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authorDaniel Baumann <daniel.baumann@progress-linux.org>2021-12-01 06:15:04 +0000
committerDaniel Baumann <daniel.baumann@progress-linux.org>2021-12-01 06:15:04 +0000
commite970e0b37b8bd7f246feb3f70c4136418225e434 (patch)
tree0b67c0ca45f56f2f9d9c5c2e725279ecdf52d2eb /ml/Host.h
parentAdding upstream version 1.31.0. (diff)
downloadnetdata-e970e0b37b8bd7f246feb3f70c4136418225e434.tar.xz
netdata-e970e0b37b8bd7f246feb3f70c4136418225e434.zip
Adding upstream version 1.32.0.upstream/1.32.0
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'ml/Host.h')
-rw-r--r--ml/Host.h104
1 files changed, 104 insertions, 0 deletions
diff --git a/ml/Host.h b/ml/Host.h
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index 000000000..86591d7ae
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+++ b/ml/Host.h
@@ -0,0 +1,104 @@
+// SPDX-License-Identifier: GPL-3.0-or-later
+
+#ifndef ML_HOST_H
+#define ML_HOST_H
+
+#include "BitRateWindow.h"
+#include "Config.h"
+#include "Database.h"
+#include "Dimension.h"
+
+#include "ml-private.h"
+
+namespace ml {
+
+class RrdHost {
+public:
+ RrdHost(RRDHOST *RH) : RH(RH) {}
+
+ RRDHOST *getRH() { return RH; }
+
+ unsigned updateEvery() { return RH->rrd_update_every; }
+
+ std::string getUUID() {
+ char S[UUID_STR_LEN];
+ uuid_unparse_lower(RH->host_uuid, S);
+ return S;
+ }
+
+ void addDimension(Dimension *D);
+ void removeDimension(Dimension *D);
+
+ void getConfigAsJson(nlohmann::json &Json) const;
+
+ virtual ~RrdHost() {};
+
+protected:
+ RRDHOST *RH;
+
+ // Protect dimension and lock maps
+ std::mutex Mutex;
+
+ std::map<RRDDIM *, Dimension *> DimensionsMap;
+ std::map<Dimension *, std::mutex> LocksMap;
+};
+
+class TrainableHost : public RrdHost {
+public:
+ TrainableHost(RRDHOST *RH) : RrdHost(RH) {}
+
+ void train();
+
+private:
+ std::pair<Dimension *, Duration<double>> findDimensionToTrain(const TimePoint &NowTP);
+ void trainDimension(Dimension *D, const TimePoint &NowTP);
+};
+
+class DetectableHost : public TrainableHost {
+public:
+ DetectableHost(RRDHOST *RH) : TrainableHost(RH) {}
+
+ void startAnomalyDetectionThreads();
+ void stopAnomalyDetectionThreads();
+
+ template<typename ...ArgTypes>
+ bool getAnomalyInfo(ArgTypes&&... Args) {
+ return DB.getAnomalyInfo(Args...);
+ }
+
+ template<typename ...ArgTypes>
+ bool getAnomaliesInRange(ArgTypes&&... Args) {
+ return DB.getAnomaliesInRange(Args...);
+ }
+
+ void getDetectionInfoAsJson(nlohmann::json &Json) const;
+
+private:
+ void detect();
+ void detectOnce();
+
+private:
+ std::thread TrainingThread;
+ std::thread DetectionThread;
+
+ BitRateWindow BRW{
+ static_cast<size_t>(Cfg.ADMinWindowSize),
+ static_cast<size_t>(Cfg.ADMaxWindowSize),
+ static_cast<size_t>(Cfg.ADIdleWindowSize),
+ static_cast<size_t>(Cfg.ADMinWindowSize * Cfg.ADWindowRateThreshold)
+ };
+
+ CalculatedNumber AnomalyRate{0.0};
+
+ size_t NumAnomalousDimensions{0};
+ size_t NumNormalDimensions{0};
+ size_t NumTrainedDimensions{0};
+
+ Database DB{Cfg.AnomalyDBPath};
+};
+
+using Host = DetectableHost;
+
+} // namespace ml
+
+#endif /* ML_HOST_H */