A Modern IT Architecture for Delivering Digital Transformation


Digital Transformation. This topic has been taking over the conversation in executive meetings for a couple of years now and seems to be an unstoppable trend, thanks to the speed at which technology is improving. As this change enables faster innovation, businesses are realizing that digital transformation gives them a massive edge on their competition, regardless of industry. It goes without saying that experiencing something so transformative requires fundamental disruption at all levels of an organization, causing customary lines of separation between functional areas of a business to become less defined. This disruption extends to the relationship between customer and user, data and applications, and also to areas impacted by security strategies, and will potentially reshape how these elements are defined. So what potential realities should business leaders be considering as we sprint towards this future and look to drive digital performance?

Modern IT architecture key for digital performance

Machine learning (ML) and artificial intelligence (AI) technologies at the security layer are going to be extremely dependable sentinels.

Delivering quality end user experience demands a modern IT architecture

Digital transformation requires a modern IT architecture that enables organizations to have the visibility to see how digital initiatives are performing, and the infrastructure to improve performance. The traditional network is hardware-dependent and runs on fragmented and sometimes inefficient technologies that can result in performance inequalities from location to location. For IT, performance management of the application and services, which are dependent upon these networks, is challenging because they don’t have a holistic view of all the activities putting demands on the network, nor the ability to readily respond to those demand signals.

Next-generation networks, which will largely be software-defined and have a management plane, provide IT with the ability to leverage the right network paths, assign appropriate priority to network traffic and ensure the health of network at all locations. These networks also incorporate an integrated, end-to-end view of the user experience from the data center to the edge, so anything that may jeopardize performance is identified and managed before the end user is impacted. Having the full visibility to see how digital services and digital transformation initiatives are performing will ensure that the digital transformation investments have a true return.

Machine learning and artificial intelligence will reshape network security

Machine learning (ML) and artificial intelligence (AI) technologies at the security layer are going to be extremely dependable sentinels. Network security processes today are largely human administered and maintained, which means vulnerabilities due to human error are a built-in hazard. An example of this is the current thinking: if you have an updated database, secure firewall, patched OpenSSL, etc., your exposure is minimized. This is a false assumption that can be fatal to the security of the network.

New and future threats will constantly be evolving and improving, and ML and AI applications will be constantly vigilant against these threats and potential vulnerabilities. ML and AI technology don’t suffer from false assumptions and will simply do the job of constantly identifying anomalies and threats, but far faster and better than a human driven security model.

Networks will become auto-resilient

Ultimately, through ML and AI we’ll see systems become inherently resilient to failures by becoming “self-healing.” Current, most legacy IT systems (infrastructures) are brittle, not organic. They are fragile systems that don’t learn—one breach point and you’re done. ML and AI can make systems far more resilient and secure as they will be able to find vulnerabilities and fix them autonomously. Today, if there’s an attack on the network, the human driven solution is to fix where that attack occurred and try to prevent the same attack. ML will say ‘oh there’s a breach point here, let me fix it—and then let me ensure that this vulnerability is handled across the network so it won’t happen again.’ ML and AI will essentially ‘vaccinate’ the network not just against an attack, but also against variations of that attack.

The future of networking is going to be very exciting. We are in a highly disruptive period with major potential to drive increased digital performance with a modern IT architecture. Advancing technology is fueling digital transformation initiatives across industries, and technology will in turn help to secure these initiatives sooner rather than later.

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