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