Those benefits remain very real, but the more compelling value of NFV lies in its ability to increase network elasticity, agility and automation. NFV creates a flexible foundation for advanced technologies, and AI-powered solutions help optimize performance and reliability.

NFV Architecture

At its core, NFV is very similar to server virtualization — a hypervisor separates operating systems and applications from hardware so that one server can run multiple virtual workloads that share the physical resources. Virtualized servers also have an automation and orchestration layer that makes it possible to spin up new virtual machines (VMs) automatically and balance workloads across them.

NFV provides these same capabilities. The Management and Organization (MANO) layer of NFV platforms includes the NFV Orchestrator, which manages the overall environment, and the Virtual Infrastructure Manager (VIM), which manages the server resources that support virtualized network functions (VNFs). The VNF manager handles the creation, modification and destruction of VNF instances.

NFV Benefits

These tools enable the creation of an elastic network that can grow and shrink as needed to support increased network traffic. The NFV platform can automatically spin up new VNF instances and then deprovision them as demand abates. Network functions can be easily configured and reconfigured through software updates, enabling dynamic adjustments to network topology and service offerings. 

New network services can be rapidly deployed by simply provisioning VNFs on the existing infrastructure without requiring physical hardware installation. VNFs can be configured 96 percent faster than traditional solutions, and automation can eliminate the manual configurations that cause 42 percent of network downtime. Enterprise-class solutions provide a graphical user interface that makes it easy to provision network services based on predefined templates.

AI-driven NFV solutions further optimize network management and enable predictive maintenance and real-time analytics to improve service quality. Studies show that machine learning can significantly improve network stability by accurately predicting traffic levels 93.7 percent of the time.

NFV Use Cases

The telecom industry is the primary adopter of NFV, and its usage has increased with the advent of 5G. NFV provides the scalability and flexibility telecom companies need for 5G rollouts while also reducing infrastructure costs.

However, large enterprises are also taking advantage of NFV to create networks that can dynamically adapt to changing requirements. Some of the top use cases include:

  • Internet of Things (IoT). NFV provides the flexibility needed to ensure the smooth functioning of IoT ecosystems. It can also reduce hardware complexity, simplify network management and enable efficient resource allocation as the number of IoT devices grows.
  • Edge Computing. Increasingly, organizations are moving applications and data to the network edge, closer to data sources. NFV helps improve performance and resilience, reduce latency and enable dynamic scalability at the edge.
  • Disaster Recovery. By moving network functions from hardware to software, organizations can create a more resilient network that can remain stable despite disruptions. They can also spin up VNFs in geographically diverse locations to maintain service continuity during outages.
  • Application Development and Testing. NFV makes it possible to create isolated virtual environments to test new applications and network configurations. Testing in a controlled setting minimizes any impact on live production networks. 

How Technologent Can Help 

Polaris Market Research projects that the NFV market will see a compound annual growth rate of 26.7 percent through 2034. If you’re considering NFV, Technologent’s network infrastructure experts can help you evaluate various solutions and plan the implementation. Let us help you take advantage of the elasticity, agility and automation benefits of NFV.