ML-Driven Autoscaling
Uses IsolationForest anomaly detection to predict resource demands and make intelligent scaling decisions based on historical patterns.
Automatically adjust LXC container resources based on real-time usage and machine learning predictions

Install LXC AutoScale ML on your Proxmox host:
curl -sSL https://raw.githubusercontent.com/fabriziosalmi/proxmox-lxc-autoscale-ml/main/install.sh | bashCheck service status:
systemctl status lxc_autoscale_api lxc_monitor lxc_autoscale_ml| Requirement | Version |
|---|---|
| Proxmox VE | 6.x or higher (tested on 8.2.4) |
| Python | 3.x |
| Operating System | Linux (Debian-based) |
βββββββββββββββ βββββββββββββββ βββββββββββββββ
β Monitor ββββββΆβ Model ββββββΆβ API β
β (Metrics) β β (ML Engine) β β (Actions) β
βββββββββββββββ βββββββββββββββ βββββββββββββββ
β β β
βΌ βΌ βΌ
Collect CPU, Train model, Apply scaling
RAM, disk, detect anomalies, decisions to
network stats predict needs containersLXC AutoScale ML is released under the MIT License.
Enjoy and contribute π