Platforms (Datadog/Splunk/PagerDuty) Intermediate

Three leading platforms offer strong AIOps capabilities for network operations. This lesson provides hands-on guidance for configuring each platform's AI features for networking use cases.

Datadog for Network AIOps

• Watchdog — Automatic anomaly detection across all metrics. No configuration needed — it learns patterns and alerts on deviations
• Network Performance Monitoring (NPM) — Flow-level visibility with AI-powered analysis of network paths
• Network Device Monitoring — SNMP-based monitoring with anomaly detection for network devices
• Anomaly Monitors — Create monitors that use ML algorithms (agile, robust, adaptive) instead of static thresholds
• Forecast Monitors — Alert when a metric is predicted to cross a threshold in the future

Splunk ITSI

• Service Models — Define services with KPIs that map to network infrastructure health
• Adaptive Thresholding — ML-based thresholds that adapt to daily and weekly patterns
• Event Analytics — Correlation of events across multiple data sources into notable events
• Predictive Analytics — MLTK (Machine Learning Toolkit) for custom network analytics
• Glass Tables — Visual service health dashboards with real-time KPI status

PagerDuty AIOps

• Intelligent Alert Grouping — ML automatically groups related alerts into a single incident
• Noise Reduction — Suppress transient alerts and deduplicate across integration sources
• Past Incidents — Surface similar historical incidents for context during active response
• Event Intelligence — ML-based triage, priority scoring, and routing recommendations
• Automation Actions — Trigger diagnostic runbooks and remediation workflows from incidents

Platform Comparison