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// 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<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
);
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);
}
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