// SPDX-License-Identifier: GPL-3.0-or-later #include "ADCharts.h" #include "Config.h" void ml::updateDimensionsChart(RRDHOST *RH, collected_number NumTrainedDimensions, collected_number NumNormalDimensions, collected_number NumAnomalousDimensions) { static thread_local RRDSET *RS = nullptr; static thread_local RRDDIM *NumTotalDimensionsRD = nullptr; static thread_local RRDDIM *NumTrainedDimensionsRD = nullptr; static thread_local RRDDIM *NumNormalDimensionsRD = nullptr; static thread_local RRDDIM *NumAnomalousDimensionsRD = nullptr; if (!RS) { std::stringstream IdSS, NameSS; IdSS << "dimensions_on_" << localhost->machine_guid; NameSS << "dimensions_on_" << localhost->hostname; RS = rrdset_create( RH, "anomaly_detection", // type IdSS.str().c_str(), // id NameSS.str().c_str(), // name "dimensions", // family "anomaly_detection.dimensions", // ctx "Anomaly detection dimensions", // title "dimensions", // units "netdata", // plugin "ml", // module 39183, // priority RH->rrd_update_every, // update_every RRDSET_TYPE_LINE // chart_type ); rrdset_flag_set(RS, RRDSET_FLAG_ANOMALY_DETECTION); NumTotalDimensionsRD = rrddim_add(RS, "total", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); NumTrainedDimensionsRD = rrddim_add(RS, "trained", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); NumNormalDimensionsRD = rrddim_add(RS, "normal", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); NumAnomalousDimensionsRD = rrddim_add(RS, "anomalous", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); } rrddim_set_by_pointer(RS, NumTotalDimensionsRD, NumNormalDimensions + NumAnomalousDimensions); rrddim_set_by_pointer(RS, NumTrainedDimensionsRD, NumTrainedDimensions); rrddim_set_by_pointer(RS, NumNormalDimensionsRD, NumNormalDimensions); rrddim_set_by_pointer(RS, NumAnomalousDimensionsRD, NumAnomalousDimensions); rrdset_done(RS); } void ml::updateHostAndDetectionRateCharts(RRDHOST *RH, collected_number AnomalyRate) { static thread_local RRDSET *HostRateRS = nullptr; static thread_local RRDDIM *AnomalyRateRD = nullptr; if (!HostRateRS) { std::stringstream IdSS, NameSS; IdSS << "anomaly_rate_on_" << localhost->machine_guid; NameSS << "anomaly_rate_on_" << localhost->hostname; HostRateRS = rrdset_create( RH, "anomaly_detection", // type IdSS.str().c_str(), // id NameSS.str().c_str(), // name "anomaly_rate", // family "anomaly_detection.anomaly_rate", // ctx "Percentage of anomalous dimensions", // title "percentage", // units "netdata", // plugin "ml", // module 39184, // priority RH->rrd_update_every, // update_every RRDSET_TYPE_LINE // chart_type ); rrdset_flag_set(HostRateRS, RRDSET_FLAG_ANOMALY_DETECTION); AnomalyRateRD = rrddim_add(HostRateRS, "anomaly_rate", NULL, 1, 100, RRD_ALGORITHM_ABSOLUTE); } rrddim_set_by_pointer(HostRateRS, AnomalyRateRD, AnomalyRate); rrdset_done(HostRateRS); static thread_local RRDSET *AnomalyDetectionRS = nullptr; static thread_local RRDDIM *AboveThresholdRD = nullptr; static thread_local RRDDIM *NewAnomalyEventRD = nullptr; if (!AnomalyDetectionRS) { std::stringstream IdSS, NameSS; IdSS << "anomaly_detection_on_" << localhost->machine_guid; NameSS << "anomaly_detection_on_" << localhost->hostname; AnomalyDetectionRS = rrdset_create( RH, "anomaly_detection", // type IdSS.str().c_str(), // id NameSS.str().c_str(), // name "anomaly_detection", // family "anomaly_detection.detector_events", // ctx "Anomaly detection events", // title "percentage", // units "netdata", // plugin "ml", // module 39185, // priority RH->rrd_update_every, // update_every