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Diffstat (limited to 'doc/book/src/design')
| -rw-r--r-- | doc/book/src/design/benchmarks.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/doc/book/src/design/benchmarks.md b/doc/book/src/design/benchmarks.md index 5a63f902..a219a3ce 100644 --- a/doc/book/src/design/benchmarks.md +++ b/doc/book/src/design/benchmarks.md @@ -19,7 +19,7 @@ This serie of benchmarks quantifies the impact of this design choice. We start with a controlled environment, all the instances are running on the same (powerful enough) machine. To control the network latency, we simulate the network with [mknet](https://git.deuxfleurs.fr/trinity-1686a/mknet) (a tool we developped, based on `tc` and the linux network stack). -To mesure S3 endpoints latency, we use our own tool [s3lat](git.deuxfleurs.fr/quentin/s3lat/) to observe only the intra-cluster latency and not some contention on the nodes (CPU, RAM, disk I/O, network bandwidth, etc.). +To mesure S3 endpoints latency, we use our own tool [s3lat](https://git.deuxfleurs.fr/quentin/s3lat/) to observe only the intra-cluster latency and not some contention on the nodes (CPU, RAM, disk I/O, network bandwidth, etc.). Compared to other benchmark tools, S3Lat sends only one (small) request at the same time and measures its latency. We selected 5 standard endpoints that are often in the critical path: ListBuckets, ListObjects, GetObject, PutObject and RemoveObject. |