The future (and arguably the present) of networking belongs to the Cloud. Legacy WAN networks deployed on aging MPLS systems can no longer handle the sheer amount of data, processing power, and security needed to keep businesses competitive. The resources required to maintain legacy networks are becoming increasingly untenable. More and more, we find on-prem data centers reaching the end of their lifespan, requiring migrations to a cloud-based network. Software-defined wide area network (SD-WAN) is a robust methodology that shifts the burden of data flow from hard-line MPLS networks to the cloud.
SD-WAN deployment benefits include increased network speed, less downtime, and increased efficiency across the board. Additionally, it expands data real estate. Companies need real-time access to their applications, mobile data, at-home devices, and data from IoT devices. As a result, the number of points of presence (PoP) for many companies, especially those in the healthcare field, has grown exponentially. Because of this, the number of potential vulnerabilities for cyberattacks has grown to match. As such, the future of SD-WAN will hinge on current and cutting-edge security tools such as SASE, ENI, and specific deployments of machine learning (ML) and AI.
In a nutshell, SD-WAN architecture shifts the control of a wide area network for a company and its branches from an onsite data center and hardware to cloud-based software. This software controls connectivity, data management, and the flow of information from headquarters to company branches and remote workers. SD-WAN connection endpoints—branches, data centers, cloud platforms, or corporate offices—are referred to as the SD-WAN edge. As we’ll discuss in more detail later in the post, securing the edge network is a core issue vital to the future of SD-WAN.
According to a study conducted by Gartner with CBTS, the drivers of SD-WAN adoption are the need to:
Optimize performance for end users and administrators.
Also read: Key SD-WAN advantages your hybrid work-from-home model needs
Cyberattacks continue to grow in volume and complexity. In 2021, an attack with an instance of 17 million requests was recorded from a botnet three times larger than any previously registered attack. The rate and escalation of cyberattacks are not slowing down. A second attack later that year—an attack of 22 million requests per second—dwarfed the first attack. Experts predict that another attack will take place soon that surpasses 30 million requests per second. Fortunately, cybersecurity measures continue to evolve as preventing cybercrime becomes a focus for enterprises and government agencies.
Secure Access Service Edge (SASE, pronounced “sassy”) is an architecture that utilizes SD-WAN via an encompassing cloud-native framework. First defined in 2019 by Gartner, SASE is a philosophical approach to cloud security instead of a set of tools or a specific technology. The SASE model merges networking and security to reduce hardware, simplify operations, and minimize security risks.
SASE engages with five core technologies:
SASE is a borderless approach to networking, meaning it can support globally distributed teams and customers. Global environments allow employers to embrace a modern, work-from-anywhere mentality. Migrating to SASE PoPs optimizes where data lands in the network by combining software apps and data storage. Additionally, the integration of FWaaS refines and maximizes security measures for data centers. SASE reduces latency and results in a higher performing network by adding PoPs globally, so data doesn’t have to travel as far. These gateways provide the functionality, reliability, and access that teams and customers need.
Edge network intelligence (ENI) allows enterprises visibility of their end-user and IoT devices. ENI creates a complete view of the entire data plane for each user (wired and wireless). This allows IT teams to home in on issues such as latency via automatically generated issue tickets. ENI also proactively engages in self-healing for the network after problems have been identified. Another feature of ENI is integration with AI-empowered Network as a Service (NaaS) such as Cisco Meraki or Juniper Mist.
Learn more: Thinking big on future of networking
ENI uses machine learning algorithms to detect, monitor, and interact with end-user devices across a client’s data estate. SASE providers also deploy AI to scan for threats and block attacks proactively.
But in terms of potential, AI and ML are just beginning to scratch the surface. AI/ML will be integral to the future of SD-WAN.
Beyond security advancements offered by SASE, ENI, and other AI solutions, other innovations will continue to trend as SD-WAN moves into the future. Those innovations revolve around:
Given the movement of most industries, it also seems highly likely that future iterations of SD-WAN technology will work well with multi-cloud platforms and help to streamline those environments.
Legacy MPLS architecture is nearing the end of its lifespan in many cases. Compounded with the surge of data streams from mobile, at-home, and IoT devices, networks are primed to falter in the immediate future without SD-WAN solutions. Replacing traditional networks in favor of SD-WAN will allow for greater agility, simplicity, and performance on every level of business operations.
CBTS is at the forefront of SD-WAN conversion for our clients. The flexibility of SD-WAN means that delivery is potentially borderless, with service in over 60 countries. Often, we can utilize existing MPLS networks to deploy SD-WAN quickly and efficiently. Our suite of managed services—including networking—are best-in-class and a valuable way to offload burden from IT teams.
Get in touch to learn more about future-proofing your business with our managed SD-WAN, networking, or security services.