M30Release of Rule-based and ML-based Refactoring

This is the M24Release of Rule-based and ML-based Refactoring. This includes ML modeling, anomaly detection, forecasting, and event-driven policy based adaptation.

M24Release of Rule-based and ML-based Refactoring

This is the M24Release of Rule-based and ML-based Refactoring. This includes ML modeling, forecasting, and event-driven policy based adaptation.

M18Release of Deployment Refactorer

MS5 Release at M18

Deployment Refactorer v.0.2

This module implements machine-learning and rule-based (knowledge-based) refactoring of application deployments. It also includes the machine learning based performance modelling for refactoring.
This release includes the performance prediction API for an application with multiple deployment variants. The predictors can be built at runtime using thee different machine leaning models: decision tree regression, random Forest Regression, and multiple-layer perceptron neural network. This release also includes the updates to the refactorer service API, and the initial support for (pull and alerting based) monitoring using SODALITE monitoring layer (Prometheus).

First Version of Deployment Refactorer

This module implements machine-learning and rule-based (knowledge-based) refactoring of application deployments. It also includes the machine learning based performance modeling for refactoring.