Linux System Performance Tuning: Optimizing CPU, Memory, and Disk

Introduction

Linux is a powerful and flexible operating system, widely used in servers, embedded systems and even personal computers. However, even the best-configured system can face performance bottlenecks over time. Performance tuning is crucial to ensuring efficient operation of Linux systems, which can optimize resource utilization and avoid unnecessary slowdowns.

This guide provides a Linux performance tuning method that focuses on three key areas: CPU, memory, and disk optimization. Whether you are a system administrator, DevOps engineer, or Linux enthusiast, understanding and implementing these optimizations will help increase system response, reduce resource waste, and ensure the system runs smoothly.

Understand system performance indicators

Before you can further optimize, be sure to understand system performance metrics. Monitoring these metrics allows us to diagnose performance issues and make informed adjustment decisions.

Key Performance Indicators (KPIs) - CPU Usage: The percentage of CPU time taken by the process.

• Average load: the number of processes waiting for CPU time.
• Memory Usage: The amount of used and available RAM.
• Disk I/O Waiting: The time the process waits for disk access.
• Swap partition usage: The amount of virtual memory being used.
• Context Switch: Number of process switching times per second.
• Disk Throughput: Read/write speed and latency.

Performance Monitoring Tool Linux provides a variety of tools to measure these metrics:

• CPU and memory monitoring: top, htop, mpstat
• Disk performance analysis: iostat, iotop, dstat
• System-level monitoring: vmstat, sar
• Performance analysis and tracking: perf, strace
• Process and resource management: nice, ulimit, cgroups

CPU performance tuning

CPU bottlenecks can occur due to high process load, inefficient scheduling, or contention for CPU resources. Here is how to optimize CPU performance.

Identify CPU bottlenecks Use the following command to diagnose CPU problems:

top htop mpstat -P ALL 1 sar -u 5

• High load average and low CPU usage indicate I/O waiting issues.
• High CPU usage represents CPU-intensive processes.

Optimized Process Scheduling Linux uses a Fully Fair Scheduler (CFS) to allocate CPU time. You can manually adjust process priorities using the following command:

nice -n 10 process_name renice -n -5 -p PID

Use taskset to bind the process to a specific CPU:

taskset -c 0,1 process_name

Limit CPU Usage To prevent processes from consuming too much CPU, please use cpulimit:

cpulimit -l 50 -p PID

For containerized environments, use cgroups:

cgcreate -g cpu:/limitedgroup echo 50000 > /sys/fs/cgroup/cpu/limitedgroup/cpu.cfs_quota_us cgexec -g cpu:limitedgroup process_name

Kernel parameter tuning and adjusting kernel parameters can improve CPU efficiency:

sysctl -w kernel.sched_min_granularity_ns=10000000 sysctl -w kernel.sched_wakeup_granularity_ns=15000000

Memory performance optimization

Memory issues can severely slow down the system, resulting in overswitching and high latency.

Diagnosing memory usage Use these tools to check memory statistics:

free -m vmstat 5 smem

Find high swap partition usage (si and so in vmstat), which indicates memory pressure.

Optimize swap partition usage - Check swap partition performance:

swapon -s

• Adjust the tendency of swap partitions:

sysctl -w vm.swappiness=10

• Use compression swap partitions zswap or zram:

modprobe zram echo 1 > /sys/block/zram0/reset

Manage caches and buffers To free up memory, clear unused caches:

sync; echo 3 > /proc/sys/vm/drop_caches

Adjust kernel buffer behavior:

sysctl -w vm.dirty_ratio=20 sysctl -w vm.dirty_background_ratio=5

Big Page Optimization For applications such as databases, enable Big Pages:

echo 1024 > /proc/sys/vm/nr_hugepages

Disk I/O performance tuning

Disk performance is critical to databases, file servers, and applications that handle large amounts of data.

Measure disk performance - Check I/O activity:

iostat -x 5 iotop

• Benchmark disk performance:

fio --name=seqwrite --rw=write --bs=128k --size=1G --numjobs=4 --runtime=60

File system optimization - Use optimized file systems (ext4, XFS, btrfs).

• Enable logging only if needed:

tune2fs -O has_journal /dev/sdX

• Use noatime and nodiratime mount options:

mount -o remount,noatime,nodiratime /dev/sdX /mnt

Disk Scheduler Optimizes I/O Scheduler for Change of SSD:

echo noop > /sys/block/sda/queue/scheduler

For HDD:

echo cfq > /sys/block/sda/queue/scheduler

RAID and LVM Optimization - Use RAID 10 for better read/write performance.

• Optimize LVM striping:

lvcreate -i 2 -I 256 -L 10G -n lv_name vg_name

SSD Optimization - Enable TRIM:

fstrim -v /

• Optimize mount settings:

mount -o discard,defaults /dev/sdX /mnt

General system optimization strategy

• Adjust kernel parameters:

sysctl -w net.core.somaxconn=1024 sysctl -w fs.file-max=100000

• Use ulimit to prevent resource exhaustion:

ulimit -n 100000

• Disable unnecessary services:

systemctl disable service_name

Performance Tuning Case Study

High CPU load on web server - High php-fpm CPU usage is identified.

• Use taskset to allocate the load.
• Implementing caching reduces CPU usage by 40%.

Excess Disk I/O on Database Server - Move logs to separate disks.

• Optimize PostgreSQL shared_buffers and work_mem.
• Switching to SSD increases query time by 60%.

in conclusion

Performance tuning is an ongoing process involving monitoring, analysis and optimization. By following the best practices outlined in this guide, you can ensure that your Linux system runs smoothly and efficiently.

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