R statistical computing and graphic tool for Zabbix monitoring metrics from data scientists
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.
doc README Jul 2, 2016


Monitoring Analytics

Limited public demo instance: https://monitoringartist.shinyapps.io/monitoring-analytics/

If you like or use this project, please provide feedback to author - Star it ★.

Yes, monitoring is not a rocket science usually. However your monitoring system keeps a lot of time series data. You can you use science / math / statistics and turn your data into knowledge, which can be used to improve your monitoring systems and settings. Don't estimate any static thresholds for your metrics. Set them based on your real values. If you don't know, what is normal value, then try to detect anomalies in your series. Remember, your only limitation is your data science imagination: histograms, linear/polynomial/... trends, prediction, anomaly detection, correlation, 3d visualization, heat map, ...

Monitoring Analytics

Overview of Monitoring Artist Dockerized monitoring ecosystem:

Please donate to author, so he can continue to publish other awesome projects for free:

Paypal donate button

Dockerized Monitoring Analytics

docker run \
  -d \
  --name=shiny \
  -p 3838:3838 \


Deep monitoring knowledge and science skills are required, so only commercial support is available.

Recommended related articles


Devops Monitoring Expert, who loves monitoring systems and cutting/bleeding edge technologies: Docker, Kubernetes, ECS, AWS, Google GCP, Terraform, Lambda, Zabbix, Grafana, Elasticsearch, Kibana, Prometheus, Sysdig, ...


Professional devops / monitoring / consulting services:

Monitoring Artist