The Autonomous Future of Today’s CSP
The Autonomous Future of Today’s CSP
Secure networks have permeated every aspect of our lives. They support remote teams, mobility, our children's education, how we shop, and how we connect with our loved ones. They are also the fabric upon which our businesses operate.
As critical as these networks are, it's unsurprising that they're not just growing; they're exploding. 5G, IoT, IIoT, and trends such as software-as-a-service, cloudification, and smart everything all contribute to this growth. Consider the following figures:
By 2025, IDC predicts that there will be close to 56 billion connected devices worldwide, with 75% of these connected to an IoT platform.
According to Juniper Research, the number of IIoT connections will increase by 107 percent, from 17.7 billion in 2020 to 36.8 billion in 2025.
According to Statista, the global market for Smart Homes is expected to reach 482.8 million units in 2025.
The connected economy presupposes hyperscale secure networking (i.e., SASE). This necessitates service-level automation, as point solutions and tools alone cannot scale services.
While this growth is exciting for Communications Service Providers (CSPs), it does raise some serious concerns.
The major ones that come to mind are how we will manage all of these endpoints and the network that connects them. How will we safeguard them? How are we going to make them trustworthy enough that we can literally stake our businesses and lives on them, and how are we going to do so cost effectively at hyper scale?
Context to help explain these concerns
It currently takes between five and nine man-hours to deploy a simple secure SD-WAN endpoint. This figure encompasses all of the benefits of modern network automation, as well as the cost of swivel-chair, cross-domain manual convergence of endpoint, transport, and security domains and policies.
Now, let us look at what it does not include. To begin, it excludes ongoing service assurance, automated remediation, security updates, maintenance, restoration, and upgrade operations, as well as optimization operations. Additionally, it excludes service enablement.
In today's SaaS and cloud-based world, where businesses seek to leverage digital transformation, increased speed, and performance, and where new services are introduced on a regular basis, we become increasingly vulnerable to provider network reliability and security vulnerabilities if we continue to rely on manual processes.
The bottom line is that a smart city cannot be built on top of a dumb pipe that delivers manually mediated end-user value-added services.
For CSPs, one option is to transition to autonomous service operations. Autonomous Service Operations address the shortage of trained personnel required to meet scale requirements, the inefficiency and expense of manual processes, and the cost and frequency of human errors.
The critical characteristic of Autonomous Service Operations is its autonomy. However, a close second is the fact that it manages the entire service, end-to-end, rather than just some of the components.
Consider secure networks as an illustration of why this is so critical. Endpoints, underlay elements (the provider's physical network), overlay elements (the provider's virtual network components), and frequently cloud-based elements comprise secure networks. Additionally, they have security applications and controllers, SD-WAN applications and controllers, and orchestrators deployed across the network's various levels and technology domains.
Each domain (network, security, application, and cloud) now has its own set of automation/orchestration tools, which are manually converged and mediated. The good news is that domains have a high degree of automation.
The bad news is that knowledge about the customer, the end-to-end service, and the service level agreements (SLAs) for the services are all held by humans, and only temporarily, while they manually perform cross-domain alignment and orchestration to create the service end-to-end or wade through alarms and tickets to diagnose a failure.
Autonomous Service Operations can address these issues AT SCALE by operating at the service level, encapsulating and retaining end-to-end context for each service instance, and then acting cross-domain to direct the individual domain orchestrators and controllers to accomplish the service's goals.
All of this can be accomplished during deployment and on a continuous basis for day two operations such as assurance, healing, and maintenance. Unlike the manual scenario discussed previously, the service context is preserved in this case.
It is irrelevant that the service's components are distributed across underlay, overlay, and cloud implementations. It also makes no distinction between whether they are provided by a third party or whether some elements are controlled by controllers, while others are orchestrated by orchestrators.
Finally, Autonomous Service Operations are essentially an expert AI system that encapsulates the expertise of human experts and then applies it at scale and at computer speeds to provide distributed management and control in order to meet customer service level agreements (SLAs).
This translates into a significant reduction in the time required to deploy a secure network service, faster ticket resolution, and acceleration of detection and repair to the point where issues become invisible to customers.
The ability to rapidly bring mass-market service products to market while maintaining new levels of profitability and performance through automation is precisely what CSPs require to maximize the potential of secure networks.
This is particularly critical in emerging markets where edge computing, 5G, and access services to hyperscale cloud providers are driving growth.
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