Course Outline

Introduction

  • Using mathematical algorithms to extract meaningful information

Using Predictive Analytics Models to Gain Insight on Human Behavior

Collecting Raw Data from Management and Monitoring Technologies

Understanding the Infrastructure Application Stack through Root Cause Analysis

Ranking the Impact of Multiple Root Causes (Service Impact Analysis)

Real-time Application Behavior Learning

Learning Infrastructure Behavior Using Dynamically Baselines Threshold

Determining Which Problems to Go After

Evaluating Analytics Technologies

Carrying Out Machine Learning on Big Data Using an AIOps Platform

Integrating Operations Data Silos

Continuously Fixing and Improving via Automation (CI/CD for core IT functions)

Summary and Conclusion

Requirements

  • Experience with IT operations

Audience

  • IT managers
  • Data analysts
  • Business analysts
 7 Hours

Number of participants



Price per participant

Testimonials (3)

Related Courses

Remedy IT Service Management (ITSM)

21 Hours

Advanced DevOps

35 Hours

Ansible AWX Fundamentals for DevOps Automation

21 Hours

Ansible for Experts

35 Hours

Ansible and Puppet for Large Infrastructures

14 Hours

DevOps Automation with Red Hat Ansible Tower

14 Hours

Automated Monitoring with Zabbix

14 Hours

Amazon Web Services (AWS) CodePipeline

7 Hours

AWS DevOps Engineers

21 Hours

DevOps with TeamCity

14 Hours

DASA DevOps Fundamentals

21 Hours

Fundamentals of DevOps

21 Hours

DevOps with Atlassian Bamboo

14 Hours

DevOps Fundamentals

21 Hours

DevOps and Platform Engineering: A Collaborative Approach

14 Hours

Related Categories