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# -*- coding: utf-8 -*-
# Description: changefinder netdata python.d module
# Author: andrewm4894
# SPDX-License-Identifier: GPL-3.0-or-later
from json import loads
import re
from bases.FrameworkServices.UrlService import UrlService
import numpy as np
import changefinder
from scipy.stats import percentileofscore
update_every = 5
disabled_by_default = True
ORDER = [
'scores',
'flags'
]
CHARTS = {
'scores': {
'options': [None, 'ChangeFinder', 'score', 'Scores', 'scores', 'line'],
'lines': []
},
'flags': {
'options': [None, 'ChangeFinder', 'flag', 'Flags', 'flags', 'stacked'],
'lines': []
}
}
DEFAULT_PROTOCOL = 'http'
DEFAULT_HOST = '127.0.0.1:19999'
DEFAULT_CHARTS_REGEX = 'system.*'
DEFAULT_MODE = 'per_chart'
DEFAULT_CF_R = 0.5
DEFAULT_CF_ORDER = 1
DEFAULT_CF_SMOOTH = 15
DEFAULT_CF_DIFF = False
DEFAULT_CF_THRESHOLD = 99
DEFAULT_N_SCORE_SAMPLES = 14400
DEFAULT_SHOW_SCORES = False
class Service(UrlService):
def __init__(self, configuration=None, name=None):
UrlService.__init__(self, configuration=configuration, name=name)
self.order = ORDER
self.definitions = CHARTS
self.protocol = self.configuration.get('protocol', DEFAULT_PROTOCOL)
self.host = self.configuration.get('host', DEFAULT_HOST)
self.url = '{}://{}/api/v1/allmetrics?format=json'.format(self.protocol, self.host)
self.charts_regex = re.compile(self.configuration.get('charts_regex', DEFAULT_CHARTS_REGEX))
self.charts_to_exclude = self.configuration.get('charts_to_exclude', '').split(',')
self.mode = self.configuration.get('mode', DEFAULT_MODE)
self.n_score_samples = int(self.configuration.get('n_score_samples', DEFAULT_N_SCORE_SAMPLES))
self.show_scores = int(self.configuration.get('show_scores', DEFAULT_SHOW_SCORES))
self.cf_r = float(self.configuration.get('cf_r', DEFAULT_CF_R))
self.cf_order = int(self.configuration.get('cf_order', DEFAULT_CF_ORDER))
self.cf_smooth = int(self.configuration.get('cf_smooth', DEFAULT_CF_SMOOTH))
self.cf_diff = bool(self.configuration.get('cf_diff', DEFAULT_CF_DIFF))
self.cf_threshold = float(self.configuration.get('cf_threshold', DEFAULT_CF_THRESHOLD))
self.collected_dims = {'scores': set(), 'flags': set()}
self.models = {}
self.x_latest = {}
self.scores_latest = {}
self.scores_samples = {}
def get_score(self, x, model):
"""Update the score for the model based on most recent data, flag if it's percentile passes self.cf_threshold.
"""
# get score
if model not in self.models:
# initialise empty model if needed
self.models[model] = changefinder.ChangeFinder(r=self.cf_r, order=self.cf_order, smooth=self.cf_smooth)
# if the update for this step fails then just fallback to last known score
try:
score = self.models[model].update(x)
self.scores_latest[model] = score
except Exception as _:
score = self.scores_latest.get(model, 0)
score = 0 if np.isnan(score) else score
# update sample scores used to calculate percentiles
if model in self.scores_samples:
self.scores_samples[model].append(score)
else:
self.scores_samples[model] = [score]
self.scores_samples[model] = self.scores_samples[model][-self.n_score_samples:]
# convert score to percentile
score = percentileofscore(self.scores_samples[model], score)
# flag based on score percentile
flag = 1 if score >= self.cf_threshold else 0
return score, flag
def validate_charts(self, chart, data, algorithm='absolute', multiplier=1, divisor=1):
"""If dimension not in chart then add it.
"""
if not self.charts:
return
for dim in data:
if dim not in self.collected_dims[chart]:
self.collected_dims[chart].add(dim)
self.charts[chart].add_dimension([dim, dim, algorithm, multiplier, divisor])
for dim in list(self.collected_dims[chart]):
if dim not in data:
self.collected_dims[chart].remove(dim)
self.charts[chart].del_dimension(dim, hide=False)
def diff(self, x, model):
"""Take difference of data.
"""
x_diff = x - self.x_latest.get(model, 0)
self.x_latest[model] = x
x = x_diff
return x
def _get_data(self):
# pull data from self.url
raw_data = self._get_raw_data()
if raw_data is None:
return None
raw_data = loads(raw_data)
# filter to just the data for the charts specified
charts_in_scope = list(filter(self.charts_regex.match, raw_data.keys()))
charts_in_scope = [c for c in charts_in_scope if c not in self.charts_to_exclude]
data_score = {}
data_flag = {}
# process each chart
for chart in charts_in_scope:
if self.mode == 'per_chart':
# average dims on chart and run changefinder on that average
x = [raw_data[chart]['dimensions'][dim]['value'] for dim in raw_data[chart]['dimensions']]
x = [x for x in x if x is not None]
if len(x) > 0:
x = sum(x) / len(x)
x = self.diff(x, chart) if self.cf_diff else x
score, flag = self.get_score(x, chart)
if self.show_scores:
data_score['{}_score'.format(chart)] = score * 100
data_flag[chart] = flag
else:
# run changefinder on each individual dim
for dim in raw_data[chart]['dimensions']:
chart_dim = '{}|{}'.format(chart, dim)
x = raw_data[chart]['dimensions'][dim]['value']
x = x if x else 0
x = self.diff(x, chart_dim) if self.cf_diff else x
score, flag = self.get_score(x, chart_dim)
if self.show_scores:
data_score['{}_score'.format(chart_dim)] = score * 100
data_flag[chart_dim] = flag
self.validate_charts('flags', data_flag)
if self.show_scores & len(data_score) > 0:
data_score['average_score'] = sum(data_score.values()) / len(data_score)
self.validate_charts('scores', data_score, divisor=100)
data = {**data_score, **data_flag}
return data
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