If you are using a NagVis Docker container, the location of the NagVis configuration files may be different from a traditional NagVis installation. To locate the host icon size code file in a NagVis Docker container, you can follow these steps:

1. Start a shell session in the running NagVis container by running the following command:

   pythonCopy code
   docker exec -it <container_name_or_id> /bin/bash


   Replace “<container_name_or_id>” with the name or ID of your NagVis container.

2. Once you are in the container shell, navigate to the NagVis configuration directory by typing the following command:

   bashCopy code
   cd /opt/nagvis/etc/


   Note: The exact path to the NagVis configuration directory may vary depending on how the container was configured.

3. In the configuration directory, you should see a file named “nagvis.ini.php”. This file contains the NagVis configuration settings, including the location of the object configuration files.
4. Open the “nagvis.ini.php” file in a text editor and look for the “[paths]” section. This section contains the path to the NagVis object configuration files.
5. By default, the object configuration files are located in the “etc/objects/” directory. Navigate to this directory by typing the following command:

   bashCopy code
   cd etc/objects/


6. In the “etc/objects/” directory, you should see a file named “objects.ini.php”. This file contains the definitions for the NagVis objects, including the host icon sizes.
7. Open the “objects.ini.php” file in a text editor and search for the “[iconsizes]” section. This section contains a list of available host icon sizes and their corresponding labels.
8. To add or modify host icon sizes, edit the values in this section as needed.
9. Save the “objects.ini.php” file and restart the NagVis service to apply the changes.

Note that modifying the NagVis configuration files requires knowledge of the NagVis system and should be done with caution to avoid introducing errors. Make a backup of the original file before making any changes and test the changes thoroughly before using them in a production environment.