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authorGitLab Bot <gitlab-bot@gitlab.com>2021-07-20 12:55:51 +0300
committerGitLab Bot <gitlab-bot@gitlab.com>2021-07-20 12:55:51 +0300
commite8d2c2579383897a1dd7f9debd359abe8ae8373d (patch)
treec42be41678c2586d49a75cabce89322082698334 /doc/development/performance.md
parentfc845b37ec3a90aaa719975f607740c22ba6a113 (diff)
Add latest changes from gitlab-org/gitlab@14-1-stable-eev14.1.0-rc42
Diffstat (limited to 'doc/development/performance.md')
-rw-r--r--doc/development/performance.md2
1 files changed, 1 insertions, 1 deletions
diff --git a/doc/development/performance.md b/doc/development/performance.md
index 84b3a8f1092..e59f7fb154b 100644
--- a/doc/development/performance.md
+++ b/doc/development/performance.md
@@ -120,7 +120,7 @@ allowing you to profile which code is running on CPU in detail.
It's important to note that profiling an application *alters its performance*.
Different profiling strategies have different overheads. Stackprof is a sampling
profiler. It samples stack traces from running threads at a configurable
-frequency (e.g. 100hz, that is 100 stacks per second). This type of profiling
+frequency (for example, 100hz, that is 100 stacks per second). This type of profiling
has quite a low (albeit non-zero) overhead and is generally considered to be
safe for production.