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Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

2026-04-07 21:51:06 +02:00

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comments	description	keywords
true	Deploy YOLO models to dedicated endpoints in 43 global regions with scale-to-zero behavior and monitoring on Ultralytics Platform.	Ultralytics Platform, deployment, endpoints, YOLO, production, scaling, global regions

Dedicated Endpoints

Ultralytics Platform enables deployment of YOLO models to dedicated endpoints in 43 global regions. Each endpoint is a single-tenant service with scale-to-zero behavior, a unique endpoint URL, and independent monitoring.

Create Endpoint

From the Deploy Tab

Deploy a model from its Deploy tab:

Navigate to your model
Click the Deploy tab
Select a region from the interactive world map — regions are color-coded by latency from your location (green < 100ms, yellow < 200ms, red > 200ms)
Click Deploy on the region row

The deployment name is auto-generated from the model name and region city (e.g., yolo26n-iowa).

From the Deployments Page

Create a deployment from the global Deploy page in the sidebar:

Click New Deployment
Select a model from the model selector
Select a region from the map or table
Review the auto-generated deployment name (editable) and the default resources
Click Deploy Model

Deployment Lifecycle

stateDiagram-v2
    [*] --> Creating: Deploy
    Creating --> Deploying: Container starting
    Deploying --> Ready: Health check passed
    Ready --> Stopping: Stop
    Stopping --> Stopped: Stopped
    Stopped --> Ready: Start
    Ready --> [*]: Delete
    Stopped --> [*]: Delete
    Creating --> Failed: Error
    Deploying --> Failed: Error
    Failed --> [*]: Delete

Region Selection

Choose from 43 regions worldwide. The interactive region map and table show:

Region pins: Color-coded by latency (green < 100ms, yellow < 200ms, red > 200ms)
Deployed regions: Highlighted with a "Deployed" badge
Deploying regions: Animated pulse indicator
Bidirectional highlighting: Hover on the map highlights the table row, and vice versa

The region table on the model Deploy tab includes:

Column	Description
Location	City and country with flag icon
Zone	Region identifier
Latency	Measured ping time (median of 3 pings)
Distance	Distance from your location in km
Actions	Deploy button or "Deployed" status badge

!!! note "New Deployment Dialog"

The `New Deployment` dialog (from the global `Deploy` page) shows a simpler region table with only Location, Latency, and Select columns.

!!! tip "Choose Wisely"

Select the region closest to your users for lowest latency. Use the **Rescan** button to re-measure latency from your current location.

Available Regions

=== "Americas (14)"

| Zone                    | Location               |
| ----------------------- | ---------------------- |
| us-central1             | Iowa, USA              |
| us-east1                | South Carolina, USA    |
| us-east4                | Northern Virginia, USA |
| us-east5                | Columbus, USA          |
| us-south1               | Dallas, USA            |
| us-west1                | Oregon, USA            |
| us-west2                | Los Angeles, USA       |
| us-west3                | Salt Lake City, USA    |
| us-west4                | Las Vegas, USA         |
| northamerica-northeast1 | Montreal, Canada       |
| northamerica-northeast2 | Toronto, Canada        |
| northamerica-south1     | Queretaro, Mexico      |
| southamerica-east1      | Sao Paulo, Brazil      |
| southamerica-west1      | Santiago, Chile        |

=== "Europe (13)"

| Zone              | Location               |
| ----------------- | ---------------------- |
| europe-west1      | St. Ghislain, Belgium  |
| europe-west2      | London, UK             |
| europe-west3      | Frankfurt, Germany     |
| europe-west4      | Eemshaven, Netherlands |
| europe-west6      | Zurich, Switzerland    |
| europe-west8      | Milan, Italy           |
| europe-west9      | Paris, France          |
| europe-west10     | Berlin, Germany        |
| europe-west12     | Turin, Italy           |
| europe-north1     | Hamina, Finland        |
| europe-north2     | Stockholm, Sweden      |
| europe-central2   | Warsaw, Poland         |
| europe-southwest1 | Madrid, Spain          |

