ML VM (Threat Hunting) Deployment
Overview
Threat Hunting is a machine learning-based anomaly detection add-on. It requires a dedicated Machine Learning (ML) VM, deployed alongside — but separate from — the ECA cluster, to run the anomaly-detection models against the same audit event stream the ECA already processes. Threat Hunting is included in your subscription license for Data Security Edition — no separate license is required, your data does not leave your on-premises environment, and it will show up in the menu once installed.
Sizing for the ML VM scales with the size of your ECA cluster — see Design Guide — Threat Hunting Machine Learning VM Sizing for the full table. This page covers what's specific to the ML VM itself: platform support, minimum hardware/software requirements, and the configuration details you need to gather before installing it.
Platform Support
The Threat Hunting module is currently distributed as an OVA package and is supported only on VMware-based virtualization platforms. Support for additional hypervisors is planned for a future release.
Minimum Requirements
- CPU: 8 cores minimum
- RAM: 48 GB minimum
- Storage: 300 GB minimum
These are the minimum specifications for smaller environments (3 or 6 ECA nodes). For larger ECA clusters (9 or more nodes), the ML VM requires more resources — see the full sizing table in the Design Guide.
Software Prerequisites
- Operating system: OpenSUSE Linux. Deploy the OVA named Superna Kubernetes OVF (latest version) from the Superna Support Portal.
- Eyeglass: Version 2.14.1 or higher, with an ECA cluster already configured.
- Administrative access: Root/sudo privileges on the installation server.
This 2.15.0 release satisfies the Eyeglass version minimum above (2.15.0 is higher than 2.14.1).
Required Configuration Details
Before starting installation, gather the following from each relevant VM:
On the Threat Hunting VM:
| Information | How to obtain |
|---|---|
| ML module IP address and port | Run ip addr show for the IP address; the port is specified during installation. |
On ECA node 1:
| Information | How to obtain |
|---|---|
| ECA node IP addresses | Run ecactl cluster exec hostname -I to list all node IPs. |
| Kafka connection info | Run ecactl cluster exec docker exec kafka cat ./config/server.properties | grep listeners= on the ECA master node. |
On the Eyeglass/SCA VM:
| Information | How to obtain |
|---|---|
| Eyeglass server IP | Run hostname -I on the Eyeglass VM. |
| Appliance ID | Displayed directly in Inventory → License Management (with a Copy Appliance ID button), or run igls admin appid on the Eyeglass server. |
Download Requirements
Download the Threat Hunting installer (latest version) from the Superna Support Portal, in addition to the Superna Kubernetes OVF referenced above.
See also
- Design Guide — Threat Hunting Machine Learning VM Sizing — VM sizing table by ECA cluster size.
- Installation — Threat Hunting — full installation and configuration procedure.
- ECAs — ECA cluster sizing that determines ML VM sizing tier.