Ixia Inventory Explorer is Flask based tool for managing all Ixia Inventory that user might have from a single UI. Project is UI written over open IxOS API's that we can find at https://github.com/OpenIxia/IxOS/tree/master/Utilities/Python

REST API references at

https://(chassisIp)/chassis/swagger/index.html
https://(chassisIp)/platform/swagger/index.html

Why use this ?

• Lab Ixia Inventory Explorer tool for Administrators/ NE’s/ SE’s.
• Chassis, Cards, Ports, Licensing, Sensor, Chassis Utilization Metrics all under one tool.
• Ability to be deployed on-prem since it is docker containerized.

Functionality

Ixia Inventor Explorer offers a range of features that make it an ideal tool for lab network engineers, lab administrators, and Keysight SE’s.

Some of the key features include:

• Unified preview of available Ixia Chassis with custom tagging feature
• License statistics for every Ixia Chassis
• Card Statistics with custom tagging feature
• Port Statistics for owner, type of optic
• One-click IxOS chassis log collection
• Download Statistics as csv for Ixia Support Team
• On-demand data refresh
• Column based filtering.

Prerequisites

• Linux Server with docker installed
• Linux server with internet access to https://github.com/Keysight/
• Linux Server with access to chassis that one wants to monitor

Installation and Running the tool:

Pull Docker Image.
docker pull ghcr.io/keysight/ixiainventoryexplorer:latest_1.0

** This is a linux/amd64 type of docker image. If you need an idea for different OS Architecture types, you must build it yourself from the source code.

** Let us create volume to persist the data**
docker volume create <volume-name>

For instance: docker volume create iie-data

Run Docker Image.

docker run -dp 80:3000 --mount type=volume,src=<volume-name>,target=/python-docker ghcr.io/keysight/ixiainventoryexplorer:latest_1.0
For instance: docker run -dp 80:3000 --mount type=volume,src=iie-data,target=/python-docker ghcr.io/keysight/ixiainventoryexplorer:latest_1.0

Then, go to browser and http://host:port/
In this case host is where you are running the docker image and port is what you have specified while executing docker run command. For instance, in the above installation, we have exposed port 80 on the host to run the tool.

Disclaimer:

Please note that the Python-based tool provided here is offered as-is, without any warranty or guarantee of fitness for any particular purpose. The author of this tool will not be able to provide support for feature requests, bug fixes, or any other modifications to the code. However, customers are welcome to use the code provided and modify it as they see fit for their own use.

For feedback please reach out to [email protected]