Cybersecurity & Networking

  • The Role of AI and Automation in Networking

    Applications are deployed across data centers, multiple public cloud services, and numerous edge locations. Hybrid work initiatives mean employees are increasingly connecting to these applications from the office, their home, and other remote locations. Regardless of where they are, employees expect to be productive and have a positive experience. Likewise, organizations depend on the network environment to deliver highly available and secure connectivity to every application, location, and employee. However, network operations teams now have exponentially more network connections, endpoints, and data traversing the network to contend with.

    Operations teams struggle to collect all the network data, correlate it with context, and act decisively to resolve issues that arise. As a result, organizations need to take advantage of the intelligence provided by AI and the ability to automate more than just initial configurations. Importantly, they’ll need to determine how long it will take for operations teams to become comfortable with and trust these technologies as well as the implications of generative AI for network operations.

    To gain further insight into these trends, Enterprise Strategy Group surveyed 362 network professionals at organizations in North America (US and Canada) involved with network AI and automation technology and processes.

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  • Emily Marsh

  • Christian Perry

  • Securing SaaS Ecosystems Survey

    This Complete Survey Results presentation focuses on the top use cases for SaaS security, the benefits realized or expected by organizations implementing different SaaS security practices, and the key stakeholders across the SaaS security buyer’s journey.

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  • Zero-trust network access (ZTNA) is an important supporting component of zero-trust strategies that allows users to securely connect to the infrastructure, applications, and services they need to do their jobs from anywhere. Recent research by TechTarget’s Enterprise Strategy Group revealed some interesting findings when it comes to how this approach is stacking up to the technology that was previously predominately used for this functionality, VPN.

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  • Microsegmentation is a strategy that has helped many network and cybersecurity teams by creating secure zones within the network; this makes individual parts more manageable at scale and ensure cyberattacks cannot run rampant through an open field of digital infrastructure. Recent research by TechTarget’s Enterprise Strategy Group studied this approach in the context of zero-trust strategies to see how organizations are faring and where they could use help.

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  • Rapid application development and deployment are major priorities for many organizations today, but the networking teams tasked with managing multi-cloud environments are struggling to ensure connectivity and security for these fast release cycles. Recent research by TechTarget’s Enterprise Strategy Group revealed that networking teams increasingly feel pressure to be more responsive to developer requests and must better align to and support modern application environments.

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  • Many organizations today rely on multiple cloud services to match the needs of their various IT operations, but this introduces a complex set of challenges for the networking teams in charge of such environments. Recent research by TechTarget’s Enterprise Strategy Group revealed that these teams have concerns about cybersecurity in multi-cloud networking environments as well as ideas regarding how to combat them.

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  • This Complete Survey Results presentation focuses on private 5G adoption, use cases, connected devices, benefits, challenges, comparisons with Wi-Fi deployments, third-party assistance, consumption models, supplier preferences, edge deployment factors, and future spending plans.

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  • This Complete Survey Results focuses on automation and AI maturity, network automation use cases, network domains using AI, network AI providers, network AI use cases, automation and AI performance against expectations, use cases for integrated AI, the challenges of using AI in the network, and generative AI use cases.

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  • And so it begins, again. A few weeks ago, I joined TechTarget’s Enterprise Strategy Group to lead the Networking and Network Management analysis practice, and I could not be more thrilled. I’ve spent the last 30-plus years in this space, working mostly for network management product vendors in engineering, product, project, marketing, partnership and executive leadership roles. Amid that 30-plus year span, there was also six-plus years as an industry analyst, putting my knowledge and experience to work in tracking and analyzing real life networking challenges and potential solutions. It is to this role that I now return, to study, learn, listen, contemplate, discuss and share findings and insights.

    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.

  • TechTarget and Enterprise Strategy Group ran a global survey examining where buyers source information throughout their purchase journey. This report focuses on responses from almost 700 global technology buyers of which 385 were Sr. IT or Business Leadership. Below are 5 insights you can learn from this report:

    • Media types B2B buyers rely on when building a vendor shortlist
    • Channels where B2B buyers are spending more time doing research
    • What buyers want from vendor content including what motivates them to attend webinars
    • Trends in vendor loyalty, including what causes customers to switch vendors/suppliers
    • What tech vendors need to do to maintain a strong ongoing relationship with their customers
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