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VMware SD-WAN Release 4.1.0

SD-WAN release
November 6, 2020
VMware SD-WAN release updates
Availability of the AIOps solution, VMware Edge Network Intelligence™, which integrates with VMware SD-WAN™ to offer insights all the way to users and things (IoT) to deliver a complete, end-to-end  understanding of the entire edge network. The analytics solution helps enterprises make sense of the massive amount of SD-WAN data and helps ensure better network performance, while end-users and IoT devices gain higher productivity.

Click here to learn more about patch release 4.1.1.

New Features on Orchestrator UI:
  • Enable Analytics collection for Edge Network Intelligence
  • Cross reference Edge Network Intelligence UI for visibility and insights
Benefits of the Integrated Solution:
  • Application assurance: Analyzes over 3000 applications, tracking performance for fault detection and fault isolation.  This helps IT teams determine the worst-performing clients for an application, identify if the problem is systemic or isolated, and compare performance with other locations within the organization and with peers in the industry.  
  • Wireless and wired end client experience: Significantly improves and quantifies the end user and IoT device experience at any location, helping pinpoint with clarity whether a perceived application problem is due to issues with the local Wi-Fi network, broadband network, WAN, network services or with the application.  
  • Business continuity and work from home: Helps IT teams manage their remote workforce by collecting application data related to user experience directly from SaaS applications, and combining it with telemetry received from an optional client application installed on the end user device.  
  • Change verification and ROI:Offers change verification by comparing performance before and after a change.  This provides quantifiable data on whether a change has resolved an issue or whether a rollback is required, instead of waiting for users to open cases to find out. This helps justify the ROI.  
  • Fault isolation and recommendations: Can isolate a fault to the client LAN, WAN, data center LAN, cloud, the internet or the application. Using ML algorithms, such as clustering, analyzes historical network data to determine where the problem occurs and makes recommendations and predictions to IT.  
  • IoT operational assurance: Leverages an ML-based hierarchical device classification system and uses the detailed behavioral signature of each detected device. It automatically inventories and classifies IoT devices, and flags anomalous behavior from a security threat perspective.