Multi‑Domain Orchestration

Key Topics Covered

• Foundations of closed-loop automation, including the Monitor–Analyse–Decide–Act model and its role in improving service reliability, efficiency, and SLA performance across network domains
  
• Telemetry and real-time observability, covering data collection from multi-domain sources, streaming analytics, and integration with assurance systems
  
• Analytics and decision-making frameworks, including rule-based and AI-driven policy engines for SLA monitoring, predictive analysis, and automated decision triggers
  
• Automated orchestration and remediation actions, enabling scaling, rerouting, reconfiguration, and fault recovery across RAN, Core, Transport, and Cloud
  
• End-to-end service assurance integration, including KPI monitoring, SLA enforcement, incident automation, and alignment with operational processes

Learning Outcomes

• Apply closed‑loop automation frameworks (monitor → analyse → decide → act)
  
• Identify relevant telemetry/KPI sources for real‑time decisions
  
• Explain interplay between analytics engines and orchestration layers
  
• Understand assisted vs full closed‑loop implementation models.

Target Audience

• Network automation engineers
  
• AI/analytics engineers supporting network assurance
  
• OSS platform architects
  
• Operations teams responsible for service assurance and performance