AIOps Fundamentals: Monitoring, Correlation, and Intelligent Alerting

• An understanding of IT operations and system monitoring concepts
• Experience with monitoring tools or dashboards
• Familiarity with basic log and metric formats

Audience

• Operations teams responsible for infrastructure and applications
• Site Reliability Engineers (SREs)
• IT monitoring and observability teams

AIOps (Artificial Intelligence for IT Operations) is a practice that applies machine learning and analytics to automate and improve IT operations, particularly in the areas of monitoring, incident detection, and response.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT operations professionals who wish to implement AIOps techniques to correlate metrics and logs, reduce alert noise, and improve observability through intelligent automation.

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

• Understand the principles and architecture of AIOps platforms.
• Correlate data across logs, metrics, and traces to identify root causes.
• Reduce alert fatigue through intelligent filtering and noise suppression.
• Use open-source or commercial tools to monitor and respond to incidents automatically.

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.

Introduction to AIOps

• What is AIOps and why it matters
• Traditional monitoring vs. AIOps-driven observability
• AIOps architecture and key components

Collecting and Normalizing Operational Data

• Types of observability data: metrics, logs, and traces
• Ingesting data from multiple sources (servers, containers, cloud)
• Using agents and exporters (Prometheus, Beats, Fluentd)

Data Correlation and Anomaly Detection

• Time series correlation and statistical methods
• Using ML models for anomaly detection
• Detecting incidents across distributed systems

Alerting and Noise Reduction

• Designing intelligent alert rules and thresholds
• Suppression, deduplication, and alert grouping
• Integrating with Alertmanager, Slack, PagerDuty, or Opsgenie

Root Cause Analysis and Visualization

• Using dashboards to visualize metrics and detect trends
• Exploring events and timelines for RCA
• Tracing issues across layers with distributed tracing tools

Automation and Remediation

• Triggering automated scripts or workflows from incidents
• Integrating with ITSM systems (ServiceNow, Jira)
• Use cases: self-healing, scaling, traffic rerouting

Open Source and Commercial AIOps Platforms

• Overview of tools: Prometheus, Grafana, ELK, Moogsoft, Dynatrace
• Evaluation criteria for selecting an AIOps platform
• Demo and hands-on with a selected stack

Summary and Next Steps