ANOMALIES MANAGEMENT SOLUTION
Improve the awareness and understanding of network performance deviations
CSPs face challenges in swiftly detecting anomalies while minimizing false positives. Identifying root causes within a dynamic network, integrating diverse data, and ensuring scalability present complexities.
Managing the immense volume and complexity of network data poses difficulties. Analyzing diverse data sources for anomalies requires sophisticated tools and algorithms
Data volume and complexity
Minimizing false positives is crucial. Overly sensitive anomaly detection systems can generate unnecessary alerts, leading to resource wastage and decreased efficiency.
Navigating the ever-changing landscape of network environments poses a continual challenge. Alterations in network configurations and traffic patterns have the potential to affect the accuracy of anomaly detection.
Dynamic network traffic patterns
Unifying data from varied sources, including performance metrics, logs, and user behavior, into an anomaly detection system necessitates meticulous coordination.
Integration of Data Sources
Pinpointing the root cause of anomalies is intricate. Multiple interconnected network elements make it challenging to trace issues back to their origin accurately.
Multi-domain root-cause identification
Using a single tool for network anomaly understanding is challenging due to the diverse data types in networks. Different tools are often required for comprehensive analysis and accurate insights.
Multiple tools needed
Kenmei's Anomalies Management solution enables CSPs to detect network deviations and gain insights into their root causes, enhancing awareness and facilitating proactive issue resolution.
Multi-data source integration in one single tool with Root Cause Analysis.
ONE SINGLE TOOL
The Root Cause Analysis algorithm identifies the network deviation reason.
ROOT CAUSE ANALYSIS
The solution automatically identifies the clusters with similar patterns.
AUTOMATIC CLUSTER ANALYSIS
The solution integrates Alarms, Work Orders, Counters, Topology, Parameters, Inventory, Open Data, etc.
MULTI-DOMAIN DATA INTEGRATION
Automated anomaly detection and root cause analysis enhance overall network performance by swiftly identifying issues, minimizing downtime, improving efficiency, and ensuring a reliable and secure network environment.
Accelerates resolution time by utilizing automatic correlation of data sources and efficient root cause analysis.
Accelerate Mean Time to Resolution
Engineers now spend fewer hours on the comprehensive analysis of network performance deviations compared to previous practices.
Engineering hours reduction
Be mindful of anomalies, understanding their influence on cluster areas.
Analyze the impact on clusters rather than individual cells
The solution incorporates multiple rules to alert you to previously unrecognized issues.