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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.



Watch: 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)

Ultralytics Platform Deploy Page World Map With Overview Cards

Deployment Options

Ultralytics Platform offers multiple deployment paths:

OptionDescriptionBest For
Predict TabBrowser-based inference with image, webcam, and examplesDevelopment, validation
Shared InferenceMulti-tenant service across 3 regionsLight usage, testing
Dedicated EndpointsSingle-tenant services across 43 regionsProduction, low latency

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
StageDescription
TestValidate model with the Predict tab
ConfigureSelect region and deployment name (deployments use fixed default resources)
DeployCreate a dedicated endpoint from the Deploy tab
MonitorTrack requests, latency, errors, and logs in Monitoring

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<br/>Iowa"]
    Router -->|EU users| EU["EU Predict Service<br/>Belgium"]
    Router -->|AP users| AP["AP Predict Service<br/>Hong Kong"]

    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
RegionLocation
USIowa, USA
EUBelgium, Europe
APHong Kong, Asia-Pacific

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

Ultralytics Platform Deploy Page Overview Cards And Deployments List

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

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

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.

FAQ

What's the difference between shared and dedicated inference?

FeatureSharedDedicated
LatencyVariableConsistent
CostFree (included)Free (basic), usage-based (advanced)
ScaleLimitedScale-to-zero, single instance
Regions343
URLGenericCustom
Rate20 req/minUnlimited

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.



📅 Created 2 months ago ✏️ Updated 1 day ago
glenn-jocherRizwanMunawarsergiuwaxmann

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