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vsergeyev / loudml-grafana-app

Visualization panel and datasource for Grafana to connect with Loud ML AI solution for ICT and IoT automation
https://vsergeyev.github.io/loudml-grafana-app/
MIT License
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ai anomaly-detection baseline datasource docker donut grafana graph loudml machine-learning ml model monitoring panel plugin prediction

readme

LoudML Grafana Application

Visualization panel and datasource for Grafana 6.7.x - 7.x to connect with Loud ML AI solution for ICT and IoT automation. https://loudml.io

LoudML Panel in Grafana

LoudML Datasource in Grafana

Loud ML is an open source inference engine for metrics and events, and the fastest way to embed machine learning in your time series application. This includes APIs for storing and querying data, processing it in the background for ML or detecting outliers for alerting purposes, and more. https://github.com/regel/loudml

Installation

Repository conventions:

ZIP files has packaged plugin for each of Grafana version supported.

A) Give it a try with Docker

  docker run -d \
  -p 3000:3000 \
  --name=grafana \
  -e "GF_INSTALL_PLUGINS=https://github.com/vsergeyev/loudml-grafana-app/raw/master/loudml-grafana-app-latest.zip;loudml-grafana-app" \
  grafana/grafana

Setup LoudML if needed (please refer to https://hub.docker.com/r/loudml/loudml for config.yml setup)

  docker run -p 8077:8077 \
  -v $PWD/lib/loudml:/var/lib/loudml:rw \
  -v $PWD/config.yml:/etc/loudml/config.yml:ro \
  -ti \
  loudml/loudml

B) In existing Grafana container

C) From sources (note - default master branch is for Grafana 7.x)

Whats inside

Loud ML Panel - is a version of Grafana's default Graph Panel with a "Create Baseline" button to create ML model in 1-click.

Currently 1-click ML button ("Create Baseline") can produce model from:

Loud ML Datasource - is a connector to Loud ML server. It has capabilities to show models and jobs on server. You can add new and edit existing models.

Prerequisites

* Loud ML server https://github.com/regel/loudml
* Grafana >= 5.4.0

Configuration

In order to use Loud ML with Grafana you need to have a buckets in loudml.yml to reflect Grafana datasource(s) used in LoudML Graph

LoudML Panel Configuration in Grafana

Example: I have InfluxDB datasource with telegraf database as an input and will use loudml database as output for ML model predictions/forecasting/anomalies:

buckets:
 - name: loudml
   type: influxdb
   addr: 127.0.0.1:8086
   database: loudml
   retention_policy: autogen
   measurement: loudml
   annotation_db: loudmlannotations
 - name: influxdb1
   type: influxdb
   addr: 127.0.0.1:8086
   database: telegraf
   retention_policy: autogen
   measurement: loudml
 - name: data
   type: influxdb
   addr: 127.0.0.1:8086
   database: data
   retention_policy: autogen
   measurement: sinus
 - name: opentsdb1
   type: opentsdb
   addr: 127.0.0.1:4242
   retention_policy: autogen
 - name: prom1
   type: prometheus
   addr: 127.0.0.1:9090
   retention_policy: autogen

InfluxDB loudmlannotations here specified to store annotations. (By default Loud ML server will store annotations in chronograf database). So on Grafana dashboard annotations/anomalies from Loud ML should be configured as:

SELECT "text" FROM "autogen"."annotations" WHERE $timeFilter

LoudML Annotations in Grafana

Support

Please post issue to tracker or contact me via vova.sergeyev at gmail.com

Changelog