The Criticality of SDN Analytics Data

To reduce costs, SDN can make it possible to run service provider networks at around 70 percent or greater link utilizations.

Why Traditional SDN Architectures Are Insufficient

SDN can help address these challenges and streamline network provisioning. Figure 1 illustrates a simple two-tier architecture in which SDN applications control network behavior. Network devices (both physical and virtual) are not configured manually. Rather, they are programmed via southbound APIs by one or more SDN controllers or service orchestrators, which perform higher-level orchestration functions across domains and sometimes across the IP/MPLS and optical layers. The controllers provide access to applications via northbound APIs, enabling the applications to modify network behavior to meet their needs. 

                                       Figure 1 — Traditional Two-tier WAN-SDN Architecture

Although SDN controllers provide the means to change network configurations through software, they lack management intelligence. For example, they cannot answer basic questions such as: 

  • If applications and services are being rolled out without operator intervention and adequate visibility, how can network operators plan for them?
  • Who or what determines if these programmatic changes should be made?
  • Will the changes negatively impact existing applications and services?
  • When changes are problematic, how does the operator diagnose the problem or find the root cause?

To answer these questions in dynamic networks requires analytics.

Analytics Defined

SDN management requires much data about what is happening in the network, such as IGP topology, BGP routes, traffic demands, jitter, performance, delay, and interface utilizations. The industry talks a lot about this telemetry, but it is simply the collection of this data. It represents the beginning of effective SDN management. Many big data projects overload engineers with data, but then don’t tell them what to do with it. 

Analytics are the actionable conclusions drawn from the data. SDN analytics provide the visibility and management intelligence service providers need to run their automated networks effectively. They help answer in seconds the planning and troubleshooting questions that engineers may spend hours or days on using manual methods. 

Two Functions for SDN Analytics

The first function of SDN analytics is to maintain management visibility into the network as programmatic changes are being made. SDN analytics should provide visibility into the devices and controllers by recording real-time telemetry from the network’s control and data planes, including the routing topology, performance metrics, and traffic flow data. Recorded data helps with back-in-time forensics to identify the root cause of issues.

The second and more important function of SDN analytics is to provide management intelligence. Analytics software replicates the expertise of network planning groups, assessing the network’s readiness and capacity for making significant changes, acquiring a new enterprise customer, or turning on a new service.

Once the SDN analytics software comes up with a solution based on telemetry data, the SDN controller or orchestrator can provision it in the network. 


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