The Convergence of Service Fulfillment and Assurance in Next-Generation OSS
As OSS evolves alongside hybrid, cloud and digital environments, bridging fulfillment and assurance will ease closed-loop operations and enable the delivery of more complex services.
Service fulfillment and service assurance were once very separate activities. In the digital service era, the two disciplines are increasingly becoming two parts of the same closed-loop process. Providing real-time intelligence about the status of the network and, more specifically, the network portion used to deliver specific services is now critical to operational optimization and service-level automation.
Connecting Assurance Data Into Fulfillment
Resource monitoring on the assurance side and in the network provides key information which is pertinent to the concept of a real-time active inventory. During the provisioning process, it has always been critical to have the correct view of available network resources, but in the digital service era, this status view is becoming more dynamic. Because hybrid network environments hold much more dynamic data on the current state of network assets, fault and performance data become relevant on much shorter cycles than in previous OSS iterations. We know that digital services can be much more ephemeral than traditional connectivity packages, and so the provisioning and de-provisioning of service components becomes more reliant on real-time intelligence.
Developing this new OSS format must have the usual considerations that we associate with modern leading telecoms software solutions: DevOps-based, open standards-based APIs, “real-time” capabilities, etc.
This provisioning intelligence should not be limited to the availability of capacity or allocations that can be made on certain network routes, but should also be looking at the health of granular sections of the network and across all domains. In this way, a deeper level of network optimization can be achieved, especially when using SDN/NFV elements as well as physical networks to fulfill services.
Native AI and ML Across OSS Enable Automation and Optimization
Artificial intelligence (AI) and machine learning (ML) enable highly effective approaches to processes like provisioning with the optimum amount of awareness baked into the decision-making. If common AI and ML functions are built into both the assurance and fulfillment systems, they can share highly actionable data-driven insights from performance monitoring, fault management and various other assurance touchpoints. AI and ML have an increased propensity for dynamic decision-making (instead of a rules-based approach) and can enable maximum automation and optimization through the closed loop.
Cloud-Enabled Fulfillment and Assurance in Next-Generation OSS
Developing this new OSS format must have the usual considerations that we associate with modern leading telecoms software solutions: DevOps-based, open standards-based APIs, “real-time” capabilities, etc. In addition, the solutions must be conceived with a cloud-enabled mindset. In a hybrid network, assurance will be collecting data on VNFs that are being created, changed and deleted according to the needs of the service. Assurance needs to be able to behave in the same way, although monitoring both traditional physical/logical networks and virtualized networks has obvious complications. Hybrid operations will be around for at least another decade, but, in terms of future-proofing, leading systems should be based in the cloud so they can line up with the native cloud operations of the following decade.
Orchestration in the Loop
The management and orchestration of service-centric operations should be a key part of the story in the converging spheres of fulfillment and assurance. In the fulfillment of a simple digital service, an orchestrator may run an automated workflow through several new modern systems, down into VNF management and activation of the service. However, in a more complex hybrid case in which legacy inventory must be interrogated, physical network activation triggered, etc., assurance data becomes essential to successfully fulfill the service without the need for the order to drop out of the automated path and enter a work queue for operations staff to manually activate.
This becomes especially relevant with the growth of network slicing under a 5G paradigm. The need for full automation is obvious in fulfilling complex enterprise services that involve a network slice, which may be provided over a hybrid network, depending on a myriad of geographical and domain-specific factors. Hence, the need for the loop of data intelligence in core OSS is not something that is needed for the mid-2020s but already showing benefits to service operations in 2019.