AIOps Foundation℠

Workshop Description

This course introduces the history, background, technologies, organizational challenges and strategies towards applying artificial intelligence for IT Operations, or AIOps, a rapidly growing industry driven by the rapidly evolving IT operational environments of cloud native applications. It is tailored for those focused on understanding basic concepts, implementations, use cases, and benefits. This AIOps FoundationSM course covers the origins of AIOps, including the history behind the term, patterns that preceded it, and the technological context in which it has evolved. Learners will gain an understanding of the processes of combining Big Data analytics, Machine Learning algorithms, Generative AI, automation, and optimization into a single platform. This course introduces key principles and foundational concepts, along with the core technologies of AIOps: Big Data and Machine Learning. The course provides learners with an understanding of how and why digital transformation, together with the evolution of Machine Learning and Generative AI, have brought about the rise of AIOps as an indispensable tool in today’s IT Operational landscape. Core technologies of Big Data, Machine Learning and Generative AI are discussed, as well as the basic concepts of artificial intelligence, different types of Machine Learning models that can be implemented, the relationship between AIOps and MLOps, as well as DevOps and Site Reliability. This foundation course provides the learner with a solid understanding of the benefits of implementing AIOps in the organization, including common challenges and key steps in ensuring valuable and successful integration of artificial intelligence in the day-to-day operations of information technology solutions. Practical, real-world exercises are used to apply the concepts covered in the course and sample documents, templates, tools, and techniques will be provided to use after the class. This course positions learners to successfully complete the AIOps FoundationSM certification exam.

Why Choose AIOps?

Stay Ahead of Evolving Technologies The AIOps Foundation certification will equip you with the necessary knowledge to navigate the complexities of cloud-native applications and harness artificial intelligence for IT Operations. Master Cutting-edge Technologies Gain an in-depth understanding of how artificial intelligence, big data analytics and machine learning can be combined to optimise IT processes. Drive Digital Transformation Efforts Explore the synergy between digital transformation, machine learning, and the rise of AIOps to spearhead initiatives that seamlessly integrate AIOps into organisational workflows. Overcome Common Challenges, Maximise Benefits Acquire the tools and practical strategies needed to overcome common hurdles and maximise the benefits of AIOps adoption. Gain a greater understanding of deployment effectiveness and learn to quantify outcomes using industry-standard metrics.

Audience

Anyone focused on IT Operations ​ Anyone interested in software in today’s IT landscape AIOps Architects and Engineers​ Business Managers, Stakeholders​ Cloud Engineers​ Data Engineers and Scientists DevOps Engineers and Practitioners IT Directors IT Managers ​ IT Security Analysts IT Team Leaders ​ Product Owners ​ Scrum Masters ​ Software Engineers ​ Site Reliability Engineers System Integrators ​ AIOps Platform and Tool Providers

Course objectives

The learning objectives for the AIOps FoundationSM course include a practical understanding of: • the basic concepts, industry contexts, and key principles of AIOps • the concepts and principles of core technologies required for AIOps implementation • the changes in organizational mindset and required skill sets for deploying AIOps • how to evaluate the performance of an AIOps implementation using industry standard metrics • the challenges and opportunities that arise when looking to deploy AIOps in the organization • key considerations and strategies required to succeed in promoting and delivering AIOps in your organization.

What will you learn?

AIOps Fundamentals Discover how AIOps has evolved through the years, the difference between AIOps and IT Operations Analytics, and the current stages of an AIOps system. AIOps in the Organization Learn how AIOps can be integrated into organizational frameworks, and its impact on DevOps, site reliability, security, and system complexity. Core Technologies: Big Data Gain an introduction to Big Data, covering what Big Data is, the Five V’s, its key characteristics, AIOps data sources/types, and diverse data. Core Technologies: Machine Learning (ML) Explore AI and Machine Learning in AIOps, supervised vs. unsupervised learning, ML vs. analytics, training models, and future prospects. AIOps and Operations Metrics Leverage industry standard metrics to quantify the outcomes of implementing AIOps. AIOps Use Cases and Organizational Mindset Understand the challenges and opportunities of applying AIOps in the organization. Evaluating AIOps Impact Measure the effectiveness of AIOps deployment and its potential benefits. Implementing AIOps Discover the challenges, trends and ethical considerations organizations may face while deploying an AIOps initiative.

Course outline

Introduction

Module 1: AIOps Foundation • History and predecessors • Core technologies and basic concepts • AIOps capability chain Module 2: AIOps in the organization • Drivers and influences • AIOps and DevOps • AIOps and Site Reliability Engineering • AIOps and security Module 3: Core technologies: Data • What is Big Data? • Five Vs of Big Data • AIOps data sources and types • From source to AIOps Module 4: Core Technologies: Machine Learning (ML) and Generative AI (GenAI) • AI, ML, and GenAI • How ML models learn • Supervised versus unsupervised • Analytics versus AI • AIOps and the future of AI Module 5: AIOPs and operations metrics • Metrics and operations • Key metrics to track across systems • Agreements, objectives and indicators Module 6: AIOps use cases and organizational mindset • Shifting from reactive to proactive • Deterministic to probabilistic • Deep dive into use cases Module 7: Evaluating AIOps’ impact • AIOps and operations metrics • AIOps, DevOps, and SRE • Improving AI accuracy • AIOps system visibility Module 8: Implementing AIOps in the organization • Avoiding common challenges • Ethics and ML

Prerequisites

Familiarity with IT terminology and IT related work experience are recommended.

Professional Development Units (PDUs)

Professional Development Units (PDUs) Attendees may be eligible to apply for 14 PDUs toward their continuing education requirements with the Project Management Institute (PMI) for PMP®, PgMP®, and PMI-ACP® certifications.

Certification Exam

Successfully passing (65%) the 60-minute examination, consisting of 40 multiple-choice questions, leads to the AIOps Foundation Certificate. The certification is governed and maintained by the DevOps Institute, a member of the PeopleCert Group.

Learning Materials

2 days of instructor-led training and exercise facilitation Learner Manual (excellent post-class reference) Participation in unique exercises designed to apply concepts Sample documents, templates, tools and techniques Access to additional value-added resources and communities.

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