AIOps Training in the Netherlands

Developing an AIOps pipeline entirely with open-source tools enables teams to craft cost-efficient and adaptable solutions for observability, anomaly detection, and intelligent alerting within production environments.

This instructor-led live training (available online or onsite) is designed for advanced-level engineers aiming to build and deploy an end-to-end AIOps pipeline utilizing tools such as Prometheus, ELK, Grafana, and custom ML models.

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

• Architecting an AIOps structure using exclusively open-source components.
• Gathering and standardizing data from logs, metrics, and traces.
• Applying machine learning models to identify anomalies and predict incidents.
• Automating alerting and remediation processes using open tooling.

Course Format

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

Customization Options

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

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

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

Upon completion of this training, participants will be able 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, prioritization, and response through built-in and custom workflows.
• Enhance performance, reduce MTTR, and improve operational efficiency at an enterprise scale.

Course Format

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

Customization Options

• To request a customized training for this course, please contact us to make arrangements.

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.

Prometheus and Grafana are extensively adopted tools for ensuring observability in modern infrastructure. The integration of machine learning enriches these platforms with predictive capabilities and intelligent insights, thereby automating operational decision-making.

This instructor-led training, available either online or onsite, is designed for observability professionals with intermediate expertise who aim to modernize their monitoring systems by incorporating AIOps methodologies using Prometheus, Grafana, and machine learning techniques.

Upon completing this training, participants will be capable of:

• Configuring Prometheus and Grafana to ensure observability across various systems and services.
• Collecting, storing, and visualizing high-quality time series data.
• Applying machine learning models for the purpose of anomaly detection and forecasting.
• Constructing intelligent alerting rules grounded in predictive insights.

Format of the Course

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

Course Customization Options

• For customized training arrangements for this course, please contact us to discuss your requirements.

AIOps (Artificial Intelligence for IT Operations) represents a methodology that leverages machine learning and advanced analytics to automate and enhance IT operations. This approach is particularly effective in the domains of monitoring, incident detection, and response.

This instructor-led training session, available either online or onsite, targets intermediate-level IT operations professionals eager to apply AIOps techniques. The goal is to correlate metrics and logs, minimize alert noise, and enhance observability through intelligent automation.

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

• Grasp the core principles and architectural frameworks of AIOps platforms.
• Correlate data from logs, metrics, and traces to pinpoint root causes effectively.
• Alleviate alert fatigue by employing intelligent filtering and noise suppression strategies.
• Utilize open-source or commercial solutions to automatically monitor and respond to incidents.

Course Format

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

Customization Options

• For tailored training requirements, please reach out to us for arrangement.

This instructor-led live training in the Netherlands (online or onsite) is designed for observability and SRE engineers aiming to integrate LLMs and AI into their monitoring, alerting, and incident analysis workflows.

This instructor-led, live training in the Netherlands (online or onsite) is aimed at SRE and DevOps engineers who want to design, build, and safely deploy AI agents for autonomous IT operations.

This instructor-led, live training in the Netherlands (online or onsite) is aimed at ML engineers and platform teams who need to build robust operational pipelines for LLM-powered applications at scale.

This instructor-led, live training in the Netherlands (online or onsite) is aimed at security and ML engineers who need to identify, test, and defend against attacks on ML models and LLM-powered applications.