diff options
Diffstat (limited to 'ml/ADCharts.cc')
| -rw-r--r-- | ml/ADCharts.cc | 518 |
1 files changed, 0 insertions, 518 deletions
diff --git a/ml/ADCharts.cc b/ml/ADCharts.cc deleted file mode 100644 index cbb13f5d..00000000 --- a/ml/ADCharts.cc +++ /dev/null @@ -1,518 +0,0 @@ -// SPDX-License-Identifier: GPL-3.0-or-later - -#include "ADCharts.h" -#include "Config.h" - -void ml::updateDimensionsChart(RRDHOST *RH, const MachineLearningStats &MLS) { - /* - * Machine learning status - */ - { - static thread_local RRDSET *MachineLearningStatusRS = nullptr; - - static thread_local RRDDIM *Enabled = nullptr; - static thread_local RRDDIM *DisabledUE = nullptr; - static thread_local RRDDIM *DisabledSP = nullptr; - - if (!MachineLearningStatusRS) { - std::stringstream IdSS, NameSS; - - IdSS << "machine_learning_status_on_" << localhost->machine_guid; - NameSS << "machine_learning_status_on_" << rrdhost_hostname(localhost); - - MachineLearningStatusRS = rrdset_create( - RH, - "netdata", // type - IdSS.str().c_str(), // id - NameSS.str().c_str(), // name - NETDATA_ML_CHART_FAMILY, // family - "netdata.machine_learning_status", // ctx - "Machine learning status", // title - "dimensions", // units - NETDATA_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_TRAINING, // module - NETDATA_ML_CHART_PRIO_MACHINE_LEARNING_STATUS, // priority - RH->rrd_update_every, // update_every - RRDSET_TYPE_LINE // chart_type - ); - rrdset_flag_set(MachineLearningStatusRS , RRDSET_FLAG_ANOMALY_DETECTION); - - Enabled = rrddim_add(MachineLearningStatusRS, "enabled", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - DisabledUE = rrddim_add(MachineLearningStatusRS, "disabled-ue", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - DisabledSP = rrddim_add(MachineLearningStatusRS, "disabled-sp", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - } - - rrddim_set_by_pointer(MachineLearningStatusRS, Enabled, MLS.NumMachineLearningStatusEnabled); - rrddim_set_by_pointer(MachineLearningStatusRS, DisabledUE, MLS.NumMachineLearningStatusDisabledUE); - rrddim_set_by_pointer(MachineLearningStatusRS, DisabledSP, MLS.NumMachineLearningStatusDisabledSP); - - rrdset_done(MachineLearningStatusRS); - } - - /* - * Metric type - */ - { - static thread_local RRDSET *MetricTypesRS = nullptr; - - static thread_local RRDDIM *Constant = nullptr; - static thread_local RRDDIM *Variable = nullptr; - - if (!MetricTypesRS) { - std::stringstream IdSS, NameSS; - - IdSS << "metric_types_on_" << localhost->machine_guid; - NameSS << "metric_types_on_" << rrdhost_hostname(localhost); - - MetricTypesRS = rrdset_create( - RH, - "netdata", // type - IdSS.str().c_str(), // id - NameSS.str().c_str(), // name - NETDATA_ML_CHART_FAMILY, // family - "netdata.metric_types", // ctx - "Dimensions by metric type", // title - "dimensions", // units - NETDATA_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_TRAINING, // module - NETDATA_ML_CHART_PRIO_METRIC_TYPES, // priority - RH->rrd_update_every, // update_every - RRDSET_TYPE_LINE // chart_type - ); - rrdset_flag_set(MetricTypesRS, RRDSET_FLAG_ANOMALY_DETECTION); - - Constant = rrddim_add(MetricTypesRS, "constant", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - Variable = rrddim_add(MetricTypesRS, "variable", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - } - - rrddim_set_by_pointer(MetricTypesRS, Constant, MLS.NumMetricTypeConstant); - rrddim_set_by_pointer(MetricTypesRS, Variable, MLS.NumMetricTypeVariable); - - rrdset_done(MetricTypesRS); - } - - /* - * Training status - */ - { - static thread_local RRDSET *TrainingStatusRS = nullptr; - - static thread_local RRDDIM *Untrained = nullptr; - static