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

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.

Leveraging exclusively open-source tools to build an AIOps pipeline enables teams to create scalable and cost-efficient solutions for observability, anomaly detection, and intelligent alerting within production environments.

This instructor-led training, available both online and onsite, is designed for advanced engineers aiming to implement an end-to-end AIOps pipeline. Key tools covered include Prometheus, ELK, Grafana, and custom machine learning models.

Upon completion of this course, participants will be able to:

• Architect an AIOps infrastructure using only open-source components.
• Gather and standardize data from logs, metrics, and traces.
• Utilize machine learning models to identify anomalies and forecast incidents.
• Automate alerting and remediation processes using open-source tooling.

Course Format

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

Customization Options

• For customized training arrangements, please contact us directly.

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

This instructor-led training, available online or onsite, is designed for intermediate-level enterprise IT teams looking to incorporate AIOps tools into their current observability frameworks and operational workflows.

Upon completing this training, participants will be equipped to:

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

Course Format

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

Customisation Options

• To request a tailored training session for this course, please get in touch to make arrangements.

Prometheus and Grafana are industry-standard tools for ensuring observability within modern infrastructure. By integrating machine learning, these platforms gain the ability to deliver predictive and intelligent insights, thereby automating operational decision-making.

This instructor-led live training, available either online or onsite, is designed for observability professionals with intermediate-level expertise. It aims to help participants modernise their monitoring infrastructure by incorporating AIOps practices using Prometheus, Grafana, and machine learning techniques.

Upon completion of this training, participants will be equipped to:

• Configure Prometheus and Grafana to provide observability across various systems and services.
• Collect, store, and visualise high-quality time series data.
• Apply machine learning models for the purposes of anomaly detection and forecasting.
• Develop intelligent alerting rules driven by predictive insights.

Course Format

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

Course Customisation Options

• To arrange a customised training session for this course, please contact us.