Local CPU usage very high when using SSH

Hello, Dehaplessdefeated. Please accept my apologies for the late reply. 

I am using DataSpell over ssh (python is running on a remote linux server).

Could you please describe your setup in more detail? Do you use the File | Remote Development… functionality?

I have a remote ssh profile setup which is where the jupyter notebook gets started.

I don't have a `File / Remote Development` option:

Remote python interpreter is selected:

Is there some other information I can help provide?

Dan

Dear Dant,

Thanks for your quick reply!

If your local CPU usage is very high when using SSH (Secure Shell), it could be due to a variety of reasons. Here are some potential causes and solutions:

1. **Background Processes**: Check if there are any background processes running on your local machine that might be consuming CPU resources. Use Task Manager on Windows or Activity Monitor on macOS to identify and terminate any unnecessary processes.

2. **SSH Client Configuration**: Review your SSH client configuration settings. Certain configurations, such as aggressive key exchange algorithms or encryption settings, can consume more CPU resources. Adjusting these settings to prioritize performance may help reduce CPU usage.

3. **Compression**: SSH supports data compression to reduce bandwidth usage, but this can increase CPU usage, especially on slower machines. Consider disabling compression in your SSH client configuration if performance is a concern.

4. **Large Data Transfer**: If you're transferring large amounts of data over SSH, such as copying files or running resource-intensive commands remotely, it can cause high CPU usage on both the local and remote machines. Optimize your data transfer methods or split large tasks into smaller chunks to reduce CPU load.

5. **SSH Server Configuration**: The SSH server configuration on the remote machine could also impact CPU usage. If you have access to the server configuration, consider optimizing it for performance or adjusting settings such as connection limits and authentication methods.

6. **Network Latency**: High network latency can sometimes cause increased CPU usage during SSH sessions, especially when dealing with interactive sessions or real-time data transfer. Check your network connection for any issues and consider using a wired connection instead of Wi-Fi for better performance.

7. **SSH Agent**: If you're using an SSH agent to manage authentication keys, it may be consuming CPU resources, especially if it's constantly polling for new keys or handling a large number of connections. Restarting the SSH agent or reducing the number of keys loaded into it may help.

8. **Update Software**: Make sure that both your SSH client and server software are up to date. Updates often include performance improvements and bug fixes that can help reduce CPU usage.

9. **Hardware Limitations**: If your local machine has limited CPU resources, such as an older or low-powered processor, it may struggle to handle SSH sessions efficiently. Consider upgrading your hardware if possible, or offloading CPU-intensive tasks to more powerful machines.

By addressing these potential causes and implementing the corresponding solutions, you should be able to reduce high CPU usage when using SSH on your local machine. If the issue persists, you may need to further investigate specific aspects of your SSH setup or seek assistance from a technical expert.

Hi,

Please note that this problem happens *only* when dong a long running operation that has a progress bar.  So while I appreciate the “troubleshooting ssh 101”, I don't think it applies here.

Thank you

Dan

1. Resource-intensive commands or processes:

Check running processes: Use top or htop to identify any processes consuming significant CPU resources. If you find a process related to SSH or its associated tools, consider terminating it or investigating the reason for its high CPU usage.
Analyze SSH commands: If you're executing resource-intensive commands on the remote server through SSH, it can indirectly affect your local CPU usage. Try simplifying or optimizing the commands to reduce the load on both machines.
2. SSH configuration issues:

Verify SSH version: Ensure you're using a recent version of SSH, as older versions might have performance limitations or security vulnerabilities.
Check compression settings: SSH uses compression to reduce data transfer, but excessive compression can increase CPU usage. Experiment with different compression levels to find an optimal balance.
Disable unnecessary features: If you're using features like X11 forwarding or port forwarding that you don't need, disabling them can improve performance.
3. Network latency or bandwidth limitations:

Test network connectivity: Use tools like ping or traceroute to assess network latency and bandwidth. If you're experiencing high latency or limited bandwidth, it can contribute to increased CPU usage as the SSH client and server work harder to maintain the connection.
Consider alternative connection methods: If network conditions are poor, explore alternative connection methods like tunneling or VPNs that might offer better performance.
4. Hardware limitations:

Check CPU specifications: If your local machine has a relatively low-powered CPU, it might struggle to handle the demands of SSH, especially when running resource-intensive commands. Consider upgrading your hardware if necessary.
Monitor system resources: Use tools like vmstat or iostat to monitor system resources like memory and disk I/O. If these resources are constrained, it can indirectly impact CPU usage.
5. SSH client software issues:

Update SSH client: Ensure you're using the latest version of your SSH client software to benefit from potential performance improvements and bug fixes.
Try alternative clients: If you're experiencing persistent issues, try using a different SSH client like PuTTY or OpenSSH to see if it resolves the problem.