import csv
from itertools import product
import os
import re
import datetime
from os.path import dirname
from log import Logger
import logging
from yaml import FlowMappingEndToken
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import statistics
import numpy as np
log_path = dirname(__file__) + '/log/' + str(datetime.datetime.now().strftime(
'%Y-%m-%d')) + '_nezha.log'
logger = Logger(log_path, logging.DEBUG, __name__).getlog()
metric_threshold_dir = "metric_threshold"
def get_svc(path):
svc = path.rsplit('-', 1)[0]
svc = svc.rsplit('-', 1)[0]
return svc
def generate_threshold(metric_dir, trace_file):
"""
fun generate_threshold: calculte mean and std for each metric of each servie
write ruslt to metric_threshold_dir/service.csv
:parameter
metric_dir - metric dir in construction phase
"""
metric_map = {}
path_list = os.listdir(metric_dir)
for path in path_list:
if "metric" in path:
svc = path.rsplit('-', 1)[0]
svc = svc.rsplit('-', 1)[0]
if svc in metric_map:
metric_map[svc].append(os.path.join(metric_dir, path))
else:
metric_map[svc] = [os.path.join(metric_dir, path)]
for svc in metric_map:
frames = []
# get pod name
for path in path_list:
if svc in path:
pod_name = path.split("_")[0]
print(pod_name)
network_mean, network_std = get_netwrok_metric(
trace_file=trace_file, pod_name=pod_name)
break
metric_threshold_file = metric_threshold_dir + "/" + svc + ".csv"
for path in metric_map[svc]:
frames.append(pd.read_csv(path, index_col=False, usecols=[
'CpuUsageRate(%)', 'MemoryUsageRate(%)', 'SyscallRead', 'SyscallWrite']))
# concat pods of the same service
result = pd.concat(frames)
with open(metric_threshold_file, 'w', newline='') as f:
writer = csv.writer(f)
header = ['CpuUsageRate(%)', 'MemoryUsageRate(%)', 'SyscallRead',
'SyscallWrite', 'NetworkP90(ms)']
writer.writerow(header)
mean_list = []
std_list = []
for metric in header:
if metric == 'NetworkP90(ms)':
continue
mean_list.append(np.mean(result[metric]))
std_list.append(np.std(result[metric]))
mean_list.append(network_mean)
std_list.append(network_std)
writer.writerow(mean_list)
writer.writerow(std_list)
def get_netwrok_metric(trace_file, pod_name):
"""
func get_netwrok_metric: use trace data to get netwrok metric
:parameter
time - to regex timestamp e.g, "2022-04-18 13:00"
data_dir
pod_name
:return
p90 netwrok latency
"""
latency_list = []
if "front" in pod_name:
# front end dose not calculate netwrok latency
return 10, 10
pod_reader = pd.read_csv(
trace_file, index_col='PodName', usecols=['TraceID', 'SpanID', 'ParentID', 'PodName', 'EndTimeUnixNano'])
parent_span_reader = pd.read_csv(
trace_file, index_col='SpanID', usecols=['TraceID', 'SpanID', 'ParentID', 'PodName', 'EndTimeUnixNano'])
try:
pod_spans = pod_reader.loc[[pod_name], [
'SpanID', 'ParentID', 'PodName', 'EndTimeUnixNano']]
except:
service = pod_name.rsplit('-', 1)[0]
service = service.rsplit('-', 1)[0]
csv_file = dirname(__file__) + "/metric_threshold/" + service + ".csv"
pod_reader = pd.read_csv(csv_file, usecols=['NetworkP90(ms)'])
# print("pod", pod_name, " not found in trace, return default ",
# float(pod_reader.iloc[0]))
return float(pod_reader.iloc[0]), 0
if len(pod_spans['SpanID']) > 0:
# process span independentlt and order by timestamp
for span_index in range(len(pod_spans['SpanID'])):
# span event
parent_id = pod_spans['ParentID'].iloc[span_index]
pod_start_time = int(
pod_spans['EndTimeUnixNano'].iloc[span_index])
try:
parent_pod_span = parent_span_reader.loc[[
parent_id], ['PodName', 'EndTimeUnixNano']]
if len(parent_pod_span) > 0:
for parent_span_index in range(len(parent_pod_span['PodName'])):
parent_pod_name = parent_pod_span['PodName'].iloc[parent_span_index]
parent_end_time = int(
parent_pod_span['EndTimeUnixNano'].iloc[parent_span_index])
if str(parent_pod_name) != str(pod_name):
latency = (parent_end_time - pod_start_time) / \
1000000 # convert to microsecond
# if "contacts-service" in pod_name:
# logger.info("%s, %s, %s, %s, %s" % (
# pod_name, pod_spans['SpanID'].iloc[span_index], parent_pod_name, pod_spans['ParentID'].iloc[span_index], latency))
latency_list.append(latency)
