Lab Exercise 11 – Build Model for Recommendation
This lab exercise provides step-by-step instructions for building the models required to power a recommendation system for relevant runbooks based on incoming tickets. The process involves configuring the organization, runbook tool, and data source, and then building the entity and recommendation models. Once the models are built, the system will provide recommendations for incidents in the console.
Scenario
To enable the recommendation of relevant runbooks based on the incoming tickets, organization has asked building the requisite models which powers the recommendation system.
In this lab, we will showcase the detailed procedure building the model for powering the recommendation system.
Prerequisites
Organization should be configured
Runbook Tool should be configured
Data Source should be configured
Access to Super Admin / Org Admin credentials should be available
Solution
- Open BigFix Runbook AI Web URL and login with Organization Admin credentials.
- Go to Actions and click Build Models.
- Ensure that you have three models appearing on the Build Model screen with respect to your organization as mentioned below:
Entity Model having organization information only
Recommendation Model having organization and module information only
Recommendation Model having organization, module and runbook tool information only.
- Click gear icon to build the Entity Model first. Once entity model build is successful, Recommendation Model Build having organization, module and runbook tool information, needs to be triggered.
- Once the build for Recommendation model is successful, you will get recommendation for incidents landing into your console.
This actions on this screen are necessary whenever you are making changes to manage Runbook page to rebuild models.
Conclusion
Post the completion of this exercise, you should have a good understanding of building models for recommendation system.
The next step is to enable error logging the data sources for sourcing the ticket related information which will be covered in the next exercise.