AIOps Fundamentals: Monitoring, Correlation, and Intelligent Alerting Training Course

AIOps (Artificial Intelligence for IT Operations) is increasingly utilized to anticipate incidents before they happen and to automate root cause analysis (RCA), thereby reducing downtime and speeding up resolution times.

This instructor-led, live training session, available both online and onsite, targets advanced IT professionals looking to implement predictive analytics, automate remediation processes, and design intelligent RCA workflows using AIOps tools and machine learning models.

Upon completion of this training, participants will be capable of:

• Developing and training ML models to identify patterns that lead to system failures.
• Automating RCA workflows through the correlation of multi-source logs and metrics.
• Integrating alerting and remediation processes into existing platforms.
• Deploying and scaling intelligent AIOps pipelines within production environments.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Customization Options for the Course

• To request customized training for this course, please contact us to arrange your specific requirements.

An AIOps pipeline developed exclusively with open-source tools enables teams to create cost-efficient and adaptable solutions for observability, anomaly detection, and intelligent alerting within production environments.

This instructor-led live training (available online or on-site) targets advanced engineers looking to design and deploy a comprehensive AIOps pipeline utilizing tools such as Prometheus, ELK, Grafana, and custom machine learning models.

Upon completing this training, participants will be capable of:

• Designing an AIOps architecture comprised entirely of open-source components.
• Gathering and standardizing data from logs, metrics, and traces.
• Implementing ML models to identify anomalies and forecast incidents.
• Automating alerting and remediation processes using open-source tooling.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical sessions.
• Hands-on implementation within a live laboratory environment.

Customization Options

• To arrange customized training for this course, please contact us to discuss your requirements.

Enterprise AIOps platforms such as Splunk, Moogsoft, and Dynatrace offer robust capabilities for identifying anomalies, correlating alerts, and automating responses across large-scale IT environments.

This instructor-led training, available both online and onsite, is designed for intermediate-level enterprise IT teams looking to integrate AIOps tools into their existing observability stack and operational workflows.

Upon completing this training, participants will be able to:

• Configure and integrate Splunk, Moogsoft, and Dynatrace into a unified AIOps architecture.
• Correlate metrics, logs, and events across distributed systems using AI-driven analysis.
• Automate incident detection, prioritization, and response through built-in and custom workflows.
• Optimize performance, reduce MTTR, and enhance operational efficiency at an enterprise scale.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practice opportunities.
• Hands-on implementation in a live-lab environment.

Customization Options

• To request customized training for this course, please contact us to arrange.

Prometheus and Grafana are industry-standard tools for monitoring modern infrastructure, while machine learning augments these platforms with predictive and intelligent insights to automate operational decisions.

This instructor-led live training (available online or onsite) targets intermediate-level observability professionals looking to modernize their monitoring infrastructure by adopting AIOps practices through Prometheus, Grafana, and machine learning techniques.

Upon completing this training, participants will be capable of:

• Configuring Prometheus and Grafana to monitor systems and services effectively.
• Gathering, storing, and visualizing high-fidelity time series data.
• Implementing machine learning models for anomaly detection and predictive forecasting.
• Developing intelligent alerting rules derived from predictive insights.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live laboratory environment.

Customization Options

• For customized training requests, please reach out to us to arrange the session.