The Runbook AI (Add-on) is designed for both BigFix Runbook AI administrators and end users who are working towards the resolution of IT support tickets. Its primary purpose is to help BigFix administrators to easily monitor the health of their servers and initiate well-informed recovery actions with specialized Runbooks AI.
This lab manual provides infrastructure administrators, installation and configuration administrators, and end users with detailed instructions on how to install, configure, and use BigFix Runbook AI. It is divided into modules, each containing an introduction and lab exercises. The manual also references additional servers, post-installation steps, and other documents for more information.
This module focuses on model optimization.
This guide provides you with an overview of BigFix Runbook AI and its features and benefits. It also provides an architectural overview and talks about various configurations and end user activities in brief.
This guide provides instructions to install the prerequisites required for BigFix Runbook AI. This includes the installation of MongoDB and Solr for both HA (High Availability) and non-HA modes as well as generation of certificates for authentication and authorization purposes.
This guide provides instructions to install BigFix Runbook AI. It includes the pre-installation and the installation procedures for BigFix Runbook AI. This guide also provides summary material about additional servers and optional post- installations and references to the other documents for detailed information.
This guide instructs on how to install and configure BigFix Runbook AI. These instructions also include the configuration procedures for the product.
This guide introduces you to the key concepts of BigFix Runbook AI and describes how to use the product. It provides an overview of the end-user interface and instructions to perform different tasks. This guide is intended for the BigFix Runbook AI end-users working towards resolution of IT support tickets.
BigFix Runbook AI API guide provides documentation and instructions on how to use its application programming interface (API), including details on the functions, parameters, and endpoints available for developers to interact with the API.
This document provides detailed list of out-of-box fixlets available within BigFix Runbook AI. This information is intended for administrators and users authorized for configuring use cases / fixlets within BigFix Runbook AI, which works in conjunction with HCL Bigfix engine.
This guide provides instructions to enable integrations with various ITSM and Runbook Automation tools, while configuring BigFix Runbook AI.
Prerequisites for the training include having access to a laptop/desktop with specific hardware and software requirements, high bandwidth internet connectivity, and technical skills such as knowledge of ITIL, IT Service Management tools, command center operations, cloud computing, and familiarity with various operating systems and technologies.
This section describes a procedure to connect to the DRYiCE Labs VPN using Cisco AnyConnect Secure Mobility Client 4.5.05030 to access the BigFix Runbook AI Portal. The user needs to meet certain requirements and follow specific steps to establish the VPN connectivity.
BigFix Runbook AI is an Intelligent Runbook Automation product that uses AI, ML, and NLP to automate incident and service request management. It provides automated remediation, knowledge recommendation, and efficient task automation, resulting in cost reduction, risk mitigation, and improved efficiency.
This module focuses on the development of a business case for automation by identifying potential opportunities.
This module provides instructions for installing BigFix Runbook AI.
This module covers BigFix Runbook AI training and participants will learn how to configure the BigFix Runbook AI system.
This module covers the end to end ticket resolution flow.
This module describes how to optimize ML models used by BigFix Runbook AI components like iRecommend and iUnique for recommending relevant runbooks and ticket clustering. It explains how to configure hyperparameters and conduct experimentation to achieve an optimized model.
This lab exercise demonstrates how to configure hyperparameters for the iRecommend and iUnique components in the BigFix Runbook AI Web application. Users can customize various parameters such as tag weights, usebm25, usePOSWeights, NgramSimilarity, EntityModel, and KMeasure to optimize the recommendation and unique clustering models.
In this lab exercise, the main objective is to identify the optimal values of hyperparameters for iUnique (Unique Clustering) analysis. The procedure involves uploading data, starting the analysis, verifying the results, publishing the optimized hyperparameter template, and mapping it to the organization. This exercise aims to improve the recommendation of runbooks and ticket clustering for automation candidates.
This lab exercise covers the procedure for analyzing and identifying optimal values of hyperparameters for iRecommend (Recommendation). Users will learn how to enable the recommendation job, run new iterations for recommendation analysis, view and validate recommendation results, and publish the hyperparameter configuration template.
This module focuses on document processing and analysis.
This module covers the configuration of runbook parameters.
A module that focuses on the reporting dashboard and its functionality.
This guide provides instructions to troubleshoot some of the commonly occurring issues along with the resolution steps. This information is intended for administrators responsible for installing, configuring, and supporting BigFix Runbook AI product.
A list of abbreviations and their expansions.