AIOps (Artificial Intelligence for IT Operations) uses machine learning to help IT systems see, think, and respond faster than humans ever could.
Our instructor-led courses teach how to apply AI to automate root cause analysis, predict outages, detect anomalies, and streamline incident management.
Online live training is delivered via interactive remote desktop, while onsite sessions in Guatemala City dive deep into hands-on labs with real-world alerts, logs, and telemetry.
From data centers to war rooms, onsite training can unfold at your organization’s location in Guatemala City, or in a NobleProg facility designed for troubleshooting, collaboration, and system resilience.
Also known as AI for IT Operations or Intelligent IT Monitoring, AIOps training empowers teams to shift from manual firefighting to predictive, data-driven operations.
NobleProg – Your Local Training Provider
Guatemala - Europlaza
5a Avenue 5-55 Zone 14, Guatemala City, Guatemala, 1014
The Guatemala Europlaza Center is located on the second floor of one of the four modern 19-story towers that form the Europlaza World Business Center. The Guatemala Europlaza Center is convenient for public transport connections, including the new Transmetro bus system introduced to improve traffic flow, and the city Center is just 10 minutes away.
Guatemala - Citibank Tower
3r avenue 13-78, zone 10 , Guatemala City, Guatemala, 01010
Experience convenient access to Citibank Tower via public transportation or by car, with on-site parking available. Additionally, relish seamless international travel with the airport a mere 15-minute drive from the tower.
An AIOps pipeline built entirely with open-source tools allows teams to design cost-effective and flexible solutions for observability, anomaly detection, and intelligent alerting in production environments.
This instructor-led, live training (online or onsite) is aimed at advanced-level engineers who wish to build and deploy an end-to-end AIOps pipeline using tools like Prometheus, ELK, Grafana, and custom ML models.
By the end of this training, participants will be able to:
Design an AIOps architecture using only open-source components.
Collect and normalize data from logs, metrics, and traces.
Apply ML models to detect anomalies and predict incidents.
Automate alerting and remediation using open tooling.
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.
Enterprise AIOps platforms like Splunk, Moogsoft, and Dynatrace provide powerful capabilities for detecting anomalies, correlating alerts, and automating responses across large-scale IT environments.
This instructor-led, live training (online or onsite) is aimed at intermediate-level enterprise IT teams who wish to integrate AIOps tools into their existing observability stack and operational workflows.
By the end of 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 with built-in and custom workflows.
Optimize performance, reduce MTTR, and improve operational efficiency at enterprise scale.
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.
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 widely adopted tools for observability in modern infrastructure, while machine learning enhances these tools with predictive and intelligent insights to automate operations decisions.
This instructor-led, live training (online or onsite) is aimed at intermediate-level observability professionals who wish to modernize their monitoring infrastructure by integrating AIOps practices using Prometheus, Grafana, and ML techniques.
By the end of this training, participants will be able to:
Configure Prometheus and Grafana for observability across systems and services.
Collect, store, and visualize high-quality time series data.
Apply machine learning models for anomaly detection and forecasting.
Build intelligent alerting rules based on predictive insights.
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.
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.
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