The silent eBPF revolution is well underway. eBPF is used across the cloud-native world to enable faster and more customizable computing, moving custom logic into the kernel safely and maintainably.
Different profiling tools are essential to pinpointing the root cause of performance problems in eBPF code. Blind optimizations lead to needless complexity, emphasizing the importance of profiling.
Creating benchmarks is crucial to measuring performance optimizations for eBPF code. Continuous benchmarking with tools like Bencher helps prevent performance regressions before release.
Collection
[
|
...
]