Digital transformation for communication service providers(CSPs) can be tedious to achieve if not supported through efficient transformation tools. Compared to the existing provisioning and management of services (service lifecycle), the digital environment requires a real-time engagement with the customer and a real-time management of offered services. This necessitates a virtualized network build-up and an on-demand service environment. And instead of offering services for consumers, the CSPs will focus on offering a high-quality network as a service (NaaS) to verticals and spinning up innovative digital services, with analytics to indicate the service usage trends.

At the network level, to achieve such high speed and automation of service lifecycle management, the CSP must manage the performance of the network, analyze problems and remediate them in real-time. But this is not enough. The CSP must also optimize opex through automated closed loop orchestration of the network and generate analytics to optimize capex. In addition, there is a growing need for end customers (enterprises/ verticals) to visualize network and service data on SLA portals with dashboards that update in real-time and produce custom correlations between different datasets to track the service performance.

Traditionally, the underlying platform that feeds the Operation Center and the SLA Portal is the Service Assurance platform. However, existing Service Assurance platforms need to step up and offer real-time analytics and support automation of the service lifecycle to feed the Operation Center and SLA Portals in an on-demand service environment. This requires a transformation of the Service Assurance platform, over several steps.

Here are some recommended steps for the CSPs to bring in the transformation quickly:

1. Scale up the platform


With networks ramping up to support new services (vCPE, VxLTE, IoT etc), the Service Assurance system must scale up and react in proportion. Scaling up requires higher rates of data acquisition (E.g., 1 second data granularity) and database performance (E.g., query response time of a few ms for 1 billion records, and over 1 million data insertions/second, etc.). Storage also needs to increase to support petabytes of data.

2. Process virtualized network performance



As multi-vendor VNFs grow in the CSP network, the performance and usage data need to be quickly processed and acted upon. (e.g., VNF spin-up/down time, VNF availability and VNF resource utilization.) This also includes data from the NFV infrastructure.

3. Make it real-time

Reporting delays of hours or minutes need to be brought down to seconds, so that network orchestration can be carried out in real-time.  Streaming data via network elements that support Telemetry is one of the quickest ways to achieve this.

4. Build resilience



Services for enterprises and network-slices demand high reliability and zero-tolerance for failure, so the platform managing the services should be robust and resilient. High integrity can be built through use of resilient dataflow management systems, and cloud-native data mediation buses.

5. Contextualize analytics



The platform must act as an analytics engine which pushes out real-time contextualized insights for new services for the verticals. Pattern detection, trend analysis and forecasting problems by location and per SLA can bring significant revenue benefits.

6. Automate essential operational actions



An automated service lifecycle requires several automated functions, the Service Assurance platform being a key element. A Service Assurance system can automate data collection, policy-based events, and closed-loop optimization as the key contributors to the automation of the service lifecycle.

With the use of automated functions and analytical insights, during the VNF onboarding to the operation of the hybrid network and SLA management, the Service Assurance platform can become a strategic revenue tool for the CSPs. CSPs that transform their Service Assurance solutions will now empower their operations and engineering teams in time for the on-demand service environment.


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