The philosophy behind "Stroll": continuous learning, curiosity‑driven, and practice‑focused.
The author tests Tencent's WorkBuddy AI assistant to generate a shell script for batch checking RAID card and disk health via storcli64 across multiple servers, noting the first draft took 12 minutes and required three correction rounds before passing code review and production validation.
When a service's response time spikes from milliseconds to hundreds of milliseconds, this guide walks you through a step‑by‑step Linux toolchain—ping, mtr, iftop, netstat, sysctl, and BBR—to pinpoint the root cause of network latency without jumping straight to packet captures.
This guide walks you through installing and using tcpdump and Wireshark on Linux, showing how to capture packets, filter traffic, analyze protocols, and combine command‑line and GUI tools for effective network performance debugging.
This article explains a reproducible Linux network performance assessment covering latency, throughput, bandwidth, and packet loss, introduces built‑in and benchmark tools such as ping, ss, nstat, ethtool, iperf3, netperf and wrk, and provides a step‑by‑step workflow to generate a complete evaluation report.
This article walks through a systematic network troubleshooting workflow on Linux, detailing how to use ss to inspect sockets, ip for routing and address information, tc for traffic control at the link layer, and ethtool for hardware diagnostics, with concrete command examples and practical tips.
The article walks through the Linux packet lifecycle—from the send() system call, through the transport and network layers, to the NIC driver—explaining each step, virtual‑network abstractions, and the essential bandwidth, latency, loss, conntrack, and socket buffer metrics to monitor when problems arise.
The article walks through six concrete, reproducible methods for diagnosing and improving Linux CPU performance—including using perf for profiling, binding processes to specific cores, adjusting scheduling priorities, setting the CPU governor, leveraging NUMA awareness, and fine‑tuning kernel scheduler parameters—while showing real command examples and measured impact.
The article explains the low‑level reasons why uninterruptible (D) and zombie (Z) processes inflate Linux load average, shows how to identify them with ps, wchan and /proc tools, and provides step‑by‑step diagnostics, handling strategies, kernel and I/O scheduler tweaks, and preventive measures to keep the system responsive.
Learn the theory behind Linux CPU usage metrics, how the kernel’s jiffies and /proc/stat values are interpreted, the formula for calculating utilization over intervals, and practical commands like top, ps, and pidstat to observe real‑time CPU performance on servers and desktops.
This article explains the key CPU performance metrics on Linux—including load average, CPU usage percentages, and process states—showing how to interpret top, ps, uptime, and mpstat outputs and how to differentiate between load and utilization in various workload scenarios.