=== "Asia-Pacific (12)"

| Zone                 | Location               |
| -------------------- | ---------------------- |
| asia-east1           | Changhua, Taiwan       |
| asia-east2           | Kowloon, Hong Kong     |
| asia-northeast1      | Tokyo, Japan           |
| asia-northeast2      | Osaka, Japan           |
| asia-northeast3      | Seoul, South Korea     |
| asia-south1          | Mumbai, India          |
| asia-south2          | Delhi, India           |
| asia-southeast1      | Jurong West, Singapore |
| asia-southeast2      | Jakarta, Indonesia     |
| asia-southeast3      | Bangkok, Thailand      |
| australia-southeast1 | Sydney, Australia      |
| australia-southeast2 | Melbourne, Australia   |

=== "Middle East & Africa (4)"

| Zone          | Location                   |
| ------------- | -------------------------- |
| africa-south1 | Johannesburg, South Africa |
| me-central1   | Doha, Qatar                |
| me-central2   | Dammam, Saudi Arabia       |
| me-west1      | Tel Aviv, Israel           |

Endpoint Configuration

New Deployment Dialog

The New Deployment dialog provides:

Setting	Description	Default
Model	Select from completed models	-
Region	Deployment region	-
Deployment Name	Auto-generated, editable	-
CPU Cores	Fixed default	1
Memory (GB)	Fixed default	2

Deployments use fixed defaults of 1 CPU, 2 GiB memory, minInstances = 0, and maxInstances = 1. They scale to zero when idle, so you only pay for active inference time.

!!! note "Auto-Generated Names"

The deployment name is automatically generated from the model name and region city (e.g., `yolo26n-iowa`). If you deploy the same model to the same region again, a numeric suffix is added (e.g., `yolo26n-iowa-2`).

Deploy Tab (Quick Deploy)

When deploying from the model's Deploy tab, endpoints are created with default resources (1 CPU, 2 GB memory) with scale-to-zero enabled. The deployment name is auto-generated.

Manage Endpoints

View Modes

The deployments list supports three view modes:

Mode	Description
Cards	Full detail cards with logs, code examples, predict panel
Compact	Grid of smaller cards with key metrics
Table	DataTable with sortable columns and search

Deployment Card (Cards View)

Each deployment card in the cards view shows:

Header: Name, region flag, status badge, start/stop/delete buttons
Endpoint URL: Copyable URL with link to API docs
Metrics: Request count (24h), P95 latency, error rate
Health check: Live health indicator with latency and manual refresh
Tabs: Logs, Code, and Predict

The Logs tab shows recent log entries with severity filtering (All / Errors). The Code tab shows ready-to-use code examples in Python, JavaScript, and cURL with your actual endpoint URL and API key. The Predict tab provides an inline predict panel for testing directly on the deployment.

Deployment Statuses

Status	Description
Creating	Deployment is being set up
Deploying	Container is starting
Ready	Endpoint is live and accepting requests
Stopping	Endpoint is shutting down
Stopped	Endpoint is paused (no billing)
Failed	Deployment failed (see error message)

Endpoint URL

Each endpoint has a unique URL, for example:

https://predict-abc123.run.app

Click the copy button to copy the URL. Click the docs icon to view the auto-generated API documentation for the endpoint.

Lifecycle Management

Control your endpoint state:

graph LR
    R[Ready] -->|Stop| S[Stopped]
    S -->|Start| R
    R -->|Delete| D[Deleted]
    S -->|Delete| D

    style R fill:#4CAF50,color:#fff
    style S fill:#9E9E9E,color:#fff
    style D fill:#F44336,color:#fff

Action	Description
Start	Resume a stopped endpoint
Stop	Pause the endpoint (no billing)
Delete	Permanently remove endpoint

Stop Endpoint

Stop an endpoint to pause billing:

Click the pause icon on the deployment card
Endpoint status changes to "Stopping" then "Stopped"

Stopped endpoints:

Don't accept requests
Don't incur charges
Can be restarted anytime

Delete Endpoint

Permanently remove an endpoint:

Click the delete (trash) icon on the deployment card
Confirm deletion in the dialog

!!! warning "Permanent Action"

Deletion is immediate and permanent. You can always create a new endpoint.

