Telcos need an agile, low code platform that supports events and streaming data to develop next-generation real-time 5G and edge applications.
Envisioned telecom applications based on the availability of 5G and edge services are limitless. To power these applications, telecommunications companies are looking to use artificial intelligence and machine learning (AI/ML) for a variety of applications and in multiple business areas.
Internally, they seek to improve operational efficiencies. Efforts will focus on predictive asset management. Here, AI/ML will be used to move from scheduled maintenance and reacting to problems (outages, offline equipment, etc.) to pro-active operations. A simple example is spotting the warning signs of a transformer whose performance is rapidly degrading and fixing it before there is an unplanned outage. A more complex example is the real-time and optimized deployment of resources to address the impact of a major storm. A new approach might include the instant analysis of video streams (some from drones) to instantly assess the situation down to very fine granular coverage. That information would be combined with outage data from customer apps and other sources. The analysis of that aggregate data would then be the basis for a plan of action.
Telecom companies also hope to use AI/ML-derived insights to:
- Increase revenues. They must provide granular services and high quality of service. Additionally, they need to create and deliver new offerings in shorter and shorter life cycles.
- Deliver on digital transformation. They must develop new business models and monetization models. This requires working with partner ecosystems and integrating their (the telecom’s) offerings, applications, and services with the offerings of these third parties.
- Meet evolving and more stringent regulatory requirements. The increased complexity of telecom environments combined with a boom in global data privacy and protection regulations requires the adoption of analytics, automation, and AI to address compliance.
- Embrace the connected world. The combination of 5G, IoT, and edge open up a wealth of opportunities to deliver innovative services and applications. Most will rely on telecom companies working with partners to deliver these offerings.
Real-time application development challenges
One common factor that cuts across any telecom use case, application, or deployment is that there is no such thing as an end-to-end solution. This means telcos will need to provide an open platform for developing, provisioning, managing, and monitoring 5G and edge services so that third parties and partners (device vendors, service providers, analytics firms, etc.) can develop secure, innovative solutions.
In many cases, telcos will be dealing with multiple data sources, as well as events and streaming data, and as such will require solutions that include event-driven architectures (EDAs), real-time analytics, and the use of AI and ML.
EDAs offer several distinct features or benefits for the types of data and analysis telecom applications require. In particular, EDA supports:
Real-time streaming analytics: EDA is useful when there is a need for real-time processing with a minimum time lag. Events occur in a continuous stream as things happen in the real world. Streaming analytics is all about extracting business value from data in motion in the same way traditional analytics tools make use of data at rest.
Asynchronous operations: Asynchronous systems use data that is generated and transmitted intermittently. An example would be a 5G-connected sensor that sends an alert when a measured quantity exceeds a pre-set threshold value. Most of the time, there would be no data, but when the threshold is exceeded, the sensor will convey this information in real time to monitoring systems. The priority then is to act instantly on the event, rather than storing data and checking status later. To ensure any number of events can be acted upon in real time requires asynchronous operations. EDAs are distributed asynchronous architectures that can be used to support highly scalable applications.
Loosely coupled systems: Many telecom applications will be comprised of multiple components from different sources working together. Combining information from these separate yet loosely coupled applications delivers synergistic benefits. Building the individual apps on an EDA would allow the real-time events data from multiple apps to be used together.
The need for an agile development platform
From a development standpoint, the benefits of using an EDA can be made more easily and widely available if used in conjunction with an agile development platform.
Why? Embracing EDA is foundational to the next generation of digital applications. Telecoms will need to be able to design, develop, deploy, and operate event-driven solutions in cloud-native styles to have the required agility and speed to innovation required to stay competitive today.
While event-driven architectures have been employed in the past, the move to cloud-native architectures with microservices, container-based workloads, and serverless computing is making them more practical and provides many benefits. For example, cloud-native solutions are known to be reactive and responsive. An event-driven architecture leverages these traits and enhances them offering resiliency, agility, and scalability.
Required characteristics of a telecom real-time solution
There is also a great need to develop new real-time applications faster and not reinvent everything from scratch when developing new telecom applications. A suitable agile development platform that can handle the demands of at scale real-time applications will have specific characteristics, including:
- Low-code development environment and support for composable elements for the rapid development of event-driven applications
- Infrastructure agnostic
- Capacity to accommodate large volumes of streaming events data
- Ability to accommodate the use of different types of analysis (including real-time streaming analytics) to satisfy different objectives
- Support loosely coupled systems and asynchronous operations
- Offer a level of openness for easy integration of disparate systems, applications, and data
- Be enterprise-ready to support scalable, mission-critical applications.
With such a platform, telcos will be able to rapidly develop innovative real-time 5G and edge applications and services that their customers are demanding.