Turn multi-layer operational data into actionable intelligence

Odine MACE Sense continuously observes operational data across cloud, network and infrastructure environments. It correlates KPIs, events, alarms and system signals, detects anomalies and helps teams identify probable root causes before issues turn into service-impacting incidents.

  • Collect and correlate multi-layer operational data
  • Detect anomalies and early signs of service degradation
  • Predict KPI impact of changes, faults and system behavior
  • Accelerate troubleshooting and root cause analysis
  • Improve service and infrastructure monitoring
  • Support proactive issue detection and prevention

From monitoring to operational foresight

Modern cloud and telco cloud environments generate large volumes of data across hardware, operating systems, virtualization layers, IP networks, applications, services and user activities. When this data remains fragmented, teams face blind spots, longer troubleshooting cycles and difficulty understanding service impact.

Odine MACE Sense brings these signals together into an AI-native service assurance layer. It helps teams understand current performance, predict potential KPI impact, detect abnormal behavior and accelerate resolution across complex operational environments.

  • Cross-Layer Signal Correlation

    Collects and correlates KPIs, counters, alarms, events and system metrics across cloud, data center, IP network and service layers.

    Anomaly Detection

    Identifies abnormal behavior and early indicators of service degradation before they affect availability or performance.

    Root Cause Analysis

    Supports faster troubleshooting by highlighting probable root causes across multi-layer and multi-vendor environments.

    KPI Impact Prediction

    Applies AI and ML models to predict the potential impact of changes, faults and system behavior on service and infrastructure performance.

  • Infrastructure Health Intelligence

    Monitors performance, configuration and system health across cloud, data center and infrastructure environments, including virtual services, hardware, Kubernetes, hypervisors, OpenStack and IP networks.

    Proactive Issue Detection

    Helps teams detect and prevent potential issues earlier through continuous monitoring, correlation and predictive insight.

    Capacity and Risk Forecasting

    Supports forward-looking visibility into resource pressure, capacity risks and potential service-impacting conditions.