AIOps Foundation

Foundation Level

Develop a clear understanding of how artificial intelligence, machine learning, generative AI and operational data can improve modern IT operations.

Developed by DevOps Institute and governed by PeopleCert, AIOps Foundation introduces the principles, technologies and organisational practices behind artificial intelligence for IT operations. It explains how teams can use data and automation to detect operational issues, reduce alert noise, support faster decisions and improve service reliability.

The certification is suitable for IT professionals who want to understand AIOps before selecting tools, planning an implementation or contributing to an intelligent operations initiative.

Ready to build the AIOps knowledge needed for modern IT operations?

Understand how AIOps supports more proactive IT operations

This AIOps Foundation course aims to cover the origins of AIOps including the history behind the term, patterns that preceded it and the technology context in which it has evolved.

  • Gain an understanding of the processes of combining big data analytics, machine learning algorithms, automation, and optimization into a single platform.
  • Learn key principles and foundational concepts along with the core technologies of AIOps: big data and machine learning
  • Validate understanding of how and why digital transformation, together with the evolution of machine learning, have brought about the rise of AIOps as an indispensable tool in today’s IT Operational landscape.

This foundation course will also provide the student 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.

Fees:

RM6,000/pax RM4,500

Intakes:

8-9 Oct 2026 | 7-8 Dec 2026

What are the key skills measured:

  • AIOps foundations: History, predecessors, core technologies and the AIOps capability chain 

  • AIOps in the organization: Organizational drivers and relationships with DevOps, SRE and security 

  • Core technologies: Data: Big data, the Five Vs, operational data sources and data movement 

  • Machine learning and generative AI: AI concepts, learning models, analytics and future applications 

  • AIOps and operations metrics: Service indicators, objectives, agreements and performance measures 

  • AIOps use cases and organizational mindset: Proactive operations, probabilistic approaches and practical applications 

  • Evaluating AIOps impact: Accuracy, visibility, operational performance and organizational value 

  • Implementing AIOps: Adoption challenges, ethics, stakeholder alignment and implementation planning 

Who is this for?

  • 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

Why AIOps knowledge matters in 2026

77%

77% of IT practitioners reported limited visibility across on-premises and cloud environments. This visibility gap makes it harder for teams to understand service dependencies, isolate problems and respond effectively. 
Source: SolarWinds 2026 State of Monitoring and Observability

40%

Nearly 40% of SMEs that experienced a skills gap said generative AI helped compensate for it. However, organisations still need employees who can identify appropriate uses and evaluate AI-generated outputs. 
Source: OECD, AI and Skills 2026 Report

42%

42% of IT practitioners identified skills gaps as a barrier to adopting AI for observability. Security concerns and technical complexity were also among the leading adoption challenges.
Source: SolarWinds 2026 monitoring and observability findings

Build a vendor-neutral AIOps foundation 

Learn the underlying principles of intelligent IT operations without tying your knowledge to a single monitoring, observability or AIOps platform. 

Contribute to AIOps planning 

Develop the vocabulary and structured knowledge needed to discuss use cases, metrics, organisational readiness and implementation considerations with technical and business teams. 

Connect AI with operational needs 

Understand how machine learning, generative AI, automation and operational data can support anomaly detection, event correlation, root-cause analysis and proactive operations. 

Support reliable digital services 

Learn how AIOps can complement DevOps, SRE, observability and security practices to improve visibility, reduce operational noise and strengthen service reliability. 

Why choose Trainocate?

With more than 30 years of experience and operations across 24 countries, Trainocate is a recognised technology and professional development training provider trusted by over 7,000 organisations worldwide.

Trainocate is an accredited PeopleCert Training Organisation for DevOps Institute certifications, providing learners with access to official training, current certification content and globally recognised examination pathways. Its wider portfolio is supported by more than 30 authorised technology partnerships.

Trainocate Malaysia is also an HRD Corp Registered Training Provider and Yayasan Peneraju Accredited Learning and Training Institution, supporting professional and organisational skills development across Malaysia.

Exam Overview

Exam Code:

DO-AIOF v1.1

Category:

Fundamental

Exam Duration:

60 minutes

Exam Format:

40 multiple-choice or multiple-response questions

Passing score:

65%

Cost:

USD320
*Subject to applicable taxes and exchange rates

Language offered:

English

Testing options

Peoplecert Online

Certification validity:

3 Years

Open up new possibilities for your career

Frequently Asked Questions (FAQs)

AIOps Foundation is a vendor-neutral certification covering the principles, technologies and organizational practices used in artificial intelligence for IT operations.

It introduces big data, machine learning, generative AI, automation, operational metrics, common use cases and implementation considerations. The certification is developed under the DevOps Institute portfolio and governed by PeopleCert.

Pro Tip: Use the course to understand the operating model behind AIOps before comparing individual platforms or tools.

AIOps Foundation v1.1 is the current certification and includes refreshed content on generative AI, modern operations and ethical considerations.

Version 1.0 has been retired, and its final exam date was 30 April 2026. New learners should prepare only for the current v1.1 syllabus and exam.

Pro Tip: Confirm that your training provider uses the September 2025 v1.1 official materials before enrolling.

The course is intended for IT professionals involved in operations, DevOps, SRE, cloud, security, software delivery or digital transformation.

It is also relevant to managers, product owners and business stakeholders who need to understand AIOps use cases, implementation challenges and expected operational outcomes.

Pro Tip: Identify one recurring operational challenge in your organization and use it as a reference point throughout the course exercises.

There are no mandatory prerequisites, although familiarity with IT terminology and practical IT experience are recommended.

Learners do not need programming, data science or machine learning model-development experience. The program explains these technologies at a conceptual and operational level.

Pro Tip: Review basic monitoring, incident management and DevOps terminology if you are new to IT operations.

No. AIOps Foundation teaches vendor-neutral principles rather than training learners to operate one commercial platform.

The course focuses on data sources, machine learning concepts, use cases, metrics, organisational readiness and implementation strategy. This knowledge can help learners assess different tools more effectively.

Pro Tip: After certification, compare platforms according to your required data integrations, operational use cases, governance needs and success metrics.

Observability provides the data and context needed to understand system behavior, while AIOps applies AI and machine learning to analyze that data and support operational action.

Metrics, logs, traces, events and topology data can feed AIOps capabilities such as anomaly detection, event correlation, incident prioritization and root-cause analysis.

Pro Tip: Treat observability data quality as a prerequisite when planning an effective AIOps implementation.

AIOps supports DevOps and SRE by helping teams analyze operational data, reduce noise and make faster reliability decisions.

The course examines how AIOps can support proactive operations, service-level measurement, incident response and collaboration across development and operations teams.

Pro Tip: Map potential AIOps use cases to existing SRE indicators or DevOps performance measures rather than creating a separate measurement system.

Yes, if your work involves increasingly complex cloud, hybrid or distributed IT environments and you need a structured introduction to AI-assisted operations. The certification helps learners understand what AIOps can and cannot do, where it may deliver value and what organizations need before implementation. It does not by itself qualify someone for an advanced AIOps engineering role.

Pro Tip: Pair the certification with practical experience in monitoring, observability, incident management or service reliability to strengthen its workplace value.

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