Nextgen Network Management: What’s Next and Are We Ready?

Nextgen networks will demand high quality throughput, the ability to move traffic between clouds and company edges, robust security—and the right set of skills.

Nextgen network management
(Credit: wu kailiang / Alamy Stock Photo)

Network managers are being bombarded with tools and techniques for network monitoring, observability, QoS (quality of service), and AI (artificial intelligence)—but how do you build all of these capabilities into a go-forward, cohesive network management strategy without overlapping tools and investments?

In 2023, I wrote about the housekeeping aspect of organizing for network management. Much of this activity revolved around evaluating current tools and tool gaps, eliminating duplicity in tools and costs, and developing a network management tool bench that was inclusive of all of the tools needed, provided that these tools complemented each other and delivered end-to-end network coverage.

To a great extent, mapping out a network architecture and the tools that support it go far in setting companies up for what will come with nextgen network management, but that’s not all corporate networking groups need to consider as they prepare for the next generation of networks.

Here are three major trends that we can expect to take shape with nextgen networks:

Artificial Intelligence in the network

AI will play a growing role in network monitoring, observability, and troubleshooting. The AI will be especially useful in outside network surveillance in environments like 5G for public Internet, where network events can change rapidly and sometimes inexplicably, impacting service and requiring immediate resolution. AI will also be used for internal enterprise networks, as the increases in bandwidth, traffic, IoT, and edge systems will bring new forms of data into internal network transport systems that must be monitored, administered, and diagnosed quickly.

The AI network tools enterprises buy will come with all of the standard settings and criteria for AI-driven network performance monitoring, but that doesn’t mean that these default settings will match up well with what the enterprise network needs. It will be up to the IT networking group to “train” these AI models and tools by instilling them with appropriate monitoring and performance rules that conform with the needs of the enterprise. This will require education of the IT networking staff in the basic principles of AI, AI model development for networks, and how to "train" and fine-tune these AI models so they do what they're supposed to do when it comes to monitoring and maintaining enterprise network performance.

SASE and Zero Trust networks for the Edge

Security will continue to be a driving enterprise and networking focus, with security concerns being driven by two factors:

  • Cloud security (especially SaaS services) that is misconfigured and presents security vulnerabilities

  • More IoT and edge networks being deployed, often with wide-open security vulnerabilities.

The challenge with cloud is that enterprises use multiple clouds. Each cloud has its own security and network management tools. This means that the IT networking staff must get up to speed with each toolset and also make it a priority in all cloud onboarding procedures to set cloud security levels in the cloud to enterprise standards before cloud services are engaged.

At the edges of the enterprise where both IoT and remote users operate, security can be tightened by calibrating the default “wide open” security settings that IoT equipment arrives with before the devices are deployed—and by implementing zero trust networks that can authorize and monitor all users and network activities to ensure that appropriate security protocols are being followed.

Finally, the networking group can set an intermediate or “proxy” level of security authorization by subscribing to an outside SASE (secure access server edge) service that can perform network security authorizations before any user or activity is admitted into the internal enterprise network.

In each of these cases, network architecture will require revisions. IT networking staff will need additional training in SASE, cloud security tools, zero-trust networks, and IoT deployment.

The expansion of QoS

Networking groups use tools and establish benchmarks for monitoring everyday network performance, but not every organization uses QoS (quality of service).

Like network monitoring and managing technologies, QoS tracks network performance. The difference is that QoS sets extremely high standards for network performance because it must unfailingly support high-priority, mission-critical operations.

A company that moves its doctor-patient visits to a telehealth platform can’t afford poor quality or dropped video calls in emergencies. Unfortunately, not every clinic or company has in-house staff that is trained in QoS. They have to get outside help that can assist them in evaluating every inch of the network, going from node to node, examining pipeline end to end, checking devices, routers, servers, etc. This is painstaking and expensive work that to date has only been needed in a minority of enterprises.

This will change with nextgen networks, which will be expected to support the transport of large data payloads, AI, analytics and quality video livestreams. Not having QoS will likely not be an option——and networking staffs will need training in QoS methodology.

The bottom line

Network topologies and strategies will change as their generation does. More enterprise traffic will be running beyond enterprise walls. The demand for unfailing, high-quality network performance will be commonplace. IT networking staffs will need to be ready and upskilled for these emergent trends. If these looming trends aren’t on networking managers’ strategic roadmaps, they should be.

About the Author(s)

Mary E. Shacklett, President, Transworld Data

Mary E. Shacklett is an internationally recognized technology commentator and President of Transworld Data, a marketing and technology services firm.

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