In previous blogs, we’ve discussed the myriad of simultaneously occuring changes in telco infrastructure; virtualisation, NFV and SDN, legacy, hybrid, and next generation networks running in parallell, service convergence (for instance, fixed, VOLTE, and VoIP), and so on. And that’s without mentioning what’s coming up next (or already here); the proliferation of IoT-based business models, 5G, digitization, and more. With so many pieces on the table, putting the jigsaw puzzle together in terms of operational efficiency is a challenge. How do you make sure everything runs smoothly?
The challenge is particularly apparent in the context of OSS. Gone are the days of single NEP supplier relationships, limited service offerings and manageable customer volumes. Instead, multi-vendor infrastructures, myriad (and often vendor-dependent) OSS systems and an increased focus on service quality are now the order of the day.
Set against these realities is an emerging set of newly important needs, including:
- Access to holistic views of customer experience, service quality and assurance, and performance management.
- The ability to accommodate new data sources which may be dynamic and elastic and include VM and NFVi statistics.
- Developing an OSS that can handle hybrid environments, scale dynamically and be flexible enough to quickly support new Use Cases.
- The need for maintainability, without vendor dependencies and agile enough to ensure fast times-to-market for new services.
In pursuit of the above, how should OSS evolve and how should future OSS be managed? Deploying OSS Mediation, which in many ways puts the CSP in prime position to leverage change, would be a good start. OSS Mediation means enabling:
- Fast Time To Market in real-time or batch modes, with flexible business logic creation via a Graphical User Interface that supports configuration rather than time-consuming programming for changes.
- Extreme Performance through a hardware agnostic, scalable architecture.
- Future Proofing with programmatic handling of any new sources in real-time with a RESTful API and pre-configured workflows that can be dynamically activated.
- Access to smart (not just big) data at the right time via KPI’s that can be defined in runtime programmatically with control of hierarchies, KPI calculations, aggregation times and thresholds and scalable through Spark/Kafka architecture.
Other Blogs in this series: