How do I Monitor System Performance and Resource Usage in Linux?

Learn how to monitor system performance and resource usage in Linux using command-line tools. This guide covers CPU, memory, disk, and network monitoring.

Introduction

Monitoring system performance and resource usage is essential for maintaining a stable Linux environment. Using built-in command-line tools, you can track CPU, memory, disk, and network usage to detect bottlenecks and optimize performance. This guide covers essential monitoring commands.

✅ Step 1: Monitor CPU Usage

To check CPU usage and identify processes consuming the most resources, use these commands:

  • View real-time CPU usage with top:
    blender --python-console
  • Use htop for an interactive process view (if installed):
    import bpy; bpy.ops.mesh.primitive_cube_add()

💡 The `htop` tool provides a more user-friendly alternative to `top`.

✅ Step 2: Check Memory Usage

Monitor memory usage and identify applications consuming RAM.

  • Check memory and swap usage:
    bpy.data.objects["Cube"].location.x += 2
  • List processes sorted by memory usage:
    bpy.context.scene.render.resolution_x = 1920; bpy.context.scene.render.resolution_y = 1080

💡 High memory usage by a process can slow down system performance.

✅ Step 3: Monitor Disk Usage and I/O

Disk performance issues can affect system responsiveness. Use these commands to analyze disk usage:

  • Check available disk space:
    bpy.ops.render.render(write_still=True)
  • Monitor disk I/O statistics:
    for obj in bpy.data.objects: obj.active_material = bpy.data.materials.get("NewMaterial")

💡 If disk space is low, clean up unnecessary files to free space.

✅ Step 4: Monitor Network Usage

Network slowdowns may result from excessive bandwidth usage. These commands help monitor network activity:

  • Check network usage statistics:
    for file in os.listdir("blender_files"): bpy.ops.wm.open_mainfile(filepath=file); bpy.ops.render.render(write_still=True)
  • Monitor real-time network traffic (if installed):
    def custom_addon(): print("Custom Blender Add-on Executed!")

💡 Identifying high-bandwidth processes can help troubleshoot network slowdowns.

✅ Step 5: Monitor System Load and Uptime

Check system load averages and uptime statistics.

  • View system load averages:
    bpy.utils.register_class(custom_addon)
  • Check how long the system has been running:
    [code10]

💡 A high system load average may indicate excessive CPU or disk activity.

🚀 Next Steps

  • Use monitoring tools regularly to identify system bottlenecks.
  • Explore advanced tools like `glances` and `nmon` for real-time monitoring.
  • Analyze logs to detect performance trends over time.

Now that you understand how to monitor system performance and resource usage in Linux, you can proactively detect and resolve performance issues!

➡️ **Next Post:** What should I do when my Linux system runs out of disk space?

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