AIOps with Prometheus, Grafana and ML Training in India

This course teaches participants how to build intelligent IT operations using Prometheus and Grafana, enhanced with machine learning capabilities.

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AIOps with Prometheus, Grafana and ML Training is a professional training program delivered by ProgNXT, a globally recognized corporate training provider. ProgNXT's AIOps with Prometheus, Grafana and ML Training course in India equips professionals with industry-relevant skills through hands-on, instructor-led sessions. This hands-on course teaches participants how to build intelligent IT operations using Prometheus and Grafana, enhanced with machine...

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Designed by the ProgNXT AI & Data Science Expert Panel, specializing in Generative AI, Machine Learning, and ChatGPT applications

Advanced Monitoring with Prometheus and Grafana

Introduction to Intelligent Monitoring

Defining AIOps in the context of Prometheus and Grafana
Overview of time-series monitoring
Benefits of ML in observability pipelines
Architecture for AIOps with Prometheus + Grafana + ML

Prometheus Deep Dive

Data scraping, exporters, and relabeling
Writing effective PromQL queries
Best practices for metric naming and retention
Federation and scaling in large environments

Grafana for Operational Insights

Advanced dashboard features and templating
Using transformations, variables, and drilldowns
Real-time vs historical data views
Sharing, exporting, and alerting from Grafana panels

Alerting and Anomaly Detection with Machine Learning

Prometheus Alerting Concepts

Alert rules vs recording rules
Alertmanager setup and routing
Silence, inhibition, and grouping alerts
Alert reliability and anti-flapping techniques

Anomaly Detection Techniques

Static vs dynamic thresholds
Time-series forecasting and outlier detection
Use cases for contextual and seasonal anomalies
Approaches: Holt-Winters, ARIMA, Z-score, Isolation Forest

ML Integration in Grafana and Prometheus

Grafana ML plugins (Grafana Machine Learning, Prophet panel, etc.)
Using Grafana with Python-based ML (Jupyter, Flask API)
External anomaly detection pipelines and webhooks to Alertmanager
Integrating with external ML tools (e.g., TensorFlow, Scikit-learn)

Automating Intelligence and Building AIOps Pipelines

Predictive Monitoring and Trend Analysis

Long-term trend analysis with Prometheus and Grafana
Forecasting system load, memory, or latency
Early warning systems with prediction intervals
Custom ML models for specific operational metrics

Alert Enrichment and Automation

Enhancing alerts with logs, tags, and historical data
Integration with incident management tools
Triggering remediation workflows via webhooks or automation tools
Alert correlation and deduplication patterns

Building a Complete AIOps Stack

Full pipeline: exporters → Prometheus → ML → Grafana → Alerting
Review open source ML tool options: Sktime, Prophet, PyCaret, etc.
Key architectural considerations for enterprise use
Security, scalability, and maintainability

Final Assessment and Project Review

Wrap-up, Q&A, and next steps for real-world adoption

ProgNXT AI & Data Science Expert Panel

Course Code: NLT46
21 Hrs
Course Rating 4.9/5
Last Updated: April 2026

This hands-on course teaches participants how to build intelligent IT operations using Prometheus and Grafana, enhanced with machine learning capabilities. The course covers advanced monitoring, anomaly detection, alerting, and visualization, along with ML integration to enable predictive and automated operations workflows.

Welcome to the official AIOps with Prometheus, Grafana and ML Training certification program. This comprehensive training is designed to elevate your professional skills and provide you with practical, industry-relevant knowledge in in India. As a globally recognized corporate training provider operating in 55+ countries, ProgNXT ensures that our curriculum meets the highest standards of excellence.

Whether you are looking to upskill your team or advance your personal career, our expert-led sessions will guide you through the core concepts of this domain. Upon successful completion of the 21 Hrs program, participants will receive a globally accepted certification, demonstrating their proficiency and readiness to tackle complex challenges in the field.

Familiarity with Linux and basic shell scripting
Experience with system or application monitoring
Knowledge of Prometheus and Grafana fundamentals
Basic understanding of time-series data and alerting concepts
No prior ML experience required (concepts introduced in training)

Set up and manage advanced Prometheus-Grafana monitoring systems
Design efficient metrics pipelines and visualization dashboards
Detect anomalies and trends using ML models in Grafana and Prometheus
Integrate ML-driven alerting into DevOps workflows
Use open source ML tools to automate operational intelligence

By the end of this course, participants will be able to build an intelligent monitoring stack with Prometheus and Grafana, apply machine learning to detect anomalies and performance trends, and enable automated, intelligent alerting and remediation within their infrastructure.

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