Beyond the Silos: How Reailize's Network Health Index is Redefining Traditional Monitoring

Beyond the Silos: How Reailize's Network Health Index is Redefining Traditional Monitoring

Reailize’s Network Health Index (NHI) solution is designed to transform how network operators monitor and manage their networks. Traditionally, network monitoring has been fragmented across various domains and layers:

• Radio Access Network (RAN)

• Transport

• Core

• IP Multimedia Subsystem (IMS)

• Physical infrastructure

• Cloud monitoring

• Operating systems

• Application performance

This siloed approach has led to significant challenges in troubleshooting and identifying the root causes of network issues. When problems arise, teams often struggle to pinpoint the exact origin, leading to prolonged resolution times and potential customer dissatisfaction. To alleviate the challenges, many operators have relied on probe-based systems to gain visibility into control plane and user plane data. While these systems offer valuable insights, they come with substantial drawbacks:

• High costs associated with matching probe capacity to network size

• Frequent upgrades required to keep pace with traffic growth

• Scalability issues as networks expand

Reailize's Innovative Solution: The Network Health Index

Our Network Health Index offers a comprehensive, cost-effective alternative to traditional monitoring methods. It breaks down the silos that have long plagued network monitoring. Here's how it works:

1. Domain/Layer Health Index

We leverage performance management data across all network domains and layers to calculate a domain level "Health Index". This approach allows to create a domain-agnostic normalized score that represents the significance of anomalies within a specific network area.  

2. Aggregation Along Network Topology

The Domain/Layer Health Indices are aggregated along the network topology for each time granularity to form the comprehensive Network Health score. This process provides a holistic view of network health that allows to drill down into domains, layers, network areas, individual network elements and top contributing KPIs to best understand where the issues originate from.  

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3. Anomaly Score Calculation

At the heart of our NHI is an aggregated anomaly score. This score is:

• Updated at each time granularities

• Includes a vector of top metric contributors

• Identifies which parameters most significantly impact the anomaly score

Moreover, our solution employs a sophisticated anomaly detection algorithm based on Mahalanobis Distance (MD). This approach offers several advantages over traditional models:

1. Multivariate Analysis: Unlike systems that only detect anomalies within individual metrics, our MD-based algorithm identifies anomalies in both metric behavior and their interrelations.

2. Correlation Related Anomalies: For example, if a router's CPU level increases without a corresponding rise in traffic, our system flags this as an abnormal scenario, even if CPU levels appear within expected thresholds.

3. Unprecedented Accuracy: Performance tests have shown an extremely high accuracy for this model, with the Area Under Curve (AUC) exceeding 0.98. In statistical terms, AUC is a measure of the algorithm's performance, with values closer to 1 indicating high accuracy in distinguishing between normal and abnormal network states. To illustrate the power of MD, consider the following scenario:

As we can see, the MD provides a more accurate representation of the significance of anomalies compared to traditional Euclidian-based scores.

Proactive Change Management and Alarm Correlation

Our NHI solution goes beyond mere anomaly detection by including Temporal Correlation and Reduced Unnecessary Troubleshooting. Respectively, we correlate the NHI with change management events and network alarms by linking detected anomalies directly to known events and incidents—thus minimizing time wasted on issues with already-identified causes. However, this does not imply customer impact is deprioritized. Understanding that not all network issues are created equal, our solution offers:

• Weighting of anomaly scores based on the number of concurrent users affected by a specific network element.

• Ability to prioritize network performance issues based on their impact on customer experience.

This approach ensures that operators can focus their efforts where they matter most, maximizing the efficiency of their response processes.

The Big Picture: Transforming Network Monitoring

With Reailize's Network Health Index, network operators gain:

1. An end-to-end view of network health

2. Rapid detection of performance issues across the global network

3. Precise identification of anomaly sources and associated metrics

This bottom-up visibility and unified approach streamline troubleshooting, reduce resolution times, and significantly enhance the overall customer experience. By providing a comprehensive, accurate, and customer-focused approach to network monitoring, we're empowering operators to stay ahead of issues, optimize performance, and deliver the seamless connectivity that today's consumers demand.  

Ready to revolutionize your network monitoring? Contact us today for a personalized demonstration and take the first step towards unparalleled network visibility and performance.