Aggregate-Driven Trace Visualizations for Performance Debugging
Performance issues in cloud systems are hard to debug. Distributed tracing is a widely adopted approach that gives engineers visibility into cloud systems. Existing trace analysis approaches focus on debugging single request correctness issues but not debugging single request performance issues. Dia...
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Zusammenfassung: | Performance issues in cloud systems are hard to debug. Distributed tracing is
a widely adopted approach that gives engineers visibility into cloud systems.
Existing trace analysis approaches focus on debugging single request
correctness issues but not debugging single request performance issues.
Diagnosing a performance issue in a given request requires comparing the
performance of the offending request with the aggregate performance of typical
requests. Effective and efficient debugging of such issues faces three
challenges: (i) identifying the correct aggregate data for diagnosis; (ii)
visualizing the aggregated data; and (iii) efficiently collecting, storing, and
processing trace data.
We present TraVista, a tool designed for debugging performance issues in a
single trace that addresses these challenges. TraVista extends the popular
single trace Gantt chart visualization with three types of aggregate data -
metric, temporal, and structure data, to contextualize the performance of the
offending trace across all traces. |
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DOI: | 10.48550/arxiv.2010.13681 |