RRDSET_TYPE_LINE // chart_type ); rrdset_flag_set(AnomalyDetectionRS, RRDSET_FLAG_ANOMALY_DETECTION); AboveThresholdRD = rrddim_add(AnomalyDetectionRS, "above_threshold", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); NewAnomalyEventRD = rrddim_add(AnomalyDetectionRS, "new_anomaly_event", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); } /* * Compute the values of the dimensions based on the host rate chart */ ONEWAYALLOC *OWA = onewayalloc_create(0); time_t Now = now_realtime_sec(); time_t Before = Now - RH->rrd_update_every; time_t After = Before - Cfg.AnomalyDetectionQueryDuration; RRDR_OPTIONS Options = static_cast(0x00000000); RRDR *R = rrd2rrdr_legacy( OWA, HostRateRS, 1 /* points wanted */, After, Before, Cfg.AnomalyDetectionGroupingMethod, 0 /* resampling time */, Options, "anomaly_rate", NULL /* group options */, 0, /* timeout */ 0, /* tier */ QUERY_SOURCE_ML ); if(R) { assert(R->d == 1 && R->n == 1 && R->rows == 1); static thread_local bool PrevAboveThreshold = false; bool AboveThreshold = R->v[0] >= Cfg.HostAnomalyRateThreshold; bool NewAnomalyEvent = AboveThreshold && !PrevAboveThreshold; PrevAboveThreshold = AboveThreshold; rrddim_set_by_pointer(AnomalyDetectionRS, AboveThresholdRD, AboveThreshold); rrddim_set_by_pointer(AnomalyDetectionRS, NewAnomalyEventRD, NewAnomalyEvent); rrdset_done(AnomalyDetectionRS); rrdr_free(OWA, R); } onewayalloc_destroy(OWA); } void ml::updateDetectionChart(RRDHOST *RH) { static thread_local RRDSET *RS = nullptr; static thread_local RRDDIM *UserRD, *SystemRD = nullptr; if (!RS) { std::stringstream IdSS, NameSS; IdSS << "prediction_stats_" << RH->machine_guid; NameSS << "prediction_stats_for_" << RH->hostname; RS = rrdset_create_localhost( "netdata", // type IdSS.str().c_str(), // id NameSS.str().c_str(), // name "ml", // family "netdata.prediction_stats", // ctx "Prediction thread CPU usage", // title "milliseconds/s", // units "netdata", // plugin "ml", // module 136000, // priority RH->rrd_update_every, // update_every RRDSET_TYPE_STACKED // chart_type ); UserRD = rrddim_add(RS, "user", NULL, 1, 1000, RRD_ALGORITHM_INCREMENTAL); SystemRD = rrddim_add(RS, "system", NULL, 1, 1000, RRD_ALGORITHM_INCREMENTAL); } struct rusage TRU; getrusage(RUSAGE_THREAD, &TRU); rrddim_set_by_pointer(RS, UserRD, TRU.ru_utime.tv_sec * 1000000ULL + TRU.ru_utime.tv_usec); rrddim_set_by_pointer(RS, SystemRD, TRU.ru_stime.tv_sec * 1000000ULL + TRU.ru_stime.tv_usec); rrdset_done(RS); } void ml::updateTrainingChart(RRDHOST *RH, struct rusage *TRU) { static thread_local RRDSET *RS = nullptr; static thread_local RRDDIM *UserRD = nullptr; static thread_local RRDDIM *SystemRD = nullptr; if (!RS) { std::stringstream IdSS, NameSS; IdSS << "training_stats_" << RH->machine_guid; NameSS << "training_stats_for_" << RH->hostname; RS = rrdset_create_localhost( "netdata", // type IdSS.str().c_str(), // id NameSS.str().c_str(), // name "ml", // family "netdata.training_stats", // ctx "Training thread CPU usage", // title "milliseconds/s", // units "netdata", // plugin "ml", // module 136001, // priority RH->rrd_update_every, // update_every RRDSET_TYPE_STACKED // chart_type ); UserRD = rrddim_add(RS, "user", NULL, 1, 1000, RRD_ALGORITHM_INCREMENTAL); SystemRD = rrddim_add(RS, "system", NULL, 1, 1000, RRD_ALGORITHM_INCREMENTAL); } rrddim_set_by_pointer(RS, UserRD, TRU->ru_utime.tv_sec * 1000000ULL + TRU->ru_utime.tv_usec); rrddim_set_by_pointer(RS, SystemRD, TRU->ru_stime.tv_sec * 1000000ULL + TRU->ru_stime.tv_usec); rrdset_done(RS); }