Analytics

you can use the analytics module to create and manage analytics flows analytics flows enable you to process and analyze data at the edge a flow includes a series of connected processors, using at least one of the following types input retrieves data from a tag/topic, database, or generator see input processors docid\ st3 rfwbzixn nlgcezhe for more details function processes the input data using built in kpis (key performance indicators) see key performance indicators docid\ aypbp0hikhmscmxvov8h7 for more details statistical functions see statistical functions docid\ sbdu9ozlplfao1vrhhrnd for more details output writes the function results to a tag/topic or database see output processors (3 22 0) docid\ t x 74dsxso1bejyiv7bo for details see create an analytics flow docid\ qqogdbmh nz5rlbe3eni1 and add processors and processor connections docid\ hlhao9nxasjvcczrziclh to learn more important you may see the following error message when working with analytics "http failure response for /analytics/v2/version 0 unknown error" if you see this message, disable any ad blockers your browser may have you can build a flow manually by adding processors and then connecting them with one of the following connection types events (individual data source) used for both input/function and function/output connections makes the receiving processor react to each individual data value immediately values (combined data sources) used only for input/function connections makes the function processor wait for values from all of the combined data sources before reacting for example, if the function processor compares values from input processors a and b, it will wait for a value from both a and b before performing the comparison you can also add a flow in a more automated way see create an analytics flow docid\ qqogdbmh nz5rlbe3eni1 for details the analytics module also enables you to use machine learning models for prediction, classification, and anomaly detection you can create and save a model from tensorflow a saved model contains a complete tensorflow program, including weights and computation the analytics ui includes the following panes instances , where you can create and manage processors and flows view the debug panel organize your flows into groups instances table , where you get tabular view of instance flows created models , where you upload and remove models analytics guides review analytics guides docid\ g xbmnakgtz4wzqhdhgug to see how to leverage different analytics capabilities and functions access analytics ui to access analytics log in to litmus edge from the navigation panel, select analytics the analytics canvas appears next steps analytics guides docid\ g xbmnakgtz4wzqhdhgug analytics flows and processors docid\ szbjqpbfadrug2mc22qsh analytics flow groups docid\ xr2ph3fjcptmcrvji1 uw instances table docid 7noihhsvoqamey5zg0imu machine learning models docid\ m1ymmcocxvsrotzbpwsph input processors docid\ st3 rfwbzixn nlgcezhe output processors (3 22 0) docid\ t x 74dsxso1bejyiv7bo statistical functions docid\ sbdu9ozlplfao1vrhhrnd key performance indicators docid\ aypbp0hikhmscmxvov8h7