Lilly Tech Systems
AIOps for Networking
Apply AIOps principles to network operations: correlate events across thousands of devices, reduce alert noise by up to 95%, automate incident response, and leverage platforms like Datadog, Splunk, and PagerDuty for intelligent network management.
What You'll Learn
Master AIOps techniques specifically designed for network operations teams.
Event Correlation
Use AI to correlate thousands of network events into meaningful incidents, identifying root causes across complex topologies.
Noise Reduction
Eliminate alert fatigue with ML-based deduplication, suppression, and intelligent alert grouping techniques.
Automated Response
Build automated runbooks that diagnose and remediate common network issues without human intervention.
AIOps Platforms
Hands-on with Datadog, Splunk ITSI, and PagerDuty for implementing AIOps in real network environments.
Course Lessons
Follow the lessons in order or jump to any topic you need.
1. Introduction
What is AIOps? Understanding the pillars of AIOps, its evolution from traditional monitoring, and the value proposition for networking.
2. Event Correlation
Temporal and topological event correlation, dependency mapping, root cause analysis algorithms, and service impact analysis.
3. Noise Reduction
Alert deduplication, flapping detection, dynamic thresholds, anomaly-based alerting, and intelligent alert routing.
4. Automation
Automated diagnostics, self-healing runbooks, escalation logic, change correlation, and post-incident analysis.
5. Platforms (Datadog/Splunk/PagerDuty)
Hands-on guides for configuring AIOps features in Datadog, Splunk ITSI, and PagerDuty for network operations.
6. Best Practices
Building an AIOps culture, measuring success with KPIs, phased adoption roadmap, and avoiding common pitfalls.
Prerequisites
- Experience with network monitoring and alerting systems
- Understanding of ITIL/ITSM incident management processes
- Familiarity with at least one monitoring platform
- Basic understanding of AI/ML concepts