Course Code: aiopsact
Duration: 14 hours
Prerequisites:
  • Experience with monitoring systems such as Prometheus or ELK
  • Working knowledge of Python and basic machine learning
  • Familiarity with incident management workflows

Audience

  • Senior site reliability engineers (SREs)
  • IT automation architects
  • DevOps and observability platform leads
Overview:

AIOps (Artificial Intelligence for IT Operations) is increasingly being used to predict incidents before they occur and automate root cause analysis (RCA) to minimize downtime and accelerate resolution.

This instructor-led, live training (online or onsite) is aimed at advanced-level IT professionals who wish to implement predictive analytics, automate remediation, and design intelligent RCA workflows using AIOps tools and machine learning models.

By the end of this training, participants will be able to:

  • Build and train ML models to detect patterns leading to system failures.
  • Automate RCA workflows based on multi-source log and metric correlation.
  • Integrate alerting and remediation processes into existing platforms.
  • Deploy and scale intelligent AIOps pipelines in production environments.

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
Course Outline:

Introduction to Predictive AIOps

  • Overview of predictive analytics in IT operations
  • Data sources for prediction (logs, metrics, events)
  • Key concepts in time-series forecasting and anomaly patterns

Designing Incident Prediction Models

  • Labeling historical incidents and system behavior
  • Choosing and training models (e.g., LSTM, Random Forest, AutoML)
  • Evaluating model performance and false-positive handling

Data Collection and Feature Engineering

  • Ingesting and aligning log and metric data for model input
  • Feature extraction from structured and unstructured data
  • Handling noise and missing data in operational pipelines

Automating Root Cause Analysis (RCA)

  • Graph-based correlation of services and infrastructure
  • Using ML to infer probable root causes from event chains
  • Visualizing RCA with topology-aware dashboards

Remediation and Workflow Automation

  • Integrating with automation platforms (e.g., Ansible, Rundeck)
  • Triggering rollbacks, restarts, or traffic redirection
  • Auditing and documenting automated interventions

Scaling Intelligent AIOps Pipelines

  • MLOps for observability: retraining and model versioning
  • Running predictions in real-time across distributed nodes
  • Best practices for deploying AIOps in production environments

Case Studies and Practical Applications

  • Analyzing real incident data using predictive AIOps models
  • Deploying RCA pipelines with synthetic and production data
  • Review of industry use cases: cloud outages, microservices instability, network degradations

Summary and Next Steps

Sites Published:

United Arab Emirates - AIOps in Action: Incident Prediction and Root Cause Automation

