Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fix incorrect flag in build performance blogpost #334

Merged
merged 1 commit into from
Apr 29, 2024
Merged

Fix incorrect flag in build performance blogpost #334

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion _posts/2022-11-15-build-performance-metrics.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -200,7 +200,7 @@ To analyze Bazel’s memory footprint on a more granular level, we recommend usi
While [persistent workers](https://bazel.build/remote/persistent) can help to speed up builds significantly (especially for interpreted languages) their memory footprint can be problematic. Bazel collects metrics on its workers, in particular,
the `WorkerMetrics.WorkerStats.worker_memory_in_kb` field tells how much memory workers use (by mnemonic).

The JSON trace profiler also collects persistent worker memory usage during the invocation by passing in the `--experimental_collect_system_network_usage` flag (new in Bazel 6.0).
The JSON trace profiler also collects persistent worker memory usage during the invocation by passing in the `--experimental_collect_worker_data_in_profiler` flag (new in Bazel 6.0).

![Memory profiling for persistant workers with Json trace profiles](/assets/workers-memory-usage.png)

Expand Down