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AIOps & Visibility For Dummies

Introduction

Artificial Intelligence for IT Operations (AIOps) is the use of artificial intelligence (AI) to manage the digital complexity of modern organizations. Modern IT complexity comes from:

  • Data volume, variety, and speed of ingestion
  • Cloud and on-premises architectures
  • Virtualized and cloud-native applications
  • Containers and serverless computing

Discovering what you need to manage

  1. Security
  2. Asset management
  3. Root-cause analysis
  4. Change management
  5. Impact analysis
  6. Capacity management
  7. Performance and availability management, and more

Exploring Key AIOps Use Cases

  1. Managing Thresholds
  2. Allowing Machine Learning to Find Patterns in Alert Data
  3. Pinpointing the Cause of Service Issues
  4. Using Natural Language Processing to Uncover the Past
  5. Faster Categorization and Assignment
  6. Acting on AI’s Operational Insights

Your AIOps Journey

  1. Build Your AIOps Team
  2. Define Your AIOps Use Cases
  3. Establish Implementation Principles
  4. Create Your AIOps Technology Plan
  5. Establish Visibility with a Trustworthy CMDB
  6. Monitor the Health of Your Services
  7. Optimize Service Health through Automation
  8. Review and Learn for Continuous Improvement
  9. Share Your Success with the Enterprise

Ten Considerations for Implementing AIOps

  1. Understand Your Goals and Objectives
  2. Have Realistic Expectations
  3. Give Machines Time to Learn, Too
  4. Use CMDB to Give AIOps Visibility
  5. Remember That ITSM Is Essential for AIOps
  6. Map Your Services
  7. Respond Faster with Automation
  8. One Size Doesn’t Fit All
  9. Build the Right Team
  10. Plan Big, Start Small, and Iterate Fast