Qatar - AIOps in Action: Incident Prediction and Root Cause Automation

Egypt - AIOps in Action: Incident Prediction and Root Cause Automation

Saudi Arabia - AIOps in Action: Incident Prediction and Root Cause Automation

South Africa - AIOps in Action: Incident Prediction and Root Cause Automation

Brasil - AIOps in Action: Incident Prediction and Root Cause Automation

Canada - AIOps in Action: Incident Prediction and Root Cause Automation

中国 - AIOps in Action: Incident Prediction and Root Cause Automation

香港 - AIOps in Action: Incident Prediction and Root Cause Automation

澳門 - AIOps in Action: Incident Prediction and Root Cause Automation

台灣 - AIOps in Action: Incident Prediction and Root Cause Automation

USA - AIOps in Action: Incident Prediction and Root Cause Automation

Österreich - AIOps in Action: Incident Prediction and Root Cause Automation

Schweiz - AIOps in Action: Incident Prediction and Root Cause Automation

Deutschland - AIOps in Action: Incident Prediction and Root Cause Automation

Czech Republic - AIOps in Action: Incident Prediction and Root Cause Automation

Denmark - AIOps in Action: Incident Prediction and Root Cause Automation

Estonia - AIOps in Action: Incident Prediction and Root Cause Automation

Finland - AIOps in Action: Incident Prediction and Root Cause Automation

Greece - AIOps in Action: Incident Prediction and Root Cause Automation

Magyarország - AIOps in Action: Incident Prediction and Root Cause Automation

Ireland - AIOps in Action: Incident Prediction and Root Cause Automation

Luxembourg - AIOps in Action: Incident Prediction and Root Cause Automation

Latvia - AIOps in Action: Incident Prediction and Root Cause Automation

España - AIOps in Action: Incident Prediction and Root Cause Automation

Italia - AIOps in Action: Incident Prediction and Root Cause Automation

Lithuania - AIOps in Action: Incident Prediction and Root Cause Automation

Nederland - AIOps in Action: Incident Prediction and Root Cause Automation

Norway - AIOps in Action: Incident Prediction and Root Cause Automation

Portugal - AIOps in Action: Incident Prediction and Root Cause Automation

România - AIOps in Action: Incident Prediction and Root Cause Automation

Sverige - AIOps in Action: Incident Prediction and Root Cause Automation

Türkiye - AIOps in Action: Incident Prediction and Root Cause Automation

Malta - AIOps in Action: Incident Prediction and Root Cause Automation

Belgique - AIOps in Action: Incident Prediction and Root Cause Automation

France - AIOps in Action: Incident Prediction and Root Cause Automation

日本 - AIOps in Action: Incident Prediction and Root Cause Automation

Australia - AIOps in Action: Incident Prediction and Root Cause Automation

Malaysia - AIOps in Action: Incident Prediction and Root Cause Automation

New Zealand - AIOps in Action: Incident Prediction and Root Cause Automation

Philippines - AIOps in Action: Incident Prediction and Root Cause Automation

Singapore - AIOps in Action: Incident Prediction and Root Cause Automation

Thailand - AIOps in Action: Incident Prediction and Root Cause Automation

Vietnam - AIOps in Action: Incident Prediction and Root Cause Automation

India - AIOps in Action: Incident Prediction and Root Cause Automation

Argentina - AIOps in Action: Incident Prediction and Root Cause Automation

Chile - AIOps in Action: Incident Prediction and Root Cause Automation

Costa Rica - AIOps in Action: Incident Prediction and Root Cause Automation

Ecuador - AIOps in Action: Incident Prediction and Root Cause Automation

Guatemala - AIOps in Action: Incident Prediction and Root Cause Automation

Colombia - AIOps in Action: Incident Prediction and Root Cause Automation

México - AIOps in Action: Incident Prediction and Root Cause Automation

Panama - AIOps in Action: Incident Prediction and Root Cause Automation

Peru - AIOps in Action: Incident Prediction and Root Cause Automation

Uruguay - AIOps in Action: Incident Prediction and Root Cause Automation

Venezuela - AIOps in Action: Incident Prediction and Root Cause Automation

Polska - AIOps in Action: Incident Prediction and Root Cause Automation

United Kingdom - AIOps in Action: Incident Prediction and Root Cause Automation

South Korea - AIOps in Action: Incident Prediction and Root Cause Automation

Pakistan - AIOps in Action: Incident Prediction and Root Cause Automation

Sri Lanka - AIOps in Action: Incident Prediction and Root Cause Automation

Bulgaria - AIOps in Action: Incident Prediction and Root Cause Automation

Bolivia - AIOps in Action: Incident Prediction and Root Cause Automation

Indonesia - AIOps in Action: Incident Prediction and Root Cause Automation

Kazakhstan - AIOps in Action: Incident Prediction and Root Cause Automation

Moldova - AIOps in Action: Incident Prediction and Root Cause Automation

Morocco - AIOps in Action: Incident Prediction and Root Cause Automation

Tunisia - AIOps in Action: Incident Prediction and Root Cause Automation

Kuwait - AIOps in Action: Incident Prediction and Root Cause Automation

Oman - AIOps in Action: Incident Prediction and Root Cause Automation

Slovakia - AIOps in Action: Incident Prediction and Root Cause Automation

Kenya - AIOps in Action: Incident Prediction and Root Cause Automation

Nigeria - AIOps in Action: Incident Prediction and Root Cause Automation

Botswana - AIOps in Action: Incident Prediction and Root Cause Automation

Slovenia - AIOps in Action: Incident Prediction and Root Cause Automation

Croatia - AIOps in Action: Incident Prediction and Root Cause Automation

Serbia - AIOps in Action: Incident Prediction and Root Cause Automation

Bhutan - AIOps in Action: Incident Prediction and Root Cause Automation

Nepal - AIOps in Action: Incident Prediction and Root Cause Automation

Uzbekistan - AIOps in Action: Incident Prediction and Root Cause Automation