Be sure to take a minute to learn the FindFace Enterprise Server architecture. This knowledge is essential for the FindFace Enterprise Server deployment, integration, maintenance, and troubleshooting.

In this chapter:

Architectural Elements

FindFace Enterprise Server consists of the following architectural elements:

  • FindFace core,

  • (optional) application modules.


    Application modules are not available in the basic configuration. To learn more about building a turnkey application with the help of our team, contact our experts by

The FindFace core includes the following components:

Component Description Vendor
findface-extraction-api Service that uses neural networks to detect a face in an image and extract a face biometric sample (feature vector), gender, age, emotions, and other face attributes. CPU- or GPU-acceleration. Ntech Lab own deployment
findface-sf-api Service that implements HTTP API for face detection and face recognition.
findface-tarantool-server Service that provides interaction between the findface-sf-api service and the biometric database (the Tarantool-powered database that stores face biometric samples).
findface-upload NGINX-based web server used as a storage for original images, thumbnails, and normalized face images.
findface-facerouter Service used to define processing directives for detected faces.
findface-video-manager Part of the video face detection module. Service that is used for managing the video face detection functionality, configuring the video face detector settings, and specifying the list of to-be-processed video streams.
findface-video-worker Part of the video face detection module. Service that recognizes a face in the video and posts its normalized image, full frame, and such metadata as the camera ID and detection time to the findface-facerouter service for further processing according to given directives. CPU- or GPU-acceleration.
findface-ntls License server which interfaces with the NtechLab Global License Server or a USB dongle to verify the license of your FindFace Enterprise Server instance.
Tarantool Third-party software which implements the biometric database that stores extracted biometric samples (feature vectors). Tarantool
etcd Third-party software that implements a distributed key-value store for findface-video-manager. Used as a coordination service in the distributed system, providing the video face detector with fault tolerance. etcd
NGINX Third-party software which implements the findface-upload component. nginx
memcached Third-party software which implements a distributed memory caching system. Used by findface-extraction-api as temporary storage for extracted face biometric samples before they are written to the biometric database powered by Tarantool. memcached

Single- and Multi-Host Deployment

Depending on your system characteristics and performance requirements, you can opt to install FindFace Enterprise Server standalone or in a cluster environment:

Deployment Recommendation
Standalone You can deploy FindFace Enterprise Server and neural network models on a single host (standalone) if the number of faces in the database does not exceed 1,000,000 (recommended limit). This variant makes it easier to start deployment and cater to the basic requirements of your system.
Cluster If the number of faces in the database does exceed 1,000,000, we recommend you to deploy FindFace Enterprise Server in a cluster environment. In this case, FindFace Enterprise Server components will be distributed across several hosts. This is a medium and large deployment that can be scaled almost infinitely. It will also suit professional high load projects with severe requirements for performance.

If you opt for the cluster deployment, we offer you one of the following deployment schemes:

  • Deploy FindFace Enterprise Server standalone and distribute additional findface-video-worker components across multiple hosts.
  • Distribute the FindFace Enterprise Server components across multiple hosts. If necessary, set up load balancing.

CPU- and GPU-acceleration

The findface-extraction-api and findface-video-worker services can be either CPU- or GPU-based. During installation from the developer-friendly installer, you will have an opportunity to choose the acceleration type you need.

If you opt to install FindFace Enterprise Server from the repository package, deploy the findface-extraction-api and findface-video-worker-cpu packages on a CPU-based server, and the findface-extraction-api-gpu and/or findface-video-worker-gpu packages on a GPU-based server.


Refer to Distribution requirements when choosing hardware configuration.


If the resolution of a camera(s) in use is more than 1280x720px, it is strongly recommended to use the GPU-accelerated package findface-video-worker-gpu.