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nfv

Evolvement of Kubernetes to Manage Diverse IT Workloads

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.

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Strategies to Commercialize SDN and NFV

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.

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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:

  1. Which new virtualization services will upend the market to the maximum extent and help us take the lead in the market?
  2. Which areas should we invest in?
  3. How is the revenue potential?
  4. How long does it take to generate new revenues?
  5. What are the new services and revenue sources that SDN/NFV can bring? How long does it take to show the benefits?

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.

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Impact levels of SDN/NFV and time required to gain benefits

How Can CSPs Commercialize Deployed SDN/NFV in a Wider Enterprise Scale?

It is critical to integrate the required technical inputs with the expected business outcomes, and thus it needs multifaceted strategic planning:

  1. Learn the go-to-market impacts of SDN/NFV from the business point of view. SDN/NFV enables CSPs to fully utilize the digital value chain and work with the third-party ecological system players to build new business patterns. However, this objective can be hardly achievable without operation strategies, revenue planning, and go-to-market planning.
  2. Expand the coverage in different regions, and then quickly and efficiently deploy SDN/NFV in a large scale. Starting from a small scale, apply accumulated experiences to broader operation scenarios, fields, and entities. Do not ignore investments in the customer-oriented digital IT, which helps the new business patterns, such as IoT or network slicing, generate revenues.
  3. Focus on several critical operation best practices and agile tools to accelerate deployment of SDN/NFV. Pay close attention to the operation of SDN/NFV, and gradually increase investments in the new SDN/NFV orchestration architectures. In addition, pay attention to the operation tools (such as prediction and analysis, service modeling, and artificial intelligence), as well as standards and templates that help standardization of SDN/NFV.
  4. Implement organizational reform and leader management at the early stage. Develop a complete set of organization and talent audit mechanisms, fully utilize your investments in SDN/NFV, and introduce a set of agile service creation and test processes similar to DevOps based on the architectures, development, and operation of the network and IT.

Conclusion

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.

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The Convergence of NFV and DevOps for Accelerated Innovation

With growing number of "connected" devices, 5G technology promises to deliver accelerated connectivity to consumers along with lucrative services. But it has to complement this with automated internal operations which will speed up the introduction of new lucrative services delivered through agile networks. NFV and DevOps are the mainstream technology for many IT- and telecom-based companies. Organizations must refine their business strategies to meet speed and automation expectations along with flexibility, short time-to-market, and cost-effectiveness.

With NFV, network infrastructure has become software-centric by virtualizing core network functions (firewall, routing, DNS). The word software comes into the picture in NFV architecture to represent code written for developing virtual network functions (VNF) and a model describing infrastructure and execution environment for hosting VNFs. With software approach in NFV, telco and enterprise IT infrastructure using NFV can reduce the cost for network equipment, reduce power consumption, build a programmable centralized network, and reduce time-to-market for new initiatives for network consumers.

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Evaluating Container Based VNF Deployment For Cloud Native NFV

The best application for NFV is how it will be integrated, architected and further matured to strengthen 5G implementation for telecom service providers. Based on current pitfalls related to VNF deployment and orchestration, making cloud-native VNF is the only solution in front of service providers today. But, telecom applications requirements of VNFs are different than any cloud-native IT application. Telecom VNF applications are built for data plane/packet processing functions along with control, signaling and media processing. An error or harm to VNF may break down the network and will impact a number of subscribers. Due to such critical processing requirement, VNFs in telecom should be resilient, offer ultra-high performance, low latency, scalability, and capacity. Telecom VNFs need to be a real-time application having latency sensitivity to fulfill network data, control, and signaling processing requirements.

Decomposition of Cloud-Native VNFs into Microservices

VNFs are network functions embedded in software which are taken out of network peripherals and hosted on virtual machines as an application, forming the term "virtual network function." Any kind of update to VNFs raises a time consuming manual effort, which hammers overall NFV infrastructure operations. To get ready for cloud-native deployment, a bundled VNF software needs to be microservices-based, wherein monolithic VNFs are decomposed into different, smaller sets of collaborative services having diverse but related functionalities. These microservices should maintain their own states, have different infrastructure resource consumption requirements, should be communicated, and automatically scaled and orchestrated using well-defined APIs.

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Why Cloud-Native VNFs Are Really Important For NFV

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:

  • VNFs consumes a huge amount of hardware to be able to highly available;
  • VNFs are developed, configured and tested to run on specified NFV hardware infrastructure;
  • Need 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 utilization;
  • 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 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:

  • Cloud-native VNFs have APIs which enable
    • Automated installation and configuration
    • automated scaling when dynamic requirement from network
    • self-healing or fault tolerance
    • 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 enable less power consumption. Reduction of un-necessary allocated resources.
  • Reusability and sharing of processes within VNFs can be achieved. VNFs can be easily shared within 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, 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.

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