ML KPIs and Automated Insights > Current Health Index

Current Health Index (CHI)

The platform employs a Statistical model-based scoring system for each component type, offering a standardized measure of the system’s current health and performance. While OPI focuses on potential future failures, CHI provides an assessment of the present health.

CHI scores are generated for various components such as Servers, Databases, middleware, Network Links, and Network devices. Here are a few examples of CHI scores:

Server Health Index 

The Server Health Index (SHI) serves as an indicator of the overall health of a server. It is derived by consolidating individual Server Performance Indices (SPIs) related to CPU, Memory, and Disk Utilization.

Key Benefits:

  • Simplified Monitoring: Monitor server health through a single index instead of juggling multiple golden signals.
  • Comprehensive Alerts: Receive a consolidated alert rather than multiple alerts for the same server. This alert provides detailed information about problematic golden signals.
  • Reduced Redundancy: By consolidating alerts, eliminate redundancy and enable a focused response to address underlying issues.
  • Suppressed Alert Noise: Avoid unnecessary distractions by consolidating alerts, preventing critical alerts from being overlooked amidst a flood of notifications.

Network Health Index

The ML-driven Network Experience Index (NEI) serves as a precise depiction of the current state of a link, considering both health and performance metrics. NEI is a consolidated score at the WAN link level, derived by combining individual scores from Network Performance Indices (NPIs) associated with that WAN link.

For each WAN link, the NEI score is derived by considering golden signals from three main categories:

The behavior of the Network Performance Index score is explained using the below two scenarios:

Scenario #1:

Imagine the Network Performance Index (NPI) score starting at 10 when the network’s bandwidth utilization is within the defined limit. However, as the utilization increases and hits the maximum on a few occasions, the NPI score gradually drops. When the utilization reaches the maximum, the NPI score hits 0, signaling a critical state due to the maximum utilization.

Scenario #2:

Now, suppose the bandwidth utilization hits the maximum and stays there for about 35 minutes. During this time, the NPI score starts declining because the network is operating at full capacity. Eventually, the NPI score reaches 0, indicating a critical network performance state. This situation continues until the utilization starts dropping, indicating either a decrease in network demand or an improvement in the network’s capacity to handle the traffic.

Closely tracking the NPI score in relation to input bandwidth utilization allows organizations to pinpoint stressful or congested periods. This insight empowers them to optimize network resources, make needed upgrades, or adjust capacity planning to uphold a satisfactory level of network performance.

Further Reading

  1. ML KPIs and Automated Insights
  2. User Experience Index
  3. Operational Predictive Index
  4. ML Automated Insights


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