Exotic Trace Shapes

OpenTelemetry and Beelines are designed to trace synchronous activities, such as web application and API calls, based on the assumption that transactions begin with a user request and end with a response. While these assumptions work for most traffic, there are application flows that deviate significantly, leading to "exotic" trace shapes, such as batch processing, stream processing, and machine learning activities, which do not fit neatly into the typical request-response pattern. These types of traces can be continuous or excessively long, making it challenging to find value in them during aggregate analysis or visual representation. The text explores various strategies to adapt these non-conforming traces into more manageable and meaningful forms, such as breaking traces based on time or item count, starting new traces for each job, or using summary spans to encapsulate job activities. By managing trace identifiers strategically, organizations can apply sampling approaches to optimize the observability of their systems while minimizing data volume and cost, particularly with tools like Refinery and Honeycomb. The text also offers code examples and considerations for handling different trace shapes, emphasizing the flexibility and necessity of adapting tracing practices to diverse application patterns.