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Guided Exercise: Adjusting Tuning Profiles

In this exercise, you will tune a server’s performance by activating the tuned service and applying a tuning profile.

Outcomes

You should be able to configure a system to use a tuning profile.

Log in as the student user on workstation using student as the password.

From workstation, run the lab tuning-profiles start command. The command runs a start script to determine if the servera host is reachable on the network.

[student@workstation ~]$ lab tuning-profiles start
  1. From workstation, use SSH to log in to servera as the student user. The systems are configured to use SSH keys for authentication, therefore a password is not required.

    [student@workstation ~]$ ssh student@servera
    ...output omitted...
    [student@servera ~]$ 
    
  2. Verify that the tuned package is installed, enabled, and started.

    1. Use yum to confirm that the tuned package is installed.

      [student@servera ~]$ yum list tuned
      ...output omitted...
      Installed Packages
      tuned.noarch                    2.10.0-15.el8                    @anaconda
      
    2. The systemctl is-enabled tuned command shows whether the service is enabled.

      [student@servera ~]$ systemctl is-enabled tuned
      enabled
      
    3. The systemctl is-active tuned command show whether the service is currently running.

      [student@servera ~]$ systemctl is-active tuned
      active
      
  3. List the available tuning profiles and identify the active profile. If sudo prompts for a password, enter student after the prompt.

    [student@servera ~]$ sudo tuned-adm list
    [sudo] password for student: student
    Available profiles:
    - balanced               - General non-specialized tuned profile
    - desktop                - Optimize for the desktop use-case
    - latency-performance    - Optimize for deterministic performance at the cost of
                               increased power consumption
    - network-latency        - Optimize for deterministic performance at the cost of
                               increased power consumption, focused on low latency
                               network performance
    - network-throughput     - Optimize for streaming network throughput, generally
                               only necessary on older CPUs or 40G+ networks
    - powersave              - Optimize for low power consumption
    - throughput-performance - Broadly applicable tuning that provides excellent
                               performance across a variety of common server workloads
    - virtual-guest          - Optimize for running inside a virtual guest
    - virtual-host           - Optimize for running KVM guests
    Current active profile: virtual-guest
    
  4. Change the current active tuning profile to powersave, then confirm the results. If sudo prompts for a password, enter student after the prompt.

    1. Change the current active tuning profile.

      [student@servera ~]$ sudo tuned-adm profile powersave
      
    2. Confirm that powersave is the active tuning profile.

      [student@servera ~]$ sudo tuned-adm active
      Current active profile: powersave
      
  5. Exit from servera.

    [student@servera ~]$ exit
    logout
    Connection to servera closed.
    [student@workstation ~]$
    

Finish

On workstation, run the lab tuning-profiles finish script to finish this exercise.

[student@workstation ~]$ lab tuning-profiles finish

This concludes the guided exercise.

Revision: rh134-8.2-f0a9756