Why so long in the sector? Reason number one: Networks have never been more essential. Just look at our tech-heavy economy and you quickly realize that without reliable, high-performing networks, at the local, wide area, data center and internet levels, everything grinds to a halt. Networks are the plumbing of the modern world, and just like the physical plumbing in our homes and businesses, they are often taken for granted because they just work. But when something doesn’t work, networks typically get the first blame. And while networks do have their fair share of culpability, the reality is that problem sources are more commonly elsewhere in the stack—in the apps, servers, storage, endpoint or, in no small percentage of cases, with Layer8—the user themselves.

Reason number two: When there is a problem and there is no obvious cause—such as a server or switch on fire—then the network can be an excellent place from which to start the process of isolation and identification. Just like a traffic map for a busy metro area, viewed in Google Maps or Waze, you can use the network to quickly recognize where things are working smoothly and where they are not, so you can zoom in on the most likely source of issues, accelerating and focusing efforts to restore normal function.

Reason number three: It’s never dull. There is so much change to keep up with. Networking technology has largely settled in at Layers 2-4, converging around Ethernet and TCP/IP, and this is a good thing. No one wants to go back to the days of FDDI, Token Ring, IPX and Banyan Vines, when interoperability was a massive challenge. But this convergence does not mean the fun is over. There is still innovation due to the relentless growth in network speeds and capacity, and we continue to see evolution and change in other parts of the stack. Witness the continued, rapid development of wireless access, such as WiFi 6, 6+, 7, and Private LTE and 5G. Look for some fresh insights coming from Enterprise Strategy Group on this topic very soon.

And we can’t forget the fascinating work going on to support purpose-built generative AI (GenAI) infrastructure, including the use of both traditional networking technologies and specialized tech developed for storage networking such as RoCE—RDMA over Converged Ethernet—and Infiniband. I’ll be tracking the latter under the general heading of “Networking for AI.” I’ll be writing more on this very soon as well.

Of course, the change does not stop there. Personally, I’m fascinated by a number of ongoing developments in the sector, and hope to spend time studying and covering the following issues and challenges:

• Convergence of networking and network security. In my view, this is an absolute necessity in today’s connected world, lately manifesting using integrated functions, SASE, SSE and multipurpose monitoring and analytics techniques.
• Multi-cloud, hybrid networking. This freight train has been heading toward us for a long time, bringing major complexity headaches, but also opportunities to rethink network strategies.
• Network-as-a-Service. Part of a broader move toward a subscription basis for acquiring and licensing network technology, but also a great alternative for modernizing and hardening enterprise networks.
• AI for Networking. GenAI and natural language processors are already working their way into network management tools for diagnostic and troubleshooting workflows, but can they also make a difference in planning, configuration and overall network automation?
• Network Observability. Making sure that proactive, effective visibility exists across complex, hybrid networks, and is fully integrated with cross-domain observability stacks continues to be a priority for most but also a struggle for many.

There’s more, but that should be enough to get me off and running. As I renew old contacts and make new ones across the networking sector, I’ll have my head up and ears open for feedback. What excites you about networking and network management today? What areas of change are you most interested in? I’d love to hear and discuss.

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Despite these risks, generative AI holds great cybersecurity potential. Generative AI could help improve security team productivity, accelerate threat detection, automate remediation actions, and guide incident response. These prospective benefits are so compelling that many CISOs are already experimenting with GenAI or building their own security LLMs. At the same time, security professionals remain anxious about how cybercriminals may use GenAI as part of attack campaigns and how they can defend against these advances.

Have organizations embraced GenAI for cybersecurity today, and what will they do in the future? To gain further insight into these trends, TechTarget’s Enterprise Strategy Group surveyed 370 IT and cybersecurity professionals at organizations in North America (US and Canada) responsible for cyber-risk management, threat intelligence analysis, and security operations, with visibility into current GenAI usage and strategic plans.

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As a result, organizations are turning to encryption to maintain cyber resilience in response to a successful data breach as well as to ensure data privacy and compliance. Although organizations understand how encryption protects data, they struggle with the implementation, specifically how encryption and key management solutions balance security, usability, performance, compatibility, and costs. Further compounding these problems is quantum computing’s potential to break current encryption capabilities, representing another challenge to securing sensitive data. Vendors need to demystify and simplify encryption and key management.

To gain further insight into these trends, TechTarget’s Enterprise Strategy Group surveyed 387 IT, cybersecurity, compliance, and DevOps professionals at organizations in North America (US and Canada) involved with encryption and data security technology and processes.

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Source: Enterprise Strategy Group Research Report, Enterprise Strategy Group Research Report, Enabling Modern Business With Multi-cloud Networking, March 2024.

Organizations are increasingly deploying applications across multiple public cloud locations in a meaningful way. This is vastly different from only three years ago when the majority of organizations were using multiple cloud service providers but primarily depending on only one for almost all of their service needs. Today it is common for organizations to deploy production and mission-critical applications across multiple public cloud service (e.g., IaaS) providers. Modern application environments are driving this adoption as organizations seek to optimize performance and quickly and easily set up connections to these cloud providers.

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