Overview

IBM Cloud Pak for Watson AIOps deploys advanced, explainable AI across the IT Operations (ITOps) toolchain so that you can confidently assess, diagnose, and resolve incidents across mission-critical workloads. 

IBM Cloud Pak for Watson AIOps brings the depth and breadth of IBM’s enterprise expertise to managing complex, mission-critical IT environments. IBM Cloud Pak for Watson AIOps helps you apply AI to IT operations to maximize efficiency, reduce costs, and maintain the resiliency and security you need to drive meaningful innovation. 

This course is designed to teach you how to perform important administration tasks for the IBM Cloud Pak for Watson AIOps platform, such as user management, troubleshooting, and self-monitoring.

Audience

This course is intended for administrators and operators responsible for installing and managing containerized environments.

Prerequisites

• Experience with Linux
• Working knowledge of Kubernetes
• Experience with Red Hat OpenShift Container platform (RHOCP)
• Experience with Event Manager, which is sometimes called Netcool Operations Insight

Objective

• Understand how machine learning applies to IT operations problems
• Describe key features of IBM Cloud Pak for Watson AIOps
• Explain IBM Cloud Pak for Watson AIOps architecture
• Understand OpenShift concepts and terminology
• Manage users and groups
• Integrate the AIOps console with an LDAP user repository
• Create custom roles
• Troubleshoot your environment
• Monitor the health of Event Manager
• Monitor your Cloud Pak deployment with the topology service
• View runbook history

Exercises

• Exercise 1. About your lab environment
• Exercise 2. Integrating with LDAP
• Exercise 3. Troubleshooting
• Exercise 4. Self-monitoring

Course Outline

• Course introduction
• Unit 1. IBM Cloud Pak for Watson AIOps overview
• Exercise 1. About your lab environment
• Unit 2. Integrating with LDAP
• Exercise 2. Integrating with LDAP
• Unit 3. Troubleshooting
• Exercise 3. Troubleshooting
• Unit 4. Self-monitoring
• Exercise 4. Self-monitoring
• Summary