Kubernetes started in 2014. For the next two years, the adoption of Kubernetes as a container orchestration engine was slow but steady, as compared to its counterparts – Amazon ECS, Apache Mesos, Docker Swarm, GCE, etc. After 2016, Kubernetes started creeping into many IT systems that have a wide variety of container workloads and demand higher performance for scheduling, scaling and automation. This is to enable a cloud-native approach having a microservices architecture in application deployments. Leading tech giants (AWS, Alibaba, Microsoft Azure, Red Hat) have started new solutions based on Kubernetes and in 2018, they are consolidating to build a de facto Kubernetes solution which can cover every use case that handles dynamic hyperscale workloads.
Two very recent acquisitions depict how Kubernetes has created a huge impact in the IT ecosystem. One is IBM’s Red Hat and VMware’s Heptio acquisition. IBM did not show the direct interest to target container orchestrations but had eyes on Red Hat’s Kubernetes Based Openshift.
Software Defined Networks (SDN) and Network Function Virtualization (NFV) enable cloud service providers (CSPs) to build more agile and flexible communication infrastructures.
According to Gartner’s research director Martina Kurth, this technological innovation gives CSPs the power to create and deliver cloud-based services for enterprises or organizations in the way they need them. Hence, CSPs should be better empowered to challenge service models adopted by top cloud service providers like Amazon and Microsoft.
So far, SDN/NFV has been deployed for trial use or in few fields on a limited scale. Today, the fierce competition forces CSPs to put SDN/NFV into operation as soon as possible to generate revenue.
Kurth said, “At first, we’ve been focusing on the technical challenges of SDN and NFV. Now, the paramount concerns are shifted to commercial application and opportunities of generating new revenues.”
To implement the commercial application, CSPs raise the following questions to determine the direction better:
The following figure shows the impact of key technologies on the expected time for benefits. Services like the virtual Customer Premise Equipment (CPE) have great potential in generating revenues and can get quickly deployed. Regarding the SDN/NFV’s rate of return on investment, it is easy for those services that help improve service agility, operation efficiency, and service modeling capabilities to show effects, for example, on-demand virtual security and unified communication services. Other IoT services also have great potential in generating revenues in the long run, except that it takes a longer time to gain benefits.
Impact levels of SDN/NFV and time required to gain benefits
It is critical to integrate the required technical inputs with the expected business outcomes, and thus it needs multifaceted strategic planning:
In this article, we discussed the commercialized deployment of SDN/NFV by CSPs and how it can add value to their business. At present, not many fields have explored SDN/NFV, and that, too, to a very limited extent. However, due to intense competition, it has become a necessity for the CSPs to adopt this technology as soon as possible. We also talked about the strategic planning and actions that are required to go ahead with the process successfully and achieve maximum ROI.
VNFs, or virtual network functions, are the software implementation of network function equipment packaged in a virtual machine, on top of COTS hardware NFV infrastructure. VNFs are core part of NFV, or network functions virtualization, as we know the basis of NFV was to virtualize 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 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 is 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 environment. On-boarding VNFs remains a challenge due to lack of standard processes for complete management from development to deployment and monitoring.
At a basic level, traditional VNFs comes with limitations:
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 containerized functions, microservices based, dynamically managed and specifically designed for orchestration. The major differentiator of cloud-native VNFs from traditional VNFs could be self-management capability and scalability.
Building cloud-native VNFs overcomes the previously discussed limitations of traditional VNFs and provides the below benefits:
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, VNF onboarding, etc. Developing VNF and deploying into NFV infrastructure sounds simple but it raises various questions when it comes to scale, configure or update VNFs. Any task related to VNFs needs manual intervention, leads to more time consumption for launching or updating new services for service providers. To deliver promise of agility by NFV in 5G need exceptional automation at every level of NFV development. Building cloud-native VNFs seems to be the solution but it is at very early stage.