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Legacy networks are getting in the way of organisations trying to adopt the latest digital technologies. For successful transformation, along with other infrastructure, enterprises should also modernise their networks, through solutions such as Software Defined Networking.
Software Defined Networking (SDN) refers to an architecture that makes a network more flexible, programmable, efficient, and easier to manageSDN abstracts the control plane (where networking processes directing traffic occur) from the data plane (which forwards data packets), enabling centralised management and configuration of network resources through software.
The global SDN market is expanding rapidly – projected to grow from $10 billion in 2019 to $72.6 billion by 2027 – as enterprises around the world embrace its myriad advantages.
By allowing networks to be managed centrally, using a single controller, SDN simplifies network operations, enabling flexible, dynamic allocation of resources and efficient traffic routing. Enterprises can reduce capital expenditure by using commodity hardware and save operating costs by automating several networking tasks, such as discovery and configuration of fabrics and switches. In fact, SDN enables organisations to create a foundation for network automation across the lifecycle, and domains, including cloud and Wide Area Network.
By optimising traffic and improving load balancing, SDN reduces network congestion and enhances performance – for example, it allows the network to be reconfigured quickly in case of failure or surge in traffic, thereby limiting downtime. Network infrastructure can be scaled with speed, and without disruption. What’s more, offering capabilities, such as policy-based segmentation and isolation, as well as micro-segmentation and compliance automation, SDN allows organisations to implement zero-trust access and improve network security.
SDN creates network programmability through APIs, so that developers can innovate and customise applications that communicate with the network infrastructure. Built-in analytics and monitoring tools offer real-time visibility into network performance, to facilitate maintenance and troubleshooting.
A major advantage of SDN is seamless integration and management across public, private, and hybrid cloud, enabling consistent performance across a multi-cloud environment. As enterprises gravitate towards hybrid / multi-cloud to improve resilience, flexibility, choice, and cost efficiency, they may find it challenging to interconnect and efficiently manage their various on-premise and cloud infrastructures located around the world. This is because creating direct connections to different clouds and data centers is very expensive in traditional networking; add to that the enormity of migrating and then managing rapidly growing data and applications in a hybrid or multi-cloud environment, necessitating technical expertise and significant resources.
SDN is the ideal solution – it supports flexible deployment of IT infrastructure, accelerates cloud adoption and simplifies management of cloud connectivity, and reduces network costs. Enterprises can dynamically scale cloud resources and add (cloud) environments, interconnect their data centers, and control it all from a central location.
Now, the incorporation of technologies, such as Artificial Intelligence and Machine Learning, is taking SDN capabilities to another level, allowing enterprises to adapt quickly to changing conditions to maintain operations and service quality. Machine learning algorithms analyse past network data to detect patterns that help to anticipate and proactively address network failure, cyberattack, or other performance issues. ML models also ensure high quality of service by dynamically allocating network resources as required, which is especially important in networks carrying both real-time and non real-time traffic.
Generative AI is creating synthetic data to train and improve AI algorithms used in networking applications; simulating network environments for testing resilience in the face of cyberattack and other stressors; and optimising network design by generating multiple options based on criteria, such as cost and throughput.
Natural Language Processing allows network professionals to resolve queries or get their tasks done by simply conversing with AI-enabled systems. It also automates troubleshooting documentation by creating a record or log of administrators’ voice or text commands while troubleshooting, and even analyses email, logs and other data sources to identify suspicious activities (like phishing) or security breaches.
Further, as SDN evolves in capability, it is making it easier for organisations to deploy edge computing resources, and for telecom operators to dynamically and efficiently manage their 5G networks. In other words, it is the networking foundation on which enterprises will build their future businesses.
Authored by Saju Sankarankutty, Senior Vice President and Unit Technology Officer, Cloud and Infrastructure Services, Infosys
[Disclaimer: The views expressed are solely of the author and Analytics Insight does not necessarily subscribe to it. Analytics Insight shall not be responsible for any damage caused to any damage caused to any person/organization directly or indirectly.]
