HyperDX
LLM Observability with HyperDX using OpenLIT
To directly send OpenTelemetry metrics and traces generated by OpenLIT SDK from your AI Application to HyperDX, Follow the below steps.
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.
Configure the OpenTelemetry Collector
-
Configure HTTP Receiver: In the
receivers
section of your OpenTelemetry Collector config, ensure thehttp
receiver is set withendpoint: 0.0.0.0:4318
. -
Define Exporters: Add
otlp
exporter to export metrics and traces to HyperDX.Replace:
YOUR_HYPERDX_API_KEY_HERE
with the your HyperDX API Key.- Example -
x6xx7265-43x3-476x-1112-x9x52x29xxxx
- Example -
-
Assign Exporters to Pipelines: Link
otlphttp/hdx
toservice.pipelines.traces
andservice.pipelines.metrics
for data export.
Complete Configuration Example
Add the following two lines to your application code:
Replace:
YOUR_OTELCOL_URL:4318
with the URL HTTP endpoint of your OpenTelemetry Collector.- Example -
http://127.0.0.1:4318
- Example -
Refer to the OpenLIT Python SDK repository for more advanced configurations and use cases.
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.