For years, many infrastructure teams treated the edge as a deployment variation. It was seen as the same cloud model, only stretched outward: more devices, more gateways, more locations and a little more latency. That assumption is proving costly. The edge is not just another place to run workloads. It is a fundamentally different operating condition ...

Over the past few years, organizations have made enormous strides in enabling remote and hybrid work. But the foundational technologies powering today's digital workplace were never designed for the volume, velocity, and complexity that is coming next. By 2026 and beyond, three forces — 5G, the metaverse, and edge AI — will fundamentally reshape how people connect, collaborate, and access enterprise resources ... The businesses that begin preparing now will gain a competitive head start. Those that wait will find themselves trying to secure environments that have already outgrown their architecture ...

In MEAN TIME TO INSIGHT Episode 22, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses DNS Security ... 

Network hardware vendors are raising prices again — and enterprises are feeling it at renewal and refresh time ... Here's the reality: the buy-rack-depreciate cycle is no longer the only way to build a world-class enterprise network — and this isn't a one-off. It's sustained upward pressure across the hardware stack ...

As enterprise networks get more complex, encompassing on-prem, cloud and hybrid systems and applications, network automation is no longer optional. It's critical for uptime, security and scale. Yet persistent misconceptions about increasingly capable network automation platforms among the very NetOps professionals who would benefit the most from using them are holding back adoption. Here are 5 of the most common of those misconceptions, and why NetOps teams might want to re-think them ...

While 87% of manufacturing leaders and technical specialists report that ROI from their AIOps initiatives has met or exceeded expectations, only 37% say they are fully prepared to operationalize AI at scale, according to The Future of IT Operations in the AI Era, a report from Riverbed ...

Many organizations rely on cloud-first architectures to aggregate, analyze, and act on their operational data ... However, not all environments are conducive to cloud-first architectures ... There are limitations to cloud-first architectures that render them ineffective in mission-critical situations where responsiveness, cost control, and data sovereignty are non-negotiable; these limitations include ...

For years, cybersecurity was built around a simple assumption: protect the physical network and trust everything inside it. That model made sense when employees worked in offices, applications lived in data centers, and devices rarely left the building. Today's reality is fluid: people work from everywhere, applications run across multiple clouds, and AI-driven agents are beginning to act on behalf of users. But while the old perimeter dissolved, a new one quietly emerged ...

In MEAN TIME TO INSIGHT Episode 21, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses AI-driven NetOps ... 

Every business today depends on real-time connectivity — for meetings, cloud apps, customer transactions, and increasingly, AI-driven workloads. Yet one of the most common reasons performance feels inconsistent has nothing to do with servers or software. It's packet loss — the silent destroyer of digital experience ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

The conversation around AI in the enterprise has officially shifted from "if" to "how fast." But according to the State of Network Operations 2026 report from Broadcom, most organizations are unknowingly building their AI strategies on sand. The data is clear: CIOs and network teams are putting the cart before the horse. AI cannot improve what the network cannot see, predict issues without historical context, automate processes that aren't standardized, or recommend fixes when the underlying telemetry is incomplete. If AI is the brain, then network observability is the nervous system that makes intelligent action possible ...

In MEAN TIME TO INSIGHT Episode 20, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA presents his 2026 NetOps predictions ... 

Industry experts offer predictions on how NetOps and NPM will evolve and impact business in 2026. Part 2 covers NetOps challenges and the edge ...

APMdigest's Predictions Series continues with 2026 NetOps Predictions — industry experts offer predictions on how NetOps and Network Performance Management (NPM) will evolve and impact business in 2026 ...

The rise of hybrid cloud environments, the explosion of IoT devices, the proliferation of remote work, and advanced cyber threats have created a monitoring challenge that traditional approaches simply cannot meet. IT teams find themselves drowning in a sea of data, struggling to identify critical threats amidst a deluge of alerts, and often reacting to incidents long after they've begun. This is where AI and ML are leveraged ...

Getting applications into the hands of those who need them quickly and securely has long been the goal of a branch of IT often referred to as End User Computing (EUC). Over recent years, the way applications (and data) have been delivered to these "users" has changed noticeably. Organizations have many more choices available to them now, and there will be more to come ... But how did we get here? Where are we going? Is this all too complicated? ...

From smart factories and autonomous vehicles to real-time analytics and intelligent building systems, the demand for instant, local data processing is exploding. To meet these needs, organizations are leaning into edge computing. The promise? Faster performance, reduced latency and less strain on centralized infrastructure. But there's a catch: Not every network is ready to support edge deployments ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

Artificial intelligence is transforming network operations (NetOps), supercharging automation, enabling new predictive capabilities, improving visibility and powering nearly continuous optimization ... When trained on live network data and large libraries of validated automations, GenAI and agentic AI can help NetOps teams be more productive while making networks more reliable, easier to manage and secure. And as agentic AI becomes more powerful, AI's overall usefulness to the NetOps team will increase exponentially ...

Organizations across the globe face unprecedented cybersecurity challenges as their digital footprints expand across cloud, on-premises, and remote environments. Ransomware continues to surge as one of the top global cyber threats, with attacks increasing(link is external) by 33% globally in 2024 and organizations experiencing an average of 1,200 weekly attacks — the highest in three years ...

In MEAN TIME TO INSIGHT Episode 18, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses networking for artificial intelligence ... 

Aryaka recently conducted a series of surveys in three distinct industries (manufacturing, transportation, and business services), looking deeper at key trends and pain points in networking and security. Despite differences in industry priorities and digital maturity, IT leaders in these sectors are all clearly facing an uphill battle to secure increasingly hybrid, cloud-connected, and distributed infrastructure without overwhelming their limited resources ...

Most teams go straight to the usual suspects when performance tanks in the cloud: app bugs, code regressions, maybe even the cloud provider itself. However, the real bottleneck is hiding in plain sight more often than not: the network ...