- Introduction
This module covers the BigFix Runbook AI product's configuration process, including manual and automated ticket resolutions, document search and analysis, and other functionalities. It is important not to skip any exercise as some may be dependent on others. The module starts with the creation of an Organization.
- Lab Exercise 1 – Create Organization
In this lab exercise, the process of creating an organization and configuring various parameters for BigFix Runbook AI is detailed. The prerequisites include information about the module to be configured, authentication type, and existing ITSM and runbook automation tools. The conclusion states that this exercise provides a foundation for further configurations.
- Lab Exercise 2 – Create Data Source
This lab exercise showcases how an organization can automate resolution of incident tickets through BigFix Runbook AI by creating a data source for the ITSM tool (Service Now) against the Incident Management module. The lab exercise provides a detailed procedure for creating the data source and configuring the necessary parameters.
- Lab Exercise 3 – Create Users
This lab exercise provides a step-by-step procedure for creating users with organization admin and end user privileges, as well as mapping them to the respective groups. This helps enable role-based access control and allows users to perform various tasks within the system.
- Lab Exercise 4 – Onboard Runbook Automation Tool
This lab exercise provides a detailed procedure for onboarding a Runbook Automation tool in BigFix Runbook AI for automated resolution of incident tickets. It includes steps to add a new runbook tool, configure the integration settings, and create the tool in the system.
- Lab Exercise 5 – Map Runbook Tool to an Organization
This lab exercise provides a detailed procedure for mapping a runbook tool with an organization and data source. It requires the configuration of the organization, data source, and runbook tool, as well as access to Super Admin/Org Admin credentials. After completing this exercise, users will have a clear understanding of how to perform the mapping process.
- Lab Exercise 6 – Manage Execution Scope
This lab exercise provides a detailed procedure for managing the execution scope of BigFix Runbook AI for an organization. It includes steps to configure the organization, data source, and runbook tool, and optionally map the runbook tool tenant ID in a multi-tenant environment. By completing this exercise, users will gain a good understanding of managing the execution scope for an organization.
- Lab Exercise 6 – Release Rules Configuration
This lab exercise demonstrates how to configure release rules in BigFix Runbook AI to route tickets to another queue for resolution if they cannot be resolved automatically or if there is a resolution failure. This feature allows for assigning tickets to different resolver groups in case of failures.
- Lab Exercise 8 – Manage Columns for Recommendation and Parsing
This lab exercise provides a step-by-step procedure for configuring columns in BigFix Runbook AI Web to generate enriched recommendations and parse tickets for input parameters. After completing this exercise, users will be able to add or remove fields/columns for runbook recommendations and ticket parsing. The next exercise will cover configuring runbooks for automated ticket resolution.
- Lab Exercise 9 – Manage Runbooks
This lab exercise showcases the procedure for managing runbooks in BigFix Runbook AI, including logging in, selecting the runbook tool, importing metadata, and saving the configuration. This exercise helps automate ticket resolutions for a specific RBA tool.
- Lab Exercise 10 – Map Runbooks
In this lab exercise users get to know how to map runbooks to an organization in order to provide relevant recommendations and execution. The exercise provides step-by-step instructions for mapping runbooks using the BigFix Runbook AI Web URL.
- 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.
- Lab Exercise 12 – Enable Error Logging
This lab exercise demonstrates how to enable error logging in BigFix Runbook AI, allowing organizations to capture and track logs of errors for governance purposes. The process involves accessing the BigFix Runbook AI Web URL, enabling detail logging for the listener and application, and modifying the logging mode of all jobs to enable detailed logging of errors.
- Lab Exercise 13 – Manage Proxy
In this lab exercise, you will learn how to manage and configure proxy settings in BigFix Runbook AI. This includes entering the proxy IP address, port, username, and password, as well as enabling proxy in the data sources and runbook tool.