When a Logger gets called directly via contextual logging, it has to do its own
verbosity check and therefore needs to know what the intended verbosity level
is.
This used to work previously because all verbosity checks were done in klog
before invoking the Logger.
We don't need to worry about data loss once the data has been written to an
output stream. Calling fsync unnecessarily has been the reason for performance
issues in the past.
The recent regression https://github.com/kubernetes/kubernetes/issues/107033
shows that we need a way to automatically measure different logging
configurations (structured text, JSON with and without split streams) under
realistic conditions (time stamping, caller identification).
System calls may affect the performance and thus writing into actual files is
useful. A temp dir under /tmp (usually a tmpfs) is used, so the actual IO
bandwidth shouldn't affect the outcome. The "normal" json.Factory code is used
to construct the JSON logger when we have actual files that can be set as
os.Stderr and os.Stdout, thus making this as realistic as possible.
When discarding the output instead of writing it, the focus is more on the rest
of the pipeline and changes there can be investigated more reliably.
The benchmarks automatically gather "log entries per second" and "bytes per
second", which is useful to know when considering requirements like the ones
from https://github.com/kubernetes/kubernetes/issues/107029.
The benchmark depends on k8s.io/api (for v1.Container). Such a dependency is
not desirable for k8s.io/component-base/logs, even if it's just for
testing. The solution is to create a separate directory where such a dependency
isn't a problem.
The alternative, a separate package with its own go.mod file under
k8s.io/component-base/logs wouldd have been more complicated to maintain (yet
another go.mod file and different whitelisted dependencies).
