Deployment

Ultralytics Platform provides comprehensive deployment options for putting your YOLO models into production. Test models with browser-based inference, deploy to dedicated endpoints across 43 global regions, and monitor performance in real-time.

<strong>Watch:</strong> Get Started with Ultralytics Platform - Deploy

Overview

The Deployment section helps you:

• Test models directly in the browser with the Predict tab
• Deploy to dedicated endpoints in 43 global regions
• Monitor request metrics, logs, and health checks
• Scale to zero when idle (deployments currently run a single active instance)

Deployment Options

Ultralytics Platform offers multiple deployment paths:

Workflow

graph LR
    A[✅ Test] --> B[⚙️ Configure]
    B --> C[🌐 Deploy]
    C --> D[📊 Monitor]

    style A fill:#4CAF50,color:#fff
    style B fill:#2196F3,color:#fff
    style C fill:#FF9800,color:#fff
    style D fill:#9C27B0,color:#fff

Architecture

Shared Inference

The shared inference service runs in 3 key regions, automatically routing requests based on your data region:

graph TB
    User[User Request] --> API[Platform API]
    API --> Router{Region Router}
    Router -->|US users| US["US Predict Service
Iowa"]
    Router -->|EU users| EU["EU Predict Service
Belgium"]
    Router -->|AP users| AP["AP Predict Service
Taiwan"]

    style User fill:#f5f5f5,color:#333
    style API fill:#2196F3,color:#fff
    style Router fill:#FF9800,color:#fff
    style US fill:#4CAF50,color:#fff
    style EU fill:#4CAF50,color:#fff
    style AP fill:#4CAF50,color:#fff

Dedicated Endpoints

Deploy to 43 regions worldwide on Ultralytics Cloud:

• Americas: 14 regions
• Europe: 13 regions
• Asia-Pacific: 12 regions
• Middle East & Africa: 4 regions

Each endpoint is a single-tenant service with:

• Default resources of 1 CPU, 2 GiB memory, minInstances=0, maxInstances=1
• Scale-to-zero when idle
• Unique endpoint URL
• Independent monitoring, logs, and health checks

Deployments Page

Access the global deployments page from the sidebar under Deploy. This page shows:

• World map with deployed region pins (interactive map)
• Overview cards: Total Requests (24h), Active Deployments, Error Rate (24h), P95 Latency (24h)
• Deployments list with three view modes: cards, compact, and table
• New Deployment button to create endpoints from any completed model

!!! info "Automatic Polling"

The page polls every 15 seconds normally. When deployments are in a transitional state (`creating`, `deploying`, or `stopping`), polling increases to every 3 seconds for faster feedback.

Key Features

Global Coverage

Deploy close to your users with 43 regions covering:

• North America, South America
• Europe, Middle East, Africa
• Asia Pacific, Oceania

Scaling Behavior

Endpoints currently behave as follows:

• Scale to zero: No cost when idle (default)
• Single active instance: maxInstances is currently capped at 1 on all plans

!!! tip "Cost Savings"

Scale-to-zero is enabled by default (min instances = 0). You only pay for active inference time.

Low Latency

Dedicated endpoints provide:

• Cold start: ~5-15 seconds (cached container), up to ~45 seconds (first deploy)
• Warm inference: 50-200ms (model dependent)
• Regional routing for optimal performance

Health Checks

Each running deployment includes an automatic health check with:

• Live status indicator (healthy/unhealthy)
• Response latency display
• Auto-retry when unhealthy (polls every 20 seconds)
• Manual refresh button

Quick Start

Deploy a model in under 2 minutes:

1. Train or upload a model to a project
2. Go to the model's Deploy tab
3. Select a region from the latency table
4. Click Deploy — your endpoint is live

!!! example "Quick Deploy"

```
Model → Deploy tab → Select region → Click Deploy → Endpoint URL ready
```

Once deployed, use the endpoint URL with your API key to send inference requests from any application.

Quick Links

• Inference: Test models in browser
• Endpoints: Deploy dedicated endpoints
• Monitoring: Track deployment performance

FAQ

What's the difference between shared and dedicated inference?

How long does deployment take?

Dedicated endpoint deployment typically takes 1-2 minutes:

1. Image pull (~30s)
2. Container start (~30s)
3. Health check (~30s)

Can I deploy multiple models?

Yes, each model can have multiple endpoints in different regions. Deployment counts are limited by plan: Free 3, Pro 10, Enterprise unlimited.

What happens when an endpoint is idle?

With scale-to-zero enabled:

• Endpoint scales down after inactivity
• First request triggers cold start
• Subsequent requests are fast

First requests after an idle period trigger a cold start.