Distributed systems are widespread in usage. Yet, they continue to be marred by bugs. Distributed tracing is a widely adopted approach that gives engineers visibility into cloud systems. Existing tracing tools support analysis of a single request and are most useful for debugging correctness issues.
However, diagnosing an issue in the processing of a request, requires comparing the execution of a buggy request to a non-buggy request or even an aggregate set of requests. Some issues even require comparing the behavior of two different sets of requests to identify a potential issue. Existing trace analysis tools either do not support these use cases or produce an output that is not understandable.
To rectify this, we propose a new approach for performing trace comparison and aggregation. The key insight of our approach is to derive a text representation for each trace and then perform aggregation and comparison on texts. The benefit of this approach is twofold: we can leverage text summarization and comparison algorithms; the output produced is text which is understandable for users. We present algorithms for generating a text representation from a trace, summarization of these text representations to generate a summary of traces, and comparison of traces.