Readit Newsy_uuki commented on tcpulse: A TCP/UDP load generator that provides fine-grained, flow-level control github.com/yuuki/tcpulse... · Posted by u/y_uuki
Any possibility of using it with diodes? I've used iperf for this (two separate instances), but iperf2 doesn't support this. We've also written our own in Rust, tightly coupled to our needs, but if there are better tools out there, well, we'd be silly not to investigate. Thanks!
Currently tcpulse only supports a `pingpong` mode, so true one-way (“diode”) transfers aren’t available out of the box. That said, the design is simple enough that you could introduce an option or wrapper to lock the flow in one direction and implement a diode mode. Happy to review a PR if someone wants to add it
Any idea how this differs from iperf?
iperf3 is a link “speedometer” – spin it up between two hosts, crank -P or -u -b, and it tells you max TCP/UDP throughput (and jitter/loss if you like).
tcpulse is a fine-grained traffic “microscope” – you dial exact CPS or concurrent sockets, spray dozens of targets from one client, and get p90/p95/p99 latencies per flow.
Use iperf3 for a quick bandwidth check; use tcpulse when you need repeatable, controlled connection patterns and detailed latency stats across many backends.
Cool little tool! Is it possible for the server to also print out performance metrics of each peer which it is connected to?
Thank you!
No, tcpulse only measures and prints out metrics from the client side, not the server side. However, since multiple clients each output their own measurement results, this effectively results in performance metrics being output for each peer.
y_uuki commented on The AIOps library for removing automatically failure-unrelated metrics github.com/ai4sre/metrics... · Posted by u/y_uuki
MetricSifter is a feature reduction framework designed to accurately identify anomalous metrics caused by faults for enhancing fault localization. Our key insight is that the change point times inside the failure duration are close to each other for the failure-related metrics. MetricSifter detects change points per metric, localizes the time frame with the highest change point density, and excludes metrics with no change points in that time frame. The offline change point detection is implemented by ruptures, and the segmentation of the detected change points is based on kernel density estimation (KDE).