Installing Yadle » Self-Hosted » System Requirements

The following are requirements and recommendations you should follow when provisioning and setting up your servers to optimize the performance of Yadle for Self-Hosted deployments. The Nodes outlined on this page can be bare-metal servers, VMs, or instances running in the cloud.

Hardware Requirements

Server Node:
  • 12 Core, 24 Thread CPU
  • 64GB RAM
  • 1TB Disk Space* (with ability to grow as needed). SSD recommended.
  • *Disk requirements will largely depend on the nature of your data. A good guideline is to allocate or plan for 2.5% of the total amount of data to be scanned.
  • In order to perform self-hosted AI analysis, a CPU that supports the AVX instruction is required.
  • CUDA enabled NVIDIA GPUs can be utilized for local AI analysis.
  • AI analysis can be done using either CPUs or GPUs. Faster AI analysis is achieved when Using GPUs.

Agent Node:
  • 8 Core, 16 Thread CPU
  • 64GB RAM *
  • 250GB Disk Space
  • * The amount of memory needed for generating turntable previews of 3D models or scenes will depend on the size of the files. If your organization has large 3D file formats, we suggest at least 64 GB of RAM.
  • A 10GbE connection to network attached storage volumes to be scanned by the Yadle agent is preferred.

Software Requirements

Network Requirements

Protocol Port Direction Description
TCP 443 Outbound Connection to backend servers and downloading of docker images from Yadle download server.
TCP 80 Inbound Connection to Yadle servers from clients.
TCP 25/465/587 Outbound Connection to email server.
TCP 4444 Inbound Default port for Yadle API server.
TCP 5999 Inbound Default port for Yadle database.
TCP 443 Inbound Connection to Yadle servers configured for HTTPS.