To truly monetize 5G, CSPs must look beyond cloud native and hyperscalers to identify innovative capabilities and enhance monetization opportunities
By Keren Halpern, Head of Product Marketing • May 6, 2021
There is hype these days about hyperscale and cloud-native architecture. These technologies are not specific capabilities unique to telecom. They are technology enablers, relevant to all enterprise software across industries, that perform in competitive and changing environments requiring agility and scalability to handle growing demand.
In 5G services and related monetization opportunities, the questions that all operators are considering include:
Are cloud native and hyperscale enough?
Will solutions that are cloud native and use cloud capabilities suffice when trying to handle the major challenges of 5G monetization?
Or, is there a need for new capabilities and functionalities to create specific 5G opportunities required?
The following are commonly accepted technology challenges when it comes to 5G services.
Increased traffic and need for scalability
Handling of low latency use cases with edge capabilities
Drive automation and agility across the ecosystem
At first, it may appear that cloud capabilities are the immediate answer to these challenges. However, there are additional factors that affect and can enhance the way they are treated specifically for monetization solutions in the 5G era. Examples include the following:
1. Scalability Through Value-Based Differentiated Processing
A cloud-native based software that is elastic according to need is mandatory when it comes to growing traffic. It is based on the underlying assumption that when traffic grows its processing grows in parallel since all transactions should be handled the same way.
When it comes to 5G use cases, however, these vary based on the amount of transactions, the time when they hit the systems (devices) and are processed, and the dollar value of each transaction.
Example A: IoT devices that generate hundreds of records each day for status reporting as part of a small monthly subscription fee (low ARPU) (e.g., city light sensors, health care tracker, fleet management, etc.).
Example B: augmented reality (e.g., car racing, gaming, football, etc.) subscription fees including guaranteed bandwidth and quality for a limited time on a promotional bundle price, generating a limited number of records connected to high ARPU.
The monetary value of the transactions in these two examples differ dramatically, and they also use different business functionality, such as tracking vs. real-time monetization with ensured customer experience. Therefore, should they be processed the same, with similar rules and use the overall scalability to address the transaction load generated by the use cases?
An alternative is to process the transactions differently in accordance with business/operational efficiency needs. That means that the real-time charging would identify the type of traffic and perform different levels of processing with intelligent allocation of functionality for the corresponding business to ensure the best ARPU against resource needs.
2. Edge Allows For Smart Distributed Charging And Drives Cost Savings
Cloud-native architecture allows scaling processes by activating multiple containers with dedicated functionality based on the business needs. This is the basis for allocating the right processing functionality on the edge when it comes to distributed real-time charging. While the conversation is mainly focused on low latency 5G use cases on the edge, it is worth exploring if there are additional advantages to such an architecture and what functionality will support it.
Driven by 5G and IoT, transaction quantity will grow exponentially and influence the cost of processing on the edge or centralized location, depending on the need but also on the business value. Edge allows for a new approach to handle this traffic at the source with smart, distributed transaction handling and orchestrated traffic management between the edge and central charging components.
Combining edge capabilities with new charging orchestration functionality is an opportunity to achieve three goals with one solution.
Perform real-time charging at the edge for low latency use cases along with aggregations to reduce data volume
Reduce the costs of hybrid solutions for egress/ingress scenarios
Perform processing where it is easy to allocate dynamic resources to optimize the costs
There are not many examples that include IoT use cases where offline and real-time metering is done locally based on volume and transactions. For low latency use cases, which do non-blocking and are based on variables like time, volume, or QoS, the aggregated result is feedback to centralized charging flow with all the different functions orchestrated, such as notification, tiered pricing, discounts, etc. Local policy control in a private 5G network in the industry hall managing slices for QA control during the manufacturing process and managing fallout handling by using public cloud AI/ML image screening products.
3. Optimizing Monetization And Experience Leveraging Open Architecture
Open architecture is another important guideline in the telecom industry. TM Forum is leading it with its initiatives around Open Digital Architecture (ODA) and standard APIs. This is a great starting point for compliance and requirements definitions when CSPs evaluate monetization solutions as it is the cornerstone for implementing or expanding monetization solution capabilities to enable reduced costs in integration, ensure consistent requirements across all components, and reduce dependencies on vendors.
Yet, service and monetization opportunities lie in leveraging the standardization to drive cross-system automation and closed-loop feedback across the ecosystem to optimize monetization offerings and customer experience. For example, using data analytics capabilities provided by 5G NWDAF component or DWH analytic components provide network feedback, such as quality or service fulfillment indicators, allows for real-time monitoring and optimization to address direct customer experience issues (e.g., changing the slices on the fly to ensure quality, giving discounts in real-time if services are not fulfilled or customer notifications to mitigate their expectations).
Another example takes advantage of analytics deep learning to identify user and device patterns and behavior. This allows optimization of internal processing and even pricing and fulfillment to develop new offerings or make adaptations to existing ones.
In both scenarios, automation and new monetization opportunities utilize the open architecture. Monetization systems take a central role in real E2E digital customer experience by leveraging new 5G functionalities.
CSPs that are committed to using 5G to innovate new monetization opportunities while ensuring customer experience, agility, and cost efficiency need to search beyond cloud native and hyperscalers. These are table stakes — to truly monetize 5G, CSPs must look deeper and identify innovative functional capabilities that will further enhance their monetization opportunities and equip them for the unknown.
Discover more. Read Cloud: Lessons Learned From the Front Lines.