The new era of smart cities, connected factories, self-driven cars, and drone-based deliveries put relentless pressure on communications service providers (CSPs) to deliver seamless and reliable network connectivity.
It has compelled CSPs to reposition themselves as digital service providers (DSPs). A significant step in this transformation requires the effective management of hybrid networks, comprising both physical and virtual networks. Automating operations and taking a machine-first approach is crucial to detecting and resolving large-scale operational issues in such a complex network. It means seamlessly migrating to telco cloud networks, embracing technologies such as network function virtualization (NFV) and software-defined networking (SDN), and deploying big data-based analytics and IoT systems – a process that spans multiple phases.
We outline an evolutionary approach that enables CSPs to transform their reactive legacy physical network operations to support the requirements of real-time automated actions and cognitive orchestration, leading to zero-touch operations.
With telecommunications networks evolving rapidly, emerging architectures such as SDN and NFV seek to abstract network functions from their hardware. As a result, CSPs face the burden of managing both their legacy networks and virtual networks, increasing the complexity, security, and reskilling challenges.
In addition to technological advancements, CSPs confront a slew of challenges. There will be 3.5 billion 5G subscriptions by 2026, and virtualization is key to meeting 5G connectivity requirements. At the same time, consolidating data from various systems, tools, and products for an end-to-end analysis and view of the network and its operations is a must. Employing machines to supplement network teams, operation support system (OSS) tools, and day-to-day processes is crucial to accelerating service delivery, proactively resolving operational issues, and optimizing costs. In addition, flourishing IoT and cloud services require on-demand real-time service provisioning via automatic spawning of network circuits with the ability to terminate services when no longer needed. Today’s tech-savvy and highly aware consumers demand transparency and instantaneous responses as if that weren't enough. To attain zero-touch operations, the answer to these multi-pronged challenges is to take a holistic approach to manage today’s hybrid and legacy networks over time.
It is vital to seamless provisioning and de-provisioning through mechanized network orchestrators and monitoring of physical and virtual networks. ZTO helps CSPs monitor intrusion prevention systems (IPS), enable security tool deployments for robust operations, and automatically raise alerts for incidents and assign them to respective systems.
One of the critical benefits of ZTO is the ability to handle all communications management intuitively, maintain a record of all network events to co-relate and predict any downtime, and optimize performance, quality, and reporting for the entire network. Furthermore, ZTO enables auto software and firmware installation and troubleshooting of network elements while allowing intelligent patch management and scheduled and on-demand backup and storage for contingency.
It requires the end-to-end virtualization of multiple networks spanning legacy and next-generation technologies. Before embarking on the evolutionary journey, organizations must first clearly segregate their networks and identify the maturity of the entities within the networks to establish their starting point.
CSPs can map the degree of virtualization with the degree of automation to identify their state of network maturity. The level of virtualization in the network is the focus as this is one of the core parameters to enable the delivery of on-demand digital services in real-time.
Other parameters such as orchestration and AI/ML can also impact automation. Still, we acknowledge that virtualization is the foundational parameter to understanding the level of automation a CSP can achieve.
Stage 1 – Traditional: These networks are extensively physical, with no near-term plan to virtualize them. CSPs with traditional networks can begin by automating manual processes such as fulfillment and assurance through toolsets such as command-line interface (CLI) automation and robotic process automation (RPA) scripting to move to the next stage. This automation will bring down these networks' operation costs and make them financially viable for delivering services. Most government-owned CSPs who manage and provide traditional voice services wear this label comfortably.
Stage 2 – Reactive: Reactive networks combine extensive physical networks with a high degree of automated processes across fulfillment and assurance.
They use this approach to maximize the benefit of network investments made years earlier. This type of network lacks the elasticity and versatility to scale operations up or down based on the demand. In addition, these networks cannot run through orchestrators for delivering multiple layered services. As a next step in the evolutionary process, CSPs must proactively identify the parts to virtualize their network to take network operations to the next level. Such networks can generate AI and machine learning-based insights, triggering automated actions based on these insights.
A few multinational telecom companies have been trying to navigate stage two of the ZTO steeplechase.
Stage 3 – Progressive: Virtualization has been implemented in a significant portion of this network, even though these networks lack a good orchestrator or fail to function effectively due to dependency on specific physical networks. In such a scenario, where virtualization is available for the access network, and the backhaul network is still physical, end-to-end service deployment may not be completely automated and orchestrated, limiting the impact of virtualization.
For CSPs with progressive networks, transitioning to completely virtual networks and deploying automation and orchestration is the next step in the evolutionary process. These networks will eventually have to be automated end-to-end to realize the agility and automation benefits fully. Part of the network employs machine learning and analytics, which will not deliver the total value of any such system. Many telecom behemoths need to take either a 'giant leap' or 'one small step' depending upon their place on the change curve.
Stage 4 – Reformist: These networks are the most evolved-a high level of virtualization and automation defines their character. Most standards and products are working for this category of CSPs. They have a considerable advantage given the new open technologies available to integrate with Open APIs, orchestrators ecosystems like ONAP, OPNFV, and so on. The powerful combination of virtualization and automation helps CSPs seamlessly orchestrate services and scale up or down as needed, based on demand. This type of network is the most amenable to the implementation of ZTO as it’s easy to collect and analyze data in this type of network, generating insights for proactive network management. This category of CSPs must invest hugely in new technologies to figure out how customer and service layers will merge with the network. These CSPs have intelligent operations driven by prescriptive analytics and machine intelligence algorithms. Network components are created and shut down dynamically based on the need. It's no surprise then that the numero unos in telecom have already turned reformists.
However, only 15-20% of CSPs fall in that category. The approach includes all the types of CSPs regardless of whether they have complete physical networks or partial virtual networks. CSPs should evaluate their networks based on these categories and draw a clear strategy for ZTO. However, the reality is that many CSPs are still dependent on legacy physical networks, making the transition to ZTO challenging. With 5G poised to disrupt the telecommunications industry, evolving to ZTO quickly but in a phased manner will be vital to surviving and thriving. It will mean identifying the next steps based on the current network maturity and iterating through the subsequent stages until the network attains the reformist stage.
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