Non-Intrusive Performance Profiling for Entire Software Stacks Based on the Flow Reconstruction Principle


Xu Zhao, Kirk Rodrigues, Yu Luo, Ding Yuan, and Michael Stumm, University of Toronto


Understanding the performance behavior of distributed server stacks at scale is non-trivial. The servicing of just a single request can trigger numerous sub-requests across heterogeneous software components; and many similar requests are serviced concurrently and in parallel. When a user experiences poor performance, it is extremely difficult to identify the root cause, as well as the software components and machines that are the culprits.

This paper describes Stitch, a non-intrusive tool capable of profiling the performance of an entire distributed software stack solely using the unstructured logs output by heterogeneous software components. Stitch is substantially different from all prior related tools in that it is capable of constructing a system model of an entire software stack without building any domain knowledge into Stitch. Instead, it automatically reconstructs the extensive domain knowledge of the programmers who wrote the code; it does this by relying on the Flow Reconstruction Principle which states that programmers log events such that one can reliably reconstruct the execution flow a posteriori.

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@inproceedings {199382,
author = {Xu Zhao and Kirk Rodrigues and Yu Luo and Ding Yuan and Michael Stumm},
title = {{Non-Intrusive} Performance Profiling for Entire Software Stacks Based on the Flow Reconstruction Principle},
booktitle = {12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16)},
year = {2016},
isbn = {978-1-931971-33-1},
address = {Savannah, GA},
pages = {603--618},
url = {},
publisher = {USENIX Association},
month = nov

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