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iMaster NCE-FabricInsight

iMaster NCE-FabricInsight is an intelligent analysis platform designed for data center networks. Based on big data analytics, the platform provides users with comprehensive network application analysis and visualization, eliminating the boundary between applications and networks.

Meanwhile, telemetry enables the collection of a massive number of real service packets and displays network quality in real time, helping customers quickly identify, locate, and rectify faults, proactively identifying risks before services are affected.

Based on Huawei's best IT practices, iMaster NCE-FabricInsight meets the intelligent Operations and Maintenance (O&M) requirements for data centers of financial and other large enterprise customers.

  • Huawei
    troubleshooting
    Proactive Network Health Evaluation

    Evaluates network health based on a five-layer evaluation system, identifying 90% of potential risks.

  • Huawei
    Data Search
    "1-3-5" Troubleshooting

    Builds network knowledge graphs based on AI algorithms, detecting typical faults within one minute, locating root causes within three minutes, and rectifying faults within five minutes.

  • Huawei
    Threat Detection
    Network-Wide Full Flow Analysis

    Analyzes network-wide full flows based on TCP/UDP and performs correlated analysis between applications and networks, demarcating performance issues within minutes.

Huawei

Specifications

iMaster NCE FabricInsight provides standard and advanced solutions.


Parameters Overview

The standard solution supports standalone node deployment and is compatible with SDN and non-SDN networks.

Network Health Evaluation Evaluates network health from multiple dimensions.
Exports evaluation reports in real time or periodically.
"1-3-5" Troubleshooting Quickly detects faults, locates their root cause, and rectifies faults.
Telemetry-powered Analysis Monitors and analyzes KPIs of devices, boards, chips, interfaces, queues, and optical links.
Network Change Visibility Compares and analyzes network changes from dimensions such as configurations and entries.
Log Analysis Monitors and analyzes device exception logs.
System Monitoring Supports system monitoring, license management, resource management, and network topology management.

Based on the standard solution, the advanced solution provides the following functions and uses cluster deployment mode.
Application and Network Association Analysis Analyzes application health status.
Analyzes interactions between applications and displays application interaction relationships in the topology.
Supports intra-application interaction analysis and mutual visibility between applications and networks.
TCP Service Flow Analysis Supports visualizuation of top N statistics and analysis of hosts, applications, and sessions.
Allows users to view the number of SYN events, abnormal TCP events , traffic, and delays in a specified period.
Enables users to view details about packet loss events.
Combines packets for analysis in the 1:1 NAT mapping scenario.
Supports abnormal flow fault reasoning and one-click troubleshooting.
Edge Intelligence Analysis Supports intelligent traffic analysis based on the triplet rules of the specified TCP source IP address, destination IP address, and destination port. The system can display information such as the number of sessions with packet loss, total number of sessions, number of lost packets over the total number of packets/traffic in the request direction, number of lost packets over the total number of packets/traffic in the response direction, and application interactions based on the specified rule.
Supports intelligent traffic analysis based on the triplet rules of the specified UDP source IP address, destination IP address, and destination port. The system can display information such as the number of sessions with packet loss, total number of sessions, number of lost packets, total number of packets, discarded traffic, total traffic, average latency, maximum latency, and application interactions based on the specified rule.

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