获取openfalcon历史数据
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#!/usr/bin/python
# --*-- coding: utf-8 --*--
# 获取用户画像集群平均qps,高峰qps,请求数,超过10ms的比例,平均响应时间 按照每天计算
import requests
import time
import json
# 登录url
login_url = 'http://192.168.10.2:8080/api/v1/user/login'
# 历史数据url
history_url = "http://192.168.10.2:8080/api/v1/graph/history"
def get_sig(url):
"""返回openfalcon用户sig标记,否则无法拿到历史数据
result_json: 返回请求数据json格式
result:json格式转化成字典
sig: 用户标签
user: 用户信息
"""
user = {
'name': "xxx",
"password": "xxx"
}
result_json = requests.post(url,data=user)
result = json.loads(result_json.text)
sig = result['sig']
return sig
class nginx_analysis(object):
def __init__(self, sig, user, url):
self.sig = sig
self.user = user
self.url = url
self.api_token = '{"name":"' + self.user + '", "sig":"' + self.sig + '"}'
self.falcon_header = {
"Apitoken": self.api_token,
"X-Forwarded-For": "127.0.0.1",
"Content-Type": "application/json",
"name": self.user,
"sig": self.sig
}
def get_nginx_data(self):
"""获取nginx数据
因为上报到openfalcon的endpoints名字不同，所以上传两次数据
payload1: 获取所有主机的响应时间和每秒请求数
payload2: 获取所有主机请求超过10ms的比例
current_time: 当前时间
history_time: 24h前的时间
"""
current_time = int(time.time())
history_time = current_time - 86400
payload1 = {
"step": 60,
"start_time": history_time,
"hostnames": [
"hostname1",
"hostname2"
],
"end_time": current_time,
"counters": [
"performance/name=nginx_request_time",
],
"consol_fun": "AVERAGE"
}
payload2 = {
"step": 60,
"start_time": history_time,
"hostnames": [
"hostname1",
"hostname2"
],
"end_time": current_time,
"counters": [
"performance/name=nginx_accepts_handled_requests_sec"
],
"consol_fun": "AVERAGE"
}
payload3 = {
"step": 60,
"start_time": history_time,
"hostnames": [
"hostname3",
"hostname4"
],
"end_time": current_time,
"counters": [
"nginx_request_percent/nginx_request_percent=10ms"
],
"consol_fun": "AVERAGE"
}
params = {
'url': self.url,
'headers': self.falcon_header,
'timeout': 30
}
# 上报数据放入数组
post_data_list = [payload1,payload2,payload3]
# 返回数据放入数组
response_data_list = []
for i in post_data_list:
params['data'] = json.dumps(i)
result_json = requests.post(**params)
result = json.loads(result_json.text)
response_data_list.append(result)
return response_data_list
def get_result(self,origin_data_list):
"""分析最终结果
data: 传递的原始数据
"""
#print len(origin_data_list)
# 获取所有节点nginx响应时间
nginx_request_time = {}
# 获取所有节点每秒请求次数
nginx_accepts_handled_requests_sec = {}
# 获取所有节点超过10ms时间
nginx_request_percent = {}
##############计算响应时间##################################
for data in origin_data_list[0]:
key = data["endpoint"]
values = data["Values"]
count = len(values)
# 每个节点的响应时间和
response_time_sum = 0
for i in values:
if i['value']:
response_time_sum += float(i['value'])
# 每个节点的平均响应时间
per_sec_time = response_time_sum/(count-1)
nginx_request_time[key] = float('%.1f' % per_sec_time)
#所有节点的平均响应时间
avg_response_time = 0
#临时响应时间和
tmp_response_sum = 0
for key,value in nginx_request_time.items():
tmp_response_sum += value
avg_response_time = tmp_response_sum/len(nginx_request_time)
avg_response_time = float('%.2f' % avg_response_time)
#print avg_response_time
################################################################
######################计算每秒请求数###########################
# 存放所有主机的请求数值
high_list = []
for data in origin_data_list[1]:
key = data["endpoint"]
values = data["Values"]
count = len(values)
# 每个节点的每秒请求数
qps_sum = 0
# 存放每个主机的请求数值
per_high_list = []
for i in values:
if i['value']:
per_high_list.append(i['value'])
qps_sum += float(i['value'])
# 每个节点的平均响应时间
high_list.append(max(per_high_list))
per_qps = qps_sum/(count-1)
nginx_accepts_handled_requests_sec[key] = float('%.2f' % per_qps)
#所有节点的平均qps
avg_qps = 0
#临时qps和
tmp_qps_sum = 0
for key,value in nginx_accepts_handled_requests_sec.items():
tmp_qps_sum += value
avg_qps = tmp_qps_sum/len(nginx_accepts_handled_requests_sec)
# 每天请求数
request_sum = int(avg_qps * 14 * 86400)
avg_qps = int(avg_qps*14)
# 高峰qps
high_qps = int(sum(high_list))
#print high_list,high_qps
#print request_sum, avg_qps,high_qps
##############################################################
#################################超过10ms的占比##############
for data in origin_data_list[2]:
key = data["endpoint"]
values = data["Values"]
count = len(values)
# 每个主机超过10ms占比和
over_percent_sum = 0
for i in values:
if i['value']:
over_percent_sum += float(i['value'])
# 每个节点超过10ms占比
per_over_percent = over_percent_sum/(count-1)
nginx_request_percent[key] = float('%.1f' % per_over_percent)
#所有节点的平均超过10ms占比
avg_over_percent = 0
#临时超过10ms占比和
tmp_over_percent_sum = 0
for key,value in nginx_request_percent.items():
tmp_over_percent_sum += value
avg_over_percent = tmp_over_percent_sum/len(nginx_request_percent)
avg_over_percent = float('%.2f' % avg_over_percent)
#print avg_over_percent
############################################################
nginx_data = [avg_response_time,request_sum, avg_qps,high_qps,avg_over_percent]
return nginx_data
def main():
sig = get_sig(login_url)
# 创建对象
nginx_analysis = Nginx_analysis(sig,'xxx',history_url)
# 获取原始数据
nginx_origin_data = nginx_analysis.get_nginx_data()
nginx_analisy = nginx_analysis.get_result(nginx_origin_data)
print nginx_analisy
if __name__ == '__main__':
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