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Exam Information
Official specifications published by PEOPLECERT
Exam Format
60 min
40
65%
Foundation
Registration
$270 USD
Pearson VUE, Online Proctored, or online proctoring
Validity
3 years
Earn 60 CPD (Continuous Professional Development) points; Retake the exam; Complete advanced AIOps certifications
AIOF Exam Topics and Domains
AIOF is organized into 8 weighted domains. Expect to work with AIOps platforms, AppDynamics, AWS SageMaker, Azure DevOps, and more.
1
AIOps Fundamentals
15%
Origins and Evolution of AIOps
History of AIOpsAIOps vs IT Operations Analytics
- Understand the origins of AIOps including the history behind the term
- Differentiate AIOps from IT Operations Analytics
- Identify patterns that preceded AIOps
- Understand the technology context in which AIOps has evolved
Current State of AIOps
Stages of AIOps SystemAIOps in Modern IT
- Explore the current stages of an AIOps system
- Understand AIOps significance in modern IT environments
- Recognize foundational concepts that drive AIOps adoption
2
AIOps in the Organisation
15%
Integration with Existing Frameworks
AIOps and DevOpsAIOps and Site ReliabilityAIOps and Security
- Understand how AIOps integrates into organizational frameworks
- Recognize the impact of AIOps on DevOps practices
- Identify effects on site reliability and security measures
- Understand system complexity management with AIOps
Organizational Change
Mindset ShiftsSkills and Collaboration
- Recognize organizational changes required for successful AIOps implementation
- Understand necessary shifts in mindset and collaboration
- Identify required skill sets for AIOps teams
3
Core Technologies: Big Data
12.5%
Introduction to Big Data
What is Big DataThe Five V's
- Understand what Big Data is
- Learn the Five V's of Big Data
- Identify key characteristics of Big Data
AIOps Data Management
Data Sources and TypesDiverse Data Handling
- Understand AIOps data sources and types
- Learn about diverse data management
- Recognize data quality importance
4
Core Technologies: Machine Learning (ML)
12.5%
AI and Machine Learning Basics
AI FundamentalsMachine Learning Types
- Understand basic concepts of artificial intelligence
- Differentiate between supervised and unsupervised learning
- Identify different types of machine learning models
ML in AIOps Context
ML vs AnalyticsTraining ModelsAIOps and MLOps
- Understand ML vs analytics differences
- Learn about training models for AIOps
- Comprehend relationship between AIOps and MLOps
- Explore future prospects of AI in operations
5
AIOps and Operations Metrics
12.5%
Industry Standard Metrics
Key Performance IndicatorsBusiness Metrics
- Leverage industry standard metrics to quantify AIOps outcomes
- Understand how to measure AIOps implementation success
- Identify relevant KPIs for AIOps initiatives
Measuring AIOps Effectiveness
Deployment MetricsPotential Benefits Measurement
- Measure the effectiveness of AIOps deployment
- Quantify potential benefits
- Track continuous improvement
6
AIOps Use Cases and Organisational Mindset
10%
Common Use Cases
Incident ManagementPerformance Optimization
- Understand common AIOps use cases
- Identify opportunities for AIOps application
- Recognize organizational benefits
Organizational Transformation
Mindset ChangesCollaboration Models
- Understand changes in mindset required for AIOps
- Recognize collaboration requirements
- Identify necessary skill developments
7
Evaluating AIOps Impact
10%
Impact Assessment
Operational ImpactBusiness Impact
- Evaluate operational improvements from AIOps
- Assess business impact
- Measure success against objectives
Continuous Improvement
Feedback Loops
- Establish continuous improvement processes
- Implement feedback mechanisms
- Drive ongoing optimization
8
Implementing AIOps
12.5%
Implementation Challenges
Common ChallengesTechnical Challenges
- Identify common implementation challenges
- Understand technical barriers
- Develop mitigation strategies
Implementation Strategy
Strategic PlanningBest Practices
- Develop implementation strategies
- Apply best practices
- Ensure successful deployment
Ethics and Future Trends
Ethical ConsiderationsFuture Trends
- Understand ethical implications of AIOps
- Recognize future trends and opportunities
- Prepare for evolving landscape
How do I earn this certification?
Passing AIOF earns the AIOps Foundation certification. It sits in the DevOps/AIOps track.
Current Level Exams
- SRE-Foundation - Site Reliability Engineering Foundation
- DevSecOps-Foundation - DevSecOps Foundation
- Continuous-Testing-Foundation - Continuous Testing Foundation
- Value-Stream-Management-Foundation - Value Stream Management Foundation
Next Level Options
- AIOps-Practitioner - AIOps Practitioner
- ML-Engineer - Machine Learning Engineer
- AWS-ML-Specialty - AWS Certified Machine Learning - Specialty
- Azure-AI-Engineer - Azure AI Engineer Associate
Alternative Paths
- CKA - Certified Kubernetes AdministratorContainer orchestration for AIOps platforms
- Data-Engineering-Foundation - Data Engineering Foundation Big Data skills for AIOps
- Cloud-Architect - Cloud Architect Certification Cloud infrastructure for AIOps deployment
- Observability-Foundation - Observability Foundation Enhanced monitoring and observability skills
Practice with Precision
The PlanetCert Simulator mirrors the real exam environment with authentic questions and timed pressure.
How to study for this exam?
The most effective way to prepare for AIOF is by using the PlanetCert Simulator to practice questions and review detailed explanations.
What's changed on this exam?
Current Status
- ACTIVE
- Last content update: 2024-06-13
Updates
- Kubernetes AIOps 1.28+ Increased focus on container orchestration monitoring • Release date: 2024-08-01
- Prometheus & Grafana Prometheus 2.45+, Grafana 10.0+ Enhanced observability stack questions likely • Release date: 2024-07-01
- OpenTelemetry 1.30+ Standardized observability becoming exam focus • Release date: 2024-06-15
Who should take this exam?
This exam is typically taken by IT Operations professionals and Cloud Engineers.
- Familiarity with IT terminology
- IT-related work experience
- Basic understanding of DevOps concepts
- Knowledge of IT operations