On-premise Deployment Options

Scaleout Edge is designed to scale from a single laptop to a multi-region cloud cluster. To support this flexibility, we offer two primary deployment architectures:

  • Starter (Docker Compose): For R&D, proof-of-concept, and small-scale pilots.

  • Production (Kubernetes): For mission-critical, high-availability enterprise deployments.

1. Starter: Docker Compose

The Starter deployment runs the entire Control Plane (UI, Controller, Combiner, Database) on a single machine using Docker Compose.

Use Cases

  • R&D & Prototyping: Rapidly iterate on model architectures and client logic locally.

  • Small Fleets: Manage up to ~50 edge nodes for a pilot study.

  • Air-Gapped Demos: Run a complete, self-contained network without internet access.

Architecture

In this mode, all services run as containers on a shared Docker network:

  • Postgres: Stores metadata, users, and audit logs.

  • MinIO: Acts as a local S3-compatible object store for models and compute packages.

  • Controller & Combiner: Run as lightweight services exposing ports 8090 (API) and 12080 (gRPC).

Getting Started

To spin up a Starter instance:

# 1. Clone the repository
git clone https://github.com/scaleoutsystems/scaleout-stack.git
cd scaleout-stack

# 2. Start the stack
docker compose up -d

# 3. Access the UI
# Navigate to http://localhost:8090

2. Production: Kubernetes (K8s)

For enterprise scale, high availability, and strict security requirements, Scaleout Edge should be deployed on Kubernetes. We provide official Helm Charts to automate this process.

Use Cases

  • Large Scale: Orchestrating thousands or millions of edge nodes.

  • High Availability: Redundant Controllers and Combiners to ensure zero downtime.

  • Enterprise Integration: Connecting to external identity providers (OIDC/LDAP), managed databases (RDS/CloudSQL), and observability stacks (Datadog/Prometheus).

Architecture Changes

Moving to production introduces several architectural enhancements:

Component

Starter (Docker)

Production (K8s)

Orchestration

docker-compose.yml

Helm Charts

Storage

Local MinIO Container

Managed Object Storage (AWS S3, Azure Blob, GCS)

Database

Local Postgres or MongoDB Container

Managed Database (OEM or Self-Hosted)

Ingress

Direct Port Exposure

K8s Ingress Controller (NGINX/Traefik) with TLS termination

Scaling

Single Instance

Horizontal Pod Autoscaling (HPA)

Deployment Workflow

Deploying to a K8s cluster (e.g., EKS, AKS, GKE) typically involves:

  1. Configure values.yaml: Define your domain, external database credentials, and resource limits.

  2. Install via Helm:

helm repo add scaleout https://charts.scaleoutsystems.com
helm install scaleout-edge scaleout/scaleout-edge -f values.yaml

  1. Scale: As your fleet grows, simply increase the replicaCount of the services (or use Horizontal Pod Autoscaling) to handle more concurrent connections.