OpenTelemetry has gained prominence as a standardized way to collect and transmit telemetry data across various platforms. With its open-source model and robust ecosystem, many engineering teams are considering it for their observability stack. This post addresses common questions about integrating OpenTelemetry with Snowplow, including how to handle traces, schema configuration, and potential use cases.

Q: Does Snowplow natively support OpenTelemetry?

No, Snowplow does not natively support OpenTelemetry ingestion as a dedicated module. However, Snowplow’s flexible data pipeline architecture allows you to ingest OpenTelemetry data using custom schemas and webhooks. This approach leverages the Snowplow Iglu schema repository to validate and process the data as it flows through the pipeline.

Q: How can I send OpenTelemetry data to Snowplow?

You can send OpenTelemetry data to Snowplow using the following method:

1. Define a JSON schema for OpenTelemetry data: Create a schema that matches the OpenTelemetry data structure in Iglu. This ensures that the incoming data is validated and processed appropriately.
   
   
2. Configure OpenTelemetry to send data via HTTP POST: OpenTelemetry supports HTTP POST requests, which can be directed to a Snowplow Iglu webhook with the schema ID specified in the query string.
   
   
3. Integrate with Snowplow pipeline: The data is ingested and processed through Snowplow’s enrichment pipeline, allowing you to run downstream analysis as usual.
   
   

Example Schema for OpenTelemetry Traces

Ovidiu_Buligan provided a useful starting point based on ClickHouse’s OpenTelemetry schema. Here’s an example structure for an OpenTelemetry trace schema:

{

  "TraceId": "string",

  "SpanId": "string",

  "ParentSpanId": "string",

  "SpanName": "string",

  "SpanAttributes": {

    "attribute_key": "attribute_value"

  },

  "ResourceAttributes": {

    "resource_key": "resource_value"

  },

  "Timestamp": "datetime",

  "Duration": "integer",

  "StatusCode": "string",

  "Events": [

    {

      "EventName": "string",

      "Attributes": {"event_key": "event_value"},

      "Timestamp": "datetime"

    }

  ]

}

Q: How does OpenTelemetry add value to Snowplow data?

OpenTelemetry provides a standardized framework for tracing and observability. Integrating it with Snowplow enables teams to:

• Combine event data with tracing data: Gain a comprehensive view of user behavior and system performance.
  
  
• Streamline data ingestion: Use OpenTelemetry’s collector to aggregate and forward data to multiple destinations, including Snowplow.
  
  
• Maintain data consistency: By using standardized telemetry formats, teams can reduce data transformation complexity.
  
  

Q: What are the potential use cases for OpenTelemetry with Snowplow?

• Application Performance Monitoring (APM): Track user sessions alongside application traces to understand latency and errors.
  
  
• Error Tracking and Debugging: Analyze trace data to identify where specific user events led to errors or slow performance.
  
  
• User Journey Mapping: Visualize complete user sessions, linking page views and actions to underlying system traces.
  
  

Q: What tools can I use to visualize OpenTelemetry data in Snowplow?

• Looker: Build dashboards that integrate trace data alongside Snowplow events.
  
  
• Grafana Tempo: Use Tempo to collect and query trace data while Snowplow provides event-level context.
  
  
• dbt & Redshift: Model OpenTelemetry data with dbt for in-depth analysis.
  
  

Final Thoughts

While Snowplow doesn’t offer native support for OpenTelemetry, its open architecture enables powerful integrations using custom schemas and HTTP webhooks. Whether you’re tracking traces, spans, or other telemetry data, Snowplow’s robust data pipeline can ingest, enrich, and analyze OpenTelemetry data to enhance your observability strategy.