Virtual network functions (VNFs) are software implementations of network function equipment packaged in virtual machines, on top of commercial off the shelf hardware NFV infrastructure. VNFs are a core part of NFV – as we know the base of NFV was to virtualise the network functions and software based to reduce cost and gain full control over network operations with added agility and flexibility benefits. We can say that the majority of NFV operations are focused towards how VNFs can be served in NFV infrastructure to introduce new services for consumers. In future, we can expect major developments will be related to VNFs only.

VNFs and NFV are separated by the fact that VNF are provided by external vendors or open source communities to service providers who are transitioning their infrastructure to NFV. There may be several VNFs which combine to form a single service for NFV. This adds complexity to the overall NFV purpose of agility, where VNFs from different vendors need to deploy in NFV infrastructure having a different operational model.

VNFs developed by different vendors have different methodologies for complete deployment in existing NFV environments. Onboarding VNFs remains a challenge due to a lack of standard processes for complete management from development to deployment and monitoring.

At a basic level, traditional VNFs come with limitations such as:

• VNFs consume huge amounts of hardware in order to be highly available
• VNFs are developed, configured and tested to run for specified NFV hardware infrastructure
• Needs manual installation, configuration and deployment on NFVi
• API not provided for VNF to enable automated scaling, configuration to serve the sudden spike in demand for utilisation
• Not supporting multi-tenancy, VNFs cannot be easily shared in infrastructure for reuse

Building cloud-native VNFs is a solution for vendors and this is a revolution in software development to have all cloud-native characteristics to VNFs. Features we can expect as cloud-native VNFs are containerised functions, microservices-based, dynamically managed and specifically designed for orchestration. The major differentiator of cloud-native VNFs from traditional VNFs can be self-management capability and scalability.

Building cloud-native VNFs overcomes the limitations of traditional VNFs and gives the following benefits. Cloud-native VNFs have APIs which enables:

• Automated installation and configuration
• Automated scaling when dynamic requirement from network
• Self-healing or fault tolerant
• Automated monitoring and analysis of VNFs for errors, capacity management and performance
• Automated upgrading and updating VNFs for applying new releases and patches
• Standard and simplified management enables less power consumption; reduction of unnecessary allocated resources
• Reusability and sharing of processes within VNFs can be achieved. VNFs can be easily shared within an NFV environment

NFV is a key technology used in the development of 5G networks. But NFV is going through a maturation stage where NFV solution providers are resolving many challenges like automated deployment, and VNF onboarding. Developing VNF and deploying into NFV infrastructure sounds simple, but it raises various questions when it comes to scale, configuring or updating VNFs. Any task related to VNFs need manual intervention, leads to more time consumption for launching or updating new services for service providers.

To deliver the promise of agility by NFV in 5G needs exceptional automation at every level of NFV deployment. Building cloud-native VNFs seems to be the solution – but it is at a very early stage.

The post Importance of Cloud-Native VNFs for NFV Success appeared first on Sagar Nangare.