except:
pass
# logger.info("%s latency is %s" %(pod_name, np.percentile(latency_list, 90)))
if len(latency_list) > 2:
return np.percentile(latency_list, 90), statistics.stdev(latency_list)
else:
return 10, 10
def determine_alarm(pod, metric_type, metric_value, std_num, ns):
"""
fun determine_alarm: determin whether violate 3-sgima
:parameter
pod - podname to find corrsponding metric threshold file
metric_type - find correspding column
metric_vault - compare with the history mean and std
std_num - constrol std_num * std
:return
true - alarm
false - no alarm
"""
path_list = os.listdir(metric_threshold_dir)
if metric_type == "CpuUsageRate(%)" or metric_type == 'MemoryUsageRate(%)':
if metric_value > 80:
return True
else:
if ns == "hipster":
# for hipster
if metric_value > 200:
return True
elif ns == "ts":
# for ts
if metric_value > 300:
return True
return False
# for path in path_list:
# if re.search(path.split('.')[0], pod):
# hisory_metric = pd.read_csv(os.path.join(
# metric_threshold_dir, path), index_col=False, usecols=[metric_type])
# if metric_value > hisory_metric[metric_type][0] + std_num * hisory_metric[metric_type][1]:
# return True
# # elif metric_value < hisory_metric[metric_type][0] - std_num * hisory_metric[metric_type][1]:
# # return True
# else:
# return False
def generate_alarm(metric_list, ns, std_num=6):
"""
func generate_alarm: generate alram of each pod at current miniute
:parameter
metric_list - metric list from get_metric_with_time
:return
alarm_list, e.g., [{'pod': 'cartservice-579f59597d-n69b4', 'alarm': [{'metric_type': 'CpuUsageRate(%)', 'alarm_flag': True}]}]
[{
pod:
alarm: [
{
metric_type: CpuUsageRate(%)
alarm_flag: True
}
]
}]
"""
alarm_list = []
for pod_metric in metric_list:
alarm = {}
for i in range(len(pod_metric['metrics'])):
alarm_flag = determine_alarm(pod=pod_metric["pod"], metric_type=pod_metric['metrics'][i]["metric_type"],
metric_value=pod_metric['metrics'][i]["metric_value"], std_num=std_num, ns=ns)
if alarm_flag:
# if exist alarm_flag equal to true, create map
if "pod" not in alarm:
alarm = {"pod": pod_metric["pod"], "alarm": []}
alarm['alarm'].append(
{"metric_type": pod_metric['metrics'][i]["metric_type"], "alarm_flag": alarm_flag})
if "pod" in alarm:
alarm_list.append(alarm)
return alarm_list
def get_metric_with_time(time, base_dir):
"""
func get_metric_with_time: get metric list at determined miniute
:parameter
time - to regex timestamp e.g, "2022-04-18 13:00"
product_metric_dir
:return
target_list - traget metrics
[
{
pod:
metrics: [
{
"metric_type":
"metric_value":
}
]
}
]
"""
date = time.split(' ')[0]
hour_min = time.split(' ')[1]
hour = hour_min.split(':')[0]
min = hour_min.split(':')[1]
trace_file = base_dir + "/" + date + "/trace/" + hour + "_" + min + "_trace.csv"
metric_dir = base_dir + "/" + date + "/metric/"
path_list = os.listdir(metric_dir)
# metric_list = ['CpuUsageRate(%)', 'MemoryUsageRate(%)', 'SyscallRead',
# 'SyscallWrite']
metric_list = ['CpuUsageRate(%)', 'MemoryUsageRate(%)']
target_list = []
for path in path_list:
if "metric" in path:
metrics = pd.read_csv(os.path.join(metric_dir, path))
# metrics = pd.read_csv(os.path.join(product_metric_dir, path), index_col=False, usecols=['TimeStamp', 'PodName', 'CpuUsageRate(%)', 'MemoryUsageRate(%)', 'SyscallRead', 'SyscallWrite', 'PodServerLatencyP90(s)', 'PodClientLatencyP90(s)'])
for index in range(len(metrics['Time'])):
# regex timestamp
if re.search(time, metrics['Time'][index]):
target_metric = {
"pod": metrics['PodName'][index], "metrics": []}
for metric in metric_list:
target_metric["metrics"].append({
"metric_type": metric, "metric_value": metrics[metric][index]})
network_p90, _ = get_netwrok_metric(
trace_file=trace_file, pod_name=metrics['PodName'][index])
target_metric["metrics"].append(
{"metric_type": "NetworkP90(ms)", "metric_value": network_p90})
target_list.append(target_metric)
# print(target_list)
return target_list