Getting ready for tomorrow: how network automation is transforming high-capacity transport networks

The demand for capacity on telecommunications networks increasing rapidly, and the complexity required to deliver this capacity is increasing too. This is where network automation and intelligence comes in - with innovations such as real-time network topology and planning, advanced network restoration and proactive health management helping to achieve the dual aim of cutting complexity (and its associated costs) and improving service quality.

With this in mind, Layer123 asked for the thoughts of someone at the forefront of transport transformation - Christian Uremovic, Director of Marketing for SDN and Automation at Infinera, a company achieving big strides in 800G, 600G and 400G performance for its operator partners. Ahead of his appearance at the Layer123 World Congress, Christian discusses the challenges operators face, the applications helping them overcome these challenges, and what the future has in store.

 

Christian, how are operators looking to automate their optical networks? What is the current view on the shift from NMS/EMS to SDN?

Network operators typically have two or more optical vendors in their networks but still operate in silos when it comes to optical network management. SDN is helping to abstract optical network domains and unify the control and management of these networks. This is what is happening now. In parallel, new optical systems are being introduced into networks. These new systems have evolved with common data models (YANG) and open APIs, as well as streaming telemetry capabilities. This is a significant and important step to radically simplify the control and management of optical networks. These two elements – SDN control for legacy equipment and common data models and open APIs for new systems – are finally enabling comprehensive network automation in optical networking environments.

Typically, the first step of automation is to discover and visualize the network from end to end in a unified way and to employ a single database. From there, service automation follows, with elements such as path computation, workflow engines, real-time planning, and others. The next step is to enable dynamic optimization, such as closed-loop automation, self-optimizing networks, and proactive management with machine learning, for example.

 

What are the key implementation challenges that network operators face today?

We can summarize the key challenges as follows: fragmented management domains, poor network visibility, lack of interoperability, and no standard data models. A challenge that is often overlooked is the process of integrating and enabling new technologies into networks faster so that operators can accelerate their ROI and radically simplify operational effort. The speed of change has increased significantly in optical transport networks, and with the transition to cloud-native management and micro services, operators are looking to adapt transport networks toward IT-like operations. Established third-party IT tools, such as time series database, and new analytics tools are finding use cases in optical transport networks and enabling operators to significantly improve visibility and control while addressing some of the key challenges mentioned.

 

What benefits does automation bring?

For operators, the benefits are clear and compelling:

- Improved end-to-end control (multi-vendor and multi-layer)

- Increased speed and velocity of operation and network planning

- Improved accuracy

- Significant efficiency improvements

- Reduced OpEx

- More effective utilization of deployed network resources (reduced CapEx)

 

What are the key applications driving adoption of network automation and intelligence?

I think it’s fair to say that comprehensive and unified multi-layer, multi-vendor network discovery and visualization is a huge and important step toward automation. Having this properly in place, follow-on automation applications, such as workflow engines, path computation, service restoration, real-time planning, closed-loop dynamic optimization, self-healing networks, and AI/ML, then enable operators to bring their networks to a whole new level of control, management, and orchestration. We want and need to get ready for tomorrow.

 

What’s in store as we move forward?

Looking forward, zero-touch networks and machine learning for proactive network operation will further improve network control, operation, and management. Optical transport networks with flexible, adaptable, and programmable intelligent systems with standard open APIs, YANG data models, and streaming telemetry will then provide the foundation for IT-like operation. Further, by empowering new optical networking systems and engines with these modern APIs controlled and managed through microservices, operators will be able to leverage a new level of automation and to accelerate the introduction, implementation, and harmonization of innovative new technologies that can offer radical cost savings and transformative value in the form of service differentiation.

 

Christian will deliver a session at the Layer123 World Congress 2020 on “Speed, Accuracy and End-to-End Control – the case for software driven networks” (Thursday 15 October at 09:35 am). To register to hear him go into more detail about the benefits of software for transport networks, register here.