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

    classDef proc fill:#2196F3,color:#fff
    classDef out fill:#9C27B0,color:#fff
    classDef error fill:#F44336,color:#fff
    classDef extern fill:#607D8B,color:#fff
    class Creating,Deploying,Stopping proc
    class Ready out
    class Failed error
    class Stopped extern

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

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

| 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        |

| 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          |

| 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   |

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

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`).

https://predict-abc123.run.app

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

    classDef out fill:#9C27B0,color:#fff
    classDef error fill:#F44336,color:#fff
    classDef extern fill:#607D8B,color:#fff

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

Authorization: Bearer YOUR_API_KEY

```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
// 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);
```

```bash
curl -X POST \
  "https://predict-abc123.run.app/predict" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F "[email protected]" \
  -F "conf=0.25" \
  -F "iou=0.7" \
  -F "imgsz=640"
```

Dedicated endpoints accept both images and videos via the `file` parameter.

- **Image formats** (up to 100 MB): AVIF, BMP, DNG, HEIC, JP2, JPEG, JPG, MPO, PNG, TIF, TIFF, WEBP
- **Video formats** (up to 100 MB): ASF, AVI, GIF, M4V, MKV, MOV, MP4, MPEG, MPG, TS, WEBM, WMV

Each video frame is processed individually and results are returned per frame. You can also pass a public image URL or a base64-encoded image via the `source` parameter instead of `file`.