AI

DataForge AI is a feature to train AI models on Zabbix data. These models can be used for tasks such as detection of anomalies.

The DataForge AI workflow consists of three main parts:

  • a dataset
  • a model
  • the inference

These three parts are explained in the AI chapter of the user manual.

Datasets

Dataset configs determine how data is extracted from the Zabbix server into datasets. Each dataset is listed in the config that was used to create it. Datasets are used as training data for the AI model and as validation sets to evaluate model performance in model tests.

Models

AI Models are based on model configurations and trained on datasets. They are used by the AI Server to detect anomalies in live data.

Deployments

Deployments determine how a model is deployed and where its reconstruction loss is sent.