见开发工具介绍11.02 Eclipse和MyEclipse的概述11.03 Eclipse的下载安装及卸载11.04 ...

  3. 在C#中调用API获取网络信息和流量

    原文 在C#中调用API获取网络信息和流量 最近一项目中要求显示网络流量,而且必须使用C#. 事实上,调用 IpHlpApi.dll 的 GetIfTable API 可以轻易获得网络信息和网络流量. ...

  4. C# 通过豆瓣网络编程API获取图书信息

    这篇文章主要是关于如何通过豆瓣API获取信息的书籍,起初,我看到了原来的想法的内容是"C# 网络编程之网页简单下载实现"中通过HttpWebResponse类下载源代码,再通过正則 ...

  5. 【转】百度API获取城市名地名(附源码)

    在做一个软件时,用到了定位功能.网上有很多关于google 的GPS定位,但网上关于google定位都没有用, 搜索下原因:(这里建议大家在中国就尽量不使用系统自带的定位) 因为Google的服务器不 ...

  6. 通过SDK和API获取阿里云RDS的监控数据

    阿里云的RDS自带的监控系统获取数据不怎么直观,想要通过API获取数据通过zabbix显示,因为网上资料缺乏和其他一些原因,获取API签名很困难,但使用阿里云的SDK可以完美避开获取签名的步骤. 阿里 ...

  7. 使用Vue.js和Axios从第三方API获取数据 — SitePoint

    更多的往往不是,建立你的JavaScript应用程序时,你会想把数据从远程源或消耗一个[ API ](https:/ /恩.维基百科.org /维基/ application_programming_ ...

  8. zabbix通过SDK和API获取阿里云RDS的监控数据

    阿里云的RDS自带的监控系统获取数据不怎么直观,想要通过API获取数据通过zabbix显示,因为网上资料缺乏和其他一些原因,获取API签名很困难,但使用阿里云的SDK可以完美避开获取签名的步骤. 阿里 ...

  9. ASP.NET Web API 路由对象介绍

    ASP.NET Web API 路由对象介绍 前言 在ASP.NET.ASP.NET MVC和ASP.NET Web API这些框架中都会发现有路由的身影,它们的原理都差不多,只不过在不同的环境下作了 ...

随机推荐

  1. appium----基本概念

    转:http://www.cnblogs.com/nbkhic/p/3803830.html Client/Server Architecture appium的核心其实是一个暴露了一系列REST A ...

  2. Ubuntu安装sublime test 3 (Build 3126)

    Ubuntu下 Sublime Text 3 (Build 3143) 存在一些bug........ 满心欢喜地更新后, 又默默换回Build 3126 1. 安装 sudo apt-get upd ...

  3. 【Hadoop基础教程】3、Hadoop之伪分布式环境搭建(转)

    伪分布式模式即单节点集群模式,所有的守护进程都运行在同一台机器上.这种模式下增加了代码调试功能,可以查看内存.HDFS文件系统的输入/输出,以及与其他守护进程交互.以hadoop用户远程登录K-Mas ...

  4. IMSDroid问题集

    1.IMSDroid切换摄像头后的接收方横屏显示.事实上非常多种情况下都会突然发现就横屏了.解决的方法就是切换摄像头时同一时候切换横竖屏显示 2.IMSDroid掉音问题:IMSDroid通话几分钟后 ...

  5. Atitit.5gl 第五代语言编程语言 PROLOG教程  人工智能语言的标准 与实现

    Atitit.5gl 第五代语言编程语言 PROLOG教程  人工智能语言的标准 与实现 1. 第五代语言就是自然语言又被称为知识库语言或人工智能语言,1 2. 人工智能语言特点2 2.1. 试探法2 ...

  6. OpenLayers加载天地图

    openlayer 是基于JavaScript的webGIS库 ,通过openlayer可以很容易的调用地图,并做相应的操作. 在head中载入openlayer的js文件: <link rel ...

  7. JAVA版SqlHelper

    //JAVA版SqlHelper package com.test.Dao; import java.sql.Connection; import java.sql.DriverManager; im ...

  8. oracle中直方图的使用

    本文从不绑定变量和绑定变量两种情况讨论直方图的作用 一.不绑定变量 SQL> create table test(name varchar2(10));表已创建.SQL> insert i ...

  9. ASP.NET动态网站制作(22)-- ADO.NET(1)

    前言:这节课开始真正地学习WEB开发,ADO.NET就是一组允许.NET开发人员使用标准的.机构化的,甚至无连接的方式与数据交互的技术.所属的类库为:System.Data.dll. 内容: 1.AD ...

  10. Android Studio报Error:Execution failed for task &#39;:Companion:preDexDebug&#39;.

    错误例如以下: Error:Execution failed for task ':Companion:preDexDebug'. > com.android.ide.common.proces ...