# -*- 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', 'changefinder.scores', 'line'], 'lines': [] }, 'flags': { 'options': [None, 'ChangeFinder', 'flag', 'Flags', 'changefinder.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