thread_local RRDDIM *PendingWithoutModel = nullptr; - static thread_local RRDDIM *Trained = nullptr; - static thread_local RRDDIM *PendingWithModel = nullptr; - - if (!TrainingStatusRS) { - std::stringstream IdSS, NameSS; - - IdSS << "training_status_on_" << localhost->machine_guid; - NameSS << "training_status_on_" << rrdhost_hostname(localhost); - - TrainingStatusRS = rrdset_create( - RH, - "netdata", // type - IdSS.str().c_str(), // id - NameSS.str().c_str(), // name - NETDATA_ML_CHART_FAMILY, // family - "netdata.training_status", // ctx - "Training status of dimensions", // title - "dimensions", // units - NETDATA_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_TRAINING, // module - NETDATA_ML_CHART_PRIO_TRAINING_STATUS, // priority - RH->rrd_update_every, // update_every - RRDSET_TYPE_LINE // chart_type - ); - - rrdset_flag_set(TrainingStatusRS, RRDSET_FLAG_ANOMALY_DETECTION); - - Untrained = rrddim_add(TrainingStatusRS, "untrained", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - PendingWithoutModel = rrddim_add(TrainingStatusRS, "pending-without-model", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - Trained = rrddim_add(TrainingStatusRS, "trained", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - PendingWithModel = rrddim_add(TrainingStatusRS, "pending-with-model", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - } - - rrddim_set_by_pointer(TrainingStatusRS, Untrained, MLS.NumTrainingStatusUntrained); - rrddim_set_by_pointer(TrainingStatusRS, PendingWithoutModel, MLS.NumTrainingStatusPendingWithoutModel); - rrddim_set_by_pointer(TrainingStatusRS, Trained, MLS.NumTrainingStatusTrained); - rrddim_set_by_pointer(TrainingStatusRS, PendingWithModel, MLS.NumTrainingStatusPendingWithModel); - - rrdset_done(TrainingStatusRS); - } - - /* - * Prediction status - */ - { - static thread_local RRDSET *PredictionRS = nullptr; - - static thread_local RRDDIM *Anomalous = nullptr; - static thread_local RRDDIM *Normal = nullptr; - - if (!PredictionRS) { - std::stringstream IdSS, NameSS; - - IdSS << "dimensions_on_" << localhost->machine_guid; - NameSS << "dimensions_on_" << rrdhost_hostname(localhost); - - PredictionRS = 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_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_TRAINING, // module - ML_CHART_PRIO_DIMENSIONS, // priority - RH->rrd_update_every, // update_every - RRDSET_TYPE_LINE // chart_type - ); - rrdset_flag_set(PredictionRS, RRDSET_FLAG_ANOMALY_DETECTION); - - Anomalous = rrddim_add(PredictionRS, "anomalous", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - Normal = rrddim_add(PredictionRS, "normal", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - } - - rrddim_set_by_pointer(PredictionRS, Anomalous, MLS.NumAnomalousDimensions); - rrddim_set_by_pointer(PredictionRS, Normal, MLS.NumNormalDimensions); - - rrdset_done(PredictionRS); - } - -} - -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_" << rrdhost_hostname(localhost); - - 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_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_DETECTION, // module - ML_CHART_PRIO_ANOMALY_RATE, // 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_" << rrdhost_hostname(localhost); - - 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_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_DETECTION, // module - ML_CHART_PRIO_DETECTOR_EVENTS, // 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<RRDR_OPTIONS>(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, - STORAGE_PRIORITY_BEST_EFFORT - ); - - if(R) { - if(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::updateResourceUsageCharts(RRDHOST *RH, const struct rusage &PredictionRU, const struct rusage &TrainingRU) { - /* - * prediction rusage - */ - { - static thread_local RRDSET *RS = nullptr; - - static thread_local RRDDIM *User = nullptr; - static thread_local RRDDIM *System = nullptr; - - if (!RS) { - std::stringstream IdSS, NameSS; - - IdSS << "prediction_usage_for_" << RH->machine_guid; - NameSS << "prediction_usage_for_" << rrdhost_hostname(RH); - - RS = rrdset_create_localhost( - "netdata", // type - IdSS.str().c_str(), // id - NameSS.str().c_str(), // name - NETDATA_ML_CHART_FAMILY, // family - "netdata.prediction_usage", // ctx - "Prediction resource usage", // title - "milliseconds/s", // units - NETDATA_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_PREDICTION, // module - NETDATA_ML_CHART_PRIO_PREDICTION_USAGE, // priority - RH->rrd_update_every, // update_every - RRDSET_TYPE_STACKED // chart_type - ); - rrdset_flag_set(RS, RRDSET_FLAG_ANOMALY_DETECTION); - - User = rrddim_add(RS, "user", NULL, 1, 1000, RRD_ALGORITHM_INCREMENTAL); - System = rrddim_add(RS, "system", NULL, 1, 1000, RRD_ALGORITHM_INCREMENTAL); - } - - rrddim_set_by_pointer(RS, User, PredictionRU.ru_utime.tv_sec * 1000000ULL + PredictionRU.ru_utime.tv_usec); - rrddim_set_by_pointer(RS, System, PredictionRU.ru_stime.tv_sec * 1000000ULL + PredictionRU.ru_stime.tv_usec); - - rrdset_done(RS); - } - - /* - * training rusage - */ - { - static thread_local RRDSET *RS = nullptr; - - static thread_local RRDDIM *User = nullptr; - static thread_local RRDDIM *System = nullptr; - - if (!RS) { - std::stringstream IdSS, NameSS; - - IdSS << "training_usage_for_" << RH->machine_guid; - NameSS << "training_usage_for_" << rrdhost_hostname(RH); - - RS = rrdset_create_localhost( - "netdata", // type - IdSS.str().c_str(), // id - NameSS.str().c_str(), // name - NETDATA_ML_CHART_FAMILY, // family - "netdata.training_usage", // ctx - "Training resource usage", // title - "milliseconds/s", // units - NETDATA_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_TRAINING, // module - NETDATA_ML_CHART_PRIO_TRAINING_USAGE, // priority - RH->rrd_update_every, // update_every - RRDSET_TYPE_STACKED // chart_type - ); - rrdset_flag_set(RS, RRDSET_FLAG_ANOMALY_DETECTION); - - User = rrddim_add(RS, "user", NULL, 1, 1000, RRD_ALGORITHM_INCREMENTAL); - System = rrddim_add(RS, "system", NULL, 1, 1000, RRD_ALGORITHM_INCREMENTAL); - } - - rrddim_set_by_pointer(RS, User, TrainingRU.ru_utime.tv_sec * 1000000ULL + TrainingRU.ru_utime.tv_usec); - rrddim_set_by_pointer(RS, System, TrainingRU.ru_stime.tv_sec * 1000000ULL + TrainingRU.ru_stime.tv_usec); - - rrdset_done(RS); - } -} - -void ml::updateTrainingStatisticsChart(RRDHOST *RH, const TrainingStats &TS) { - /* - * queue stats - */ - { - static thread_local RRDSET *RS = nullptr; - - static thread_local RRDDIM *QueueSize = nullptr; - static thread_local RRDDIM *PoppedItems = nullptr; - - if (!RS) { - std::stringstream IdSS, NameSS; - - IdSS << "queue_stats_on_" << localhost->machine_guid; - NameSS << "queue_stats_on_" << rrdhost_hostname(localhost); - - RS = rrdset_create( - RH, - "netdata", // type - IdSS.str().c_str(), // id - NameSS.str().c_str(), // name - NETDATA_ML_CHART_FAMILY, // family - "netdata.queue_stats", // ctx - "Training queue stats", // title - "items", // units - NETDATA_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_TRAINING, // module - NETDATA_ML_CHART_PRIO_QUEUE_STATS, // priority - RH->rrd_update_every, // update_every - RRDSET_TYPE_LINE// chart_type - ); - rrdset_flag_set(RS, RRDSET_FLAG_ANOMALY_DETECTION); - - QueueSize = rrddim_add(RS, "queue_size", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - PoppedItems = rrddim_add(RS, "popped_items", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - } - - rrddim_set_by_pointer(RS, QueueSize, TS.QueueSize); - rrddim_set_by_pointer(RS, PoppedItems, TS.NumPoppedItems); - - rrdset_done(RS); - } - - /* - * training stats - */ - { - static thread_local RRDSET *RS = nullptr; - - static thread_local RRDDIM *Allotted = nullptr; - static thread_local RRDDIM *Consumed = nullptr; - static thread_local RRDDIM *Remaining = nullptr; - - if (!RS) { - std::stringstream IdSS, NameSS; - - IdSS << "training_time_stats_on_" << localhost->machine_guid; - NameSS << "training_time_stats_on_" << rrdhost_hostname(localhost); - - RS = rrdset_create( - RH, - "netdata", // type - IdSS.str().c_str(), // id - NameSS.str().c_str(), // name - NETDATA_ML_CHART_FAMILY, // family - "netdata.training_time_stats", // ctx - "Training time stats", // title - "milliseconds", // units - NETDATA_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_TRAINING, // module - NETDATA_ML_CHART_PRIO_TRAINING_TIME_STATS, // priority - RH->rrd_update_every, // update_every - RRDSET_TYPE_LINE// chart_type - ); - rrdset_flag_set(RS, RRDSET_FLAG_ANOMALY_DETECTION); - - Allotted = rrddim_add(RS, "allotted", NULL, 1, 1000, RRD_ALGORITHM_ABSOLUTE); - Consumed = rrddim_add(RS, "consumed", NULL, 1, 1000, RRD_ALGORITHM_ABSOLUTE); - Remaining = rrddim_add(RS, "remaining", NULL, 1, 1000, RRD_ALGORITHM_ABSOLUTE); - } - - rrddim_set_by_pointer(RS, Allotted, TS.AllottedUT); - rrddim_set_by_pointer(RS, Consumed, TS.ConsumedUT); - rrddim_set_by_pointer(RS, Remaining, TS.RemainingUT); - - rrdset_done(RS); - } - - /* - * training result stats - */ - { - static thread_local RRDSET *RS = nullptr; - - static thread_local RRDDIM *Ok = nullptr; - static thread_local RRDDIM *InvalidQueryTimeRange = nullptr; - static thread_local RRDDIM *NotEnoughCollectedValues = nullptr; - static thread_local RRDDIM *NullAcquiredDimension = nullptr; - static thread_local RRDDIM *ChartUnderReplication = nullptr; - - if (!RS) { - std::stringstream IdSS, NameSS; - - IdSS << "training_results_on_" << localhost->machine_guid; - NameSS << "training_results_on_" << rrdhost_hostname(localhost); - - RS = rrdset_create( - RH, - "netdata", // type - IdSS.str().c_str(), // id - NameSS.str().c_str(), // name - NETDATA_ML_CHART_FAMILY, // family - "netdata.training_results", // ctx - "Training results", // title - "events", // units - NETDATA_ML_PLUGIN, // plugin - NETDATA_ML_MODULE_TRAINING, // module - NETDATA_ML_CHART_PRIO_TRAINING_RESULTS, // priority - RH->rrd_update_every, // update_every - RRDSET_TYPE_LINE// chart_type - ); - rrdset_flag_set(RS, RRDSET_FLAG_ANOMALY_DETECTION); - - Ok = rrddim_add(RS, "ok", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - InvalidQueryTimeRange = rrddim_add(RS, "invalid-queries", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - NotEnoughCollectedValues = rrddim_add(RS, "not-enough-values", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - NullAcquiredDimension = rrddim_add(RS, "null-acquired-dimensions", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - ChartUnderReplication = rrddim_add(RS, "chart-under-replication", NULL, 1, 1, RRD_ALGORITHM_ABSOLUTE); - } - - rrddim_set_by_pointer(RS, Ok, TS.TrainingResultOk); - rrddim_set_by_pointer(RS, InvalidQueryTimeRange, TS.TrainingResultInvalidQueryTimeRange); - rrddim_set_by_pointer(RS, NotEnoughCollectedValues, TS.TrainingResultNotEnoughCollectedValues); - rrddim_set_by_pointer(RS, NullAcquiredDimension, TS.TrainingResultNullAcquiredDimension); - rrddim_set_by_pointer(RS, ChartUnderReplication, TS.TrainingResultChartUnderReplication); - - rrdset_done(RS); - } -} |