Link to this sectionMonitoring#

Ultralytics Platform provides monitoring for deployed endpoints. Track request metrics, view logs, and check health status with automatic polling.

Link to this sectionDeployments Dashboard#

The Deploy page in the sidebar serves as the monitoring dashboard for all your deployments. It combines the world map, overview metrics, and deployment management in one view. See Dedicated Endpoints for creating and managing deployments.

graph TB
    subgraph Dashboard
        Map[World Map] --- Cards[Overview Cards]
        Cards --- List[Deployments List]
    end
    subgraph "Per Deployment"
        Metrics[Metrics Row]
        Health[Health Check]
        Logs[Logs Tab]
        Code[Code Tab]
        Predict[Predict Tab]
    end
    List --> Metrics
    List --> Health
    List --> Logs
    List --> Code
    List --> Predict

    style Dashboard fill:#f5f5f5,color:#333
    style Map fill:#2196F3,color:#fff
    style Cards fill:#FF9800,color:#fff
    style List fill:#4CAF50,color:#fff

Link to this sectionOverview Cards#

Four summary cards at the top of the page show:

Link to this sectionWorld Map#

The interactive world map shows:

• Region pins for all 43 available regions
• Green pins for deployed regions
• Animated blue pins for regions with active deployments in progress
• Pin size varies based on deployment status and latency

Link to this sectionDeployments List#

Below the overview cards, the deployments list shows all endpoints across your projects. Use the view mode toggle to switch between:

Link to this sectionPer-Deployment Metrics#

Each deployment card (in cards view) shows real-time metrics:

Link to this sectionMetrics Row#

Metrics are fetched from the sparkline API endpoint and refresh every 60 seconds.

Link to this sectionHealth Check#

Running deployments show a health check indicator:

Health checks auto-retry every 20 seconds when unhealthy. Click the refresh icon to manually trigger a health check. The health check uses a 55-second timeout to accommodate cold starts on scale-to-zero endpoints.

Link to this sectionLogs#

Each deployment card includes a Logs tab for viewing recent log entries:

Link to this sectionLog Entries#

Each log entry shows:

The UI shows the 20 most recent entries. The API defaults to 50 entries per request (max 200).

Link to this sectionCode Examples#

Each deployment card includes a Code tab showing ready-to-use API code with your actual endpoint URL and API key:

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())

Link to this sectionDeployment Predict#

The Predict tab on each deployment card provides an inline predict panel — the same interface as the model's Predict tab, but running inference through the deployment endpoint instead of the shared service. This is useful for testing a deployed endpoint directly from the browser. See Inference for parameter details and response formats.

Link to this sectionAPI Endpoints#

Link to this sectionMonitoring Overview#

GET /api/monitoring

Returns aggregated metrics for all deployments owned by the authenticated user. Workspace-aware via optional owner query parameter.

Link to this sectionDeployment Metrics#

GET /api/deployments/{deploymentId}/metrics?sparkline=true&range=24h

Returns sparkline data and summary metrics for a specific deployment. Refresh interval: 60 seconds.

Link to this sectionDeployment Logs#

GET /api/deployments/{deploymentId}/logs?limit=50&severity=ERROR,WARNING

Returns recent log entries with optional severity filter and pagination.

Link to this sectionDeployment Health#

GET /api/deployments/{deploymentId}/health

Returns health check status with response latency.

{
    "healthy": true,
    "status": 200,
    "latencyMs": 142,
    "serverTiming": { "db": 8, "ping": 142, "total": 150 }
}

Link to this sectionPerformance Optimization#

Use monitoring data to optimize your deployments:

Link to this sectionFAQ#

Link to this sectionHow long is data retained?#

Link to this sectionCan I set up external monitoring?#

Yes, endpoint URLs work with external monitoring tools:

• Uptime monitoring (Pingdom, UptimeRobot)
• APM tools (Datadog, New Relic)
• Custom health checks via the /health endpoint

Link to this sectionHow accurate are the latency numbers?#

Latency metrics measure:

• P50: Median response time
• P95: 95th percentile
• P99: 99th percentile

These represent server-side processing time, not including network latency to your users.

Link to this sectionWhy are my metrics delayed?#

Metrics have a ~2 minute delay due to:

• Metrics aggregation pipeline
• Aggregation windows
• Dashboard caching

For real-time debugging, check logs which are near-instant.

Link to this sectionCan I monitor multiple endpoints together?#

Yes, the deployments page shows all endpoints with aggregated overview cards. Use the table view to compare performance across deployments.