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Clarify sizes and file locations.

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Adin Scannell 2019-05-13 14:50:57 -07:00 committed by Adin Scannell
parent 8b83365ba7
commit 5dcfe3c758
1 changed files with 7 additions and 6 deletions
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13
content/docs/architecture_guide/performance.md
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@ -235,17 +235,18 @@ The high costs of VFS operations can manifest in benchmarks that execute many
such operations in the hot path for serviing requests, for example. The above
figure shows the result of using gVisor to serve small pieces of static content
with predictably poor results. This workload represents `apache` serving a
single file sized 100k to a client running [ApacheBench][ab] with varying levels
of concurrency. The high overhead comes principally from the VFS implementation
that needs improvement, with several internal serialization points (since all
requests are reading the same file). Note that some of some of network stack
performance issues also impact this benchmark.
single file sized 100k from the container image to a client running
[ApacheBench][ab] with varying levels of concurrency. The high overhead comes
principally from the VFS implementation that needs improvement, with several
internal serialization points (since all requests are reading the same file).
Note that some of some of network stack performance issues also impact this
benchmark.
{{< graph id="ffmpeg" url="/performance/ffmpeg.csv" title="perf.py media.ffmpeg --runtime=runc --runtime=runsc" >}}
For benchmarks that are bound by raw disk I/O and a mix of compute, file system
operations are less of an issue. The above figure shows the total time required
for an `ffmpeg` container to start, load and transcode an input video.
for an `ffmpeg` container to start, load and transcode a 27MB input video.
[ab]: https://en.wikipedia.org/wiki/ApacheBench
[benchmark-tools]: https://gvisor.googlesource.com/benchmark-tools