AI for IT Infrastructure and Predictive Management

Unlock AIOps potential: Drive IT efficiency, reliability, and proactive management through AI-powered insights and automation.

Course Description:

This 2-day interactive workshop, AIOps Essentials, is designed for executives, department heads, and managers seeking to understand how Artificial Intelligence can revolutionize IT infrastructure management. Discover the core concepts behind AIOps – leveraging Big Data, Machine Learning, and Automation – to move from reactive firefighting to proactive, predictive operations.

Explore key capabilities like anomaly detection, event correlation, and automated root cause analysis. Understand the tangible business benefits, including improved efficiency, enhanced system reliability, reduced MTTR, and significant cost savings. Through practical examples and case studies, grasp how AIOps drives value and learn the essential considerations for exploring AIOps adoption in your organization. Equip yourself with the knowledge to lead your teams towards smarter, more resilient IT operations.

Who Should Attend:

• Head of IT
• IT Operations Manager
• Infrastructure Manager
• Digital Transformation Manager
• Technology Manager
• Managers with significant IT service dependency

Course Objectives:

Knowledge Acquisition:

• Understand the definition of AIOps and its core purpose in modern IT operations.  
• Recognize the limitations of traditional IT operations and why AIOps emerged as a necessary evolution.  
• Identify the fundamental components powering AIOps, including Big Data, AI/Machine Learning, and Automation.  
• Grasp the key objectives of AIOps, such as improving efficiency, enhancing reliability, and enabling proactive management.

Skills Development:

• Distinguish between the core AIOps capabilities: anomaly detection, event correlation, root cause analysis, and predictive analytics.
• Analyze the tangible business benefits derived from AIOps implementation, including reduced MTTR and operational cost savings.
• Evaluate the common challenges associated with AIOps adoption, such as data quality, skills gaps, and organizational change.
• Identify high-level considerations for initiating an AIOps journey within an organization, including defining scope and objectives.

Practical Application:

• Connect AIOps capabilities to real-world IT operational scenarios and use cases presented through examples and case studies.
• Articulate how AIOps can directly contribute to improving operational efficiency and system reliability within their scope of influence.
• Relate the technical advantages of AIOps to measurable business outcomes like cost reduction and enhanced user experience.
• Participate in discussions and activities designed to brainstorm potential AIOps applications relevant to their operational context.

What will I Learn From it:

• Understand how AIOps transforms IT operations for proactive management.
• Identify key opportunities to boost efficiency and automate IT tasks.
• Evaluate AIOps' potential to significantly reduce system downtime and improve reliability.
• Grasp the essential AI, ML, and Big Data concepts driving AIOps value.
• Recognize practical AIOps use cases applicable to modern IT challenges.
• Assess the strategic business value and potential ROI from AIOps adoption.
• Make more informed decisions about exploring AIOps within your organization.

Training Methodology

• Expert-Led Sessions: Clear explanations of core concepts and strategic considerations.
• Real-World Case Studies: Examining how companies are successfully (and unsuccessfully) leveraging AI in software development .
• Interactive Discussions: Opportunities to share challenges, insights, and experiences with peers and the instructor.
• Group Activities & Workshops: Collaborative exercises focused on evaluating AI outputs, crafting prompts, and developing initial integration strategies.  
• Tool Demonstrations: High-level showcases of leading AI coding assistants in action.

Requirement/
pre-requisites:

• No prior AI expertise is required.
• A general understanding of the software development lifecycle and common challenges faced by development teams is beneficial.
• An interest in improving operational efficiency and reliability through technology is beneficial.