This guide explains how to evaluate and improve Linux server performance by conducting comprehensive CPU, memory, network, and I/O stress tests using tools such as stress, stressapptest, Valgrind, ApacheBench, JMeter, wrk, siege, httperf, and fio, with detailed command examples and result analysis.
This article explains the various pseudo‑random event types that the Android Monkey tool can generate, shows the command‑line parameters for each type, and provides a sample ADB command to set custom event‑type percentages for more realistic mobile app stress testing.
This tutorial walks you through creating a Bash script that periodically captures and displays memory, disk, and CPU utilization on a Linux server, explains the underlying commands, shows how to run the script in a timed loop, and demonstrates adding a stress test for load generation.
This tutorial shows how to create a Bash script that continuously reports memory, disk, and CPU usage percentages, logs the data, and optionally applies a stress test to evaluate system performance under load.
This guide explains why mini‑programs need load testing, outlines three common testing scenarios, describes four test‑type designs, and provides step‑by‑step instructions for using Alibaba Cloud PTS to obtain platform tokens, configure APIs, and run stable, long‑duration pressure tests.
This article explains what Linux load average actually measures, distinguishes it from CPU utilization, describes runnable and uninterruptible states, and demonstrates its behavior through CPU‑intensive, I/O‑intensive, and high‑process‑count scenarios using common monitoring tools.
This article explains what Linux load average actually measures, distinguishes it from CPU utilization, and demonstrates how to interpret and monitor load with practical stress‑test scenarios using tools like uptime, mpstat, and pidstat.
This article demonstrates how to install and run load‑testing tools Artillery and Apache ab, explains their command‑line options, interprets the performance metrics they produce, and provides tips for handling system limits during high‑concurrency tests.
