For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...
As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...
The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...
The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...
Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...
Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...
Top-performing businesses prioritize data-driven decision making, enabling leaders to move from intuition and gut feel towards evidence-based judgment. But that judgment is only sound when the data underpinning decisions is accurate. With incident management, data accuracy is particularly important. Long-term revenue, customer trust, and operational stability depend on high-quality data that enables teams to quickly identify and address the root cause of major incidents. Against this backdrop, governance becomes a critical endeavor to ensure the right data drives the right action ...
In MEAN TIME TO INSIGHT Episode 26, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network compliance ...
Most production autonomous agents do not run in a vacuum. They run inside cloud infrastructure: virtual machines, containers, pods, managed clusters or private servers. That is where most operations teams start monitoring. Is the VM alive? Is the container running? Did the pod restart? Is memory stable? Is CPU too high? Did the health check pass? Those signals are useful. They tell you whether the shell around the agent is alive. They do not tell you whether the agent inside is actually operational ...
Enterprise IT environments have never been more observable ... Yet many organizations still grapple with outages, lengthy incident resolution cycles, and increasing complexity. Most teams do not suffer from a shortage of data. They struggle to determine what deserves attention and what action to take next ... Enterprise IT operations must move beyond monitoring and visibility. The next stage of maturity is decision operations, an approach that helps teams make faster, better-informed decisions ...
The biggest challenge in multi-cloud operations today isn't a technical one. It is a fundamental lack of operational transparency. Historically, cloud architecture was dominated by a singular focus on connectivity ... That initial phase is over. Today, spinning up a highly flexible environment across cloud providers, on-premises infrastructure, and various SaaS platforms is standard operating procedure. But as organizations start layering automated workflows and intelligent systems on top of this massive footprint, a much tougher question comes to the surface: Are we actually equipped to track data paths across these highly distributed environments? ...
Last year, there was a day where I spent 20 minutes just figuring out what someone actually wanted. The Slack message said "need access to the thing" ... I spent a chunk of this spring digging into how widespread that confusion is, and the numbers surprised me ... 63% said their team had experienced delayed or lost revenue because of missing or delayed internal requests. 30% reported both ...
While data center developers anticipate a prolonged period of expansion, power availability remains the defining constraint, according to the Data Center Power Report from Bloom Energy. At the same time, a broader set of barriers — including rising construction costs and growing community scrutiny — is threatening to slow the pace of new data center development. Key findings from the report include ...
Electricity consumption for data centers worldwide is projected to grow 26% in 2026, according to Gartner ...
For decades, identity security followed a straightforward rule: authenticate once, then trust ... That environment no longer exists. Today's enterprises span cloud platforms, SaaS tools, partner ecosystems, and increasingly autonomous AI-driven workflows. Employees connect from everywhere, devices vary in trustworthiness, and attackers exploit this complexity by targeting the weakest link: identity. The problem isn't that credentials are obsolete. It's that they no longer reflect reality ...