Using Endpoints

Authentication

Each deployment is created with an API key from your account. Include it in requests:

Authorization: Bearer YOUR_API_KEY

The API key prefix is displayed on the deployment card footer for identification. Generate keys from API Keys.

No Rate Limits

Dedicated endpoints are not subject to the Platform API rate limits. Requests go directly to your dedicated service, so throughput is limited only by your endpoint's CPU, memory, and scaling configuration. This is a key advantage over shared inference, which is rate-limited to 20 requests/min per API key.

Request Example

=== "Python"

```python
import requests

# Deployment endpoint
url = "https://predict-abc123.run.app/predict"

# Headers with your deployment API key
headers = {"Authorization": "Bearer YOUR_API_KEY"}

# Inference parameters
data = {"conf": 0.25, "iou": 0.7, "imgsz": 640}

# Send image for inference
with open("image.jpg", "rb") as f:
    response = requests.post(url, headers=headers, data=data, files={"file": f})

print(response.json())
```

=== "JavaScript"

```javascript
// Build form data with image and parameters
const formData = new FormData();
formData.append("file", fileInput.files[0]);
formData.append("conf", "0.25");
formData.append("iou", "0.7");
formData.append("imgsz", "640");

// Send image for inference
const response = await fetch(
  "https://predict-abc123.run.app/predict",
  {
    method: "POST",
    headers: { Authorization: "Bearer YOUR_API_KEY" },
    body: formData,
  }
);

const result = await response.json();
console.log(result);
```

=== "cURL"

```bash
curl -X POST \
  "https://predict-abc123.run.app/predict" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "file=@image.jpg" \
  -F "conf=0.25" \
  -F "iou=0.7" \
  -F "imgsz=640"
```

Request Parameters

Parameter	Type	Default	Description
`file`	file	-	Image or video file (required)
`conf`	float	0.25	Minimum confidence threshold
`iou`	float	0.7	NMS IoU threshold
`imgsz`	int	640	Input image size
`normalize`	string	-	Return normalized coordinates

!!! tip "Video Inference"

Dedicated endpoints accept video files in addition to images. Supported video formats (up to 100MB): ASF, AVI, GIF, M4V, MKV, MOV, MP4, MPEG, MPG, TS, WEBM, WMV. Each frame is processed individually and results are returned per frame. Supported image formats (up to 50MB): AVIF, BMP, DNG, HEIC, JP2, JPEG, JPG, MPO, PNG, TIF, TIFF, WEBP.

Response Format

Same as shared inference with task-specific fields.

Pricing

Basic dedicated endpoints are free on all plans. Higher-resource configurations (more vCPUs, more memory, warm start) will offer usage-based pricing in the future.

!!! tip "Cost Optimization"

- Use scale-to-zero (default) so endpoints only run when receiving requests
- Set appropriate max instances for your traffic
- Monitor usage in the [Monitoring](monitoring.md) dashboard

FAQ

How many endpoints can I create?

Endpoint limits depend on plan:

Free: Up to 3 deployments
Pro: Up to 10 deployments
Enterprise: Unlimited deployments

Each model can still be deployed to multiple regions within your plan quota.

Can I change the region after deployment?

No, regions are fixed. To change regions:

Delete the existing endpoint
Create a new endpoint in the desired region

How do I handle multi-region deployment?

For global coverage:

Deploy to multiple regions
Use a load balancer or DNS routing
Route users to the nearest endpoint

What's the cold start time?

Cold start time depends on model size and whether the container is already cached in the region. Typical ranges:

Scenario	Cold Start
Cached container	~5-15 seconds
First deploy/region	~15-45 seconds

The health check uses a 55-second timeout to accommodate worst-case cold starts.

Can I use custom domains?

Custom domains are coming soon. Currently, endpoints use platform-generated URLs.

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