To directly send OpenTelemetry metrics and traces generated by OpenLIT SDK from your AI Application to HyperDX, Follow the below steps.

1

Install OpenTelemetry Collector (Optional)

This step is optional if you have the OpenTelemetry Collector already running.

For detailed installation instructions for the OpenTelemetry Collector , please refer to the OpenTelemetry Collector Documentation. This guide provides comprehensive steps to get you up and running with the Collector on various platforms.

2

Configure the OpenTelemetry Collector

  1. Configure HTTP Receiver: In the receivers section of your OpenTelemetry Collector config, ensure the http receiver is set with endpoint: 0.0.0.0:4318.

    receivers:
      otlp:
        protocols:
          http:
            endpoint: 0.0.0.0:4318
    
  2. Define Exporters: Add otlp exporter to export metrics and traces to HyperDX.

    exporters:
      # HTTP setup
      otlphttp/hdx:
        endpoint: 'https://in-otel.hyperdx.io'
        headers:
        authorization: YOUR_HYPERDX_API_KEY_HERE
        compression: gzip
    
      # gRPC setup (alternative)
      otlp/hdx:
        endpoint: 'in-otel.hyperdx.io:4317'
        headers:
        authorization: YOUR_HYPERDX_API_KEY_HERE
        compression: gzip
    

    Replace:

    1. YOUR_HYPERDX_API_KEY_HERE with the your HyperDX API Key.
      • Example - x6xx7265-43x3-476x-1112-x9x52x29xxxx
  3. Assign Exporters to Pipelines: Link otlphttp/hdx to service.pipelines.traces and service.pipelines.metrics for data export.

    service:
      pipelines:
        traces:
          receivers: [ otlp ]
          exporters: [ otlphttp/hdx ]
        metrics:
          receivers: [ otlp ]
          exporters: [ otlphttp/hdx ]
    

Complete Configuration Example

3

Add the following two lines to your application code:

import openlit

openlit.init(
  otlp_endpoint="YOUR_OTELCOL_URL:4318", 
)

Replace:

  1. YOUR_OTELCOL_URL:4318 with the URL HTTP endpoint of your OpenTelemetry Collector.
    • Example - http://127.0.0.1:4318

Refer to the OpenLIT Python SDK repository for more advanced configurations and use cases.

4

Start monitoring using a pre-built HyperDX dashboard

You can directly import a pre-built dashboard using this URL: here

This is an unsaved dashboard URL. When you click on it, the dashboard will open in your own HyperDX instance. You can then choose to save it, and it will be added to your own HyperDX instance.