Optimizing CPU usage requires monitoring utilization and adjusting priority, frequency strategy and binding core; 2. Memory optimization should reduce Swappiness, clean caches and rationally configure application memory; 3. Disk I/O optimization includes selecting appropriate scheduler, file system, mount options and RAID/LVM configuration; 4. Network tuning requires adjusting TCP parameters, enabling interrupt merging and balancing interrupt load; 5. System-level optimization recommends turning off redundant services, using chrony synchronization time and tuning kernel parameters, combining tools such as perf and sar to continuously analyze performance bottlenecks, and finally gradually improving system efficiency through baseline comparison, and fully realizing stable and efficient operation of the server.

Linux performance tuning and server optimization are key links to ensure the stable and efficient operation of the system. Whether it is a web server, a database server, or a highly concurrent application service, a reasonable tuning strategy can significantly improve response speed, reduce latency, and make full use of hardware resources. The following introduces practical optimization techniques from several key dimensions.

1. CPU and process scheduling optimization

CPU is the core of system processing capabilities, and optimizing CPU usage can effectively reduce bottlenecks.

• Monitor CPU usage
  Use top , htop , vmstat , mpstat and other tools to view CPU utilization, context switching and waiting status. Focus on %us (user state), %sy (system state) and %wa (I/O wait).

  

• Adjust process priorities
  Use nice and renice to control process priorities, and key services can appropriately increase priorities:

   nice -n -5 ./critical_service.sh

• Enable CPU frequency adjustment strategy
  In performance-first scenarios, set the CPU frequency modulation policy to performance :

  

   cpupower frequency-set -g performance

  For most servers, it is recommended to turn off energy saving mode in the BIOS (such as Intel P-state, C-states).

• Bind CPU core (CPU affinity)
  Use taskset to bind critical processes to specific CPU cores, reducing context switching overhead:

   taskset -c 0,1 java -jar app.jar

2. Memory management and optimization

Insufficient memory will lead to frequent Swap and severely slow down system performance.

• Monitor memory usage
  Use free -h , vmstat , slabtop to view memory usage, focusing on available memory and si/so (Swap in/out).

• Adjust Swappiness
  Reduce unnecessary Swap usage, especially when memory is sufficient:

   sysctl vm.swappiness=10

  Permanently effective write to /etc/sysctl.conf .

• Clean the cache (if necessary)
  When memory pressure is high, the page cache can be manually released (cautionary):

   echo 1 > /proc/sys/vm/drop_caches

• Optimize application memory usage
  For Java and other applications, set the heap memory size (such as -Xmx , -Xms ) reasonably to avoid frequent GC.

3. Disk I/O and file system optimization

Disk I/O is often a performance bottleneck, especially in database and log-intensive applications.

• Select the right I/O scheduler
  For SSDs or virtual machines, it is more efficient to use none or deadline schedulers:

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

  Or set when starting via kernel parameter elevator=deadline .

• Using a high-performance file system
  It is recommended to use ext4 (stable) or XFS (large files, high concurrency performance is good). XFS has more advantages in large-capacity storage and high concurrent write scenarios.

• Mounting option optimization
  Add optimization options in /etc/fstab :

   /dev/sdb1 /data xfs defaults,noatime,nodiratime,barrier=1 0 0

  • noatime, nodiratime : Reduce metadata update overhead
  • barrier=1 : Ensure data integrity (can be considered for closing on SSD, but there are risks)

• RAID and LVM configuration
  Use RAID 10 to improve read and write performance and redundancy. LVM recommends turning on striping to improve throughput.

4. Network performance tuning

Network latency and throughput directly affect service response speed.

• Adjust TCP parameters
  Optimize in /etc/sysctl.conf :

   net.core.rmem_max = 134217728
  net.core.wmem_max = 134217728
  net.ipv4.tcp_rmem = 4096 87380 67108864
  net.ipv4.tcp_wmem = 4096 65536 67108864
  net.ipv4.tcp_tw_reuse = 1
  net.ipv4.tcp_fin_timeout = 30
  net.core.somaxconn = 65535

  Execution sysctl -p takes effect.

• Enable Interrupt Coalescing
  Reduce CPU interrupt overhead, suitable for high throughput scenarios:

   ethtool -C eth0 rx-usecs 50 tx-usecs 50

• Using multi-queue network cards and RPS
  For multi-core systems, enable RPS (Receive Packet Steering) or RFS to balance network interrupt load.

5. System-level comprehensive optimization suggestions

• Close unnecessary services and daemons
  Use systemctl list-unit-files --type=service to view and disable non-essential services such as cups , avahi , bluetooth , etc.

• Time synchronization optimization
  Use chrony instead of ntpd to be more adaptable to virtualized environments and have higher synchronization accuracy.

• Kernel parameter tuning
  Adjust according to the application scenario:

  • Increase the number of file handles:

     fs.file-max = 2097152

  • Increase process limit:

     kernel.pid_max = 65536

• Use performance analysis tools

  • perf : analyze CPU hotspot functions
  • sar (sysstat): historical performance data acquisition
  • iotop : Real-time I/O monitoring
  • nethogs : View network usage by process

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Basically these core points. Linux performance tuning is not achieved overnight, and requires continuous observation, testing and adjustment in combination with specific business loads. The key is to establish baseline performance indicators and then gradually optimize the bottleneck link. Not complicated, but it is easy to ignore details.

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