Modern networks are living ecosystems — vast, interconnected, and evolving by the second. From cloud to edge, across vendors and domains, they generate more data than traditional tools or teams can absorb. Managing this complexity requires more than automation scripts and dashboards. It demands intelligent systems that deliver answers and actions, not just alerts. That’s the idea behind IBM Network Intelligence, a new network-native AI platform designed to help organizations shift from reactive problem-solving to proactive performance assurance. Developed in collaboration with IBM Research, it…
It’s common to think of IT as its own silo, but the truth is that it’s become existential across the entire enterprise. And yet, when a flood of alerts hits the NOC, the response is often anything but resilient. It’s usually quite hectic as engineers scramble to correlate signals and manually trigger fixes. It’s a familiar story with a familiar question: why haven’t we solved this already? Many enterprises have invested heavily in automation, and while visibility sometimes improves, the ability to autonomously act on…
If you could claw back some cash from your company’s technical debt, no doubt you would. Instead of having 70 to 80% of your IT budget stuck on maintenance on aging infrastructure vs. innovation, imagine having enough budget to put towards cloud modernization and migration, GenAI, agentic AI and intelligent automation, real-time analytics or zero trust security. Now there are certainly legitimate reasons why tackling technical debt isn’t easy. You get caught up in firefighting bugs and there’s no time to improve the design or…
If you’ve gone through an MPLS to SD-WAN transition or simply operate a network with 100+ sites, you’ve likely undergone some form of “bulk” connectivity procurement in the past. Bulk procurement comes with drawbacks – complex RFP creation, tons of quoting to manage, lengthy contracting, and painfully complex installations. That said, I’ve found that IT leaders often espouse the benefits of bulk procurement. Why? The bulk discount! If you buy many circuits at once, you’ll end up with a lower price per Mbps on average…
The evolution of artificial intelligence, particularly the rise of large language models (LLMs) and deep learning, has created an immense demand for computational power primarily driven by GPUs. However, maximizing GPU efficiency requires a robust networking infrastructure that ensures minimal latency and zero packet loss. This post highlights the critical role of Data Center Bridging (DCB) with a focus on its two key components; Priority-based Flow Control (PFC) and Explicit Congestion Notification (ECN) in achieving lossless and high-performance networks suitable for large-scale GPU deployments in…
For the past decade, IT leaders have driven innovation by migrating workloads to the cloud. But now, as AI, machine learning, and high-performance computing take center stage, infrastructure needs have shifted. Compute is no longer just about flexibility and scale—it’s about raw power, speed, and efficiency. And that’s where traditional cloud models are falling short. The Challenge: Cloud Isn’t Keeping Up With AI When cloud computing became mainstream, it promised elasticity and simplicity. But that promise is starting to break under the weight of generative…
In today’s digital-first world, the question for IT leaders isn’t if problems will arise—it’s how early you can spot them, and how fast you can resolve them. Yet despite massive investments in observability, ticketing platforms, AIOps solutions and automation, too many organizations remain stuck in firefighting mode—managing symptoms instead of solving root causes. It’s time to break the reactive cycle. With Cognitive AI Learning, IT teams can proactively identify and resolve recurring issues before they impact services. From Reactive Chaos to Proactive Control The traditional model of problem management is reactive…
The introduction of production level AI has become the trigger for IT organizations to re-evaluate their entire approach to providing business services across the organization. Decades of incremental growth using proprietary technologies in networking and compute is now being parked, in favor of fresh blank-canvas approaches to IT. And for the networking practitioners, it became clear that that original promise of seamless integration and single-vendor support came at a steep price – years of vendor lock-in, limited customization, missed capabilities, and greatly inflated costs. But…
The shift to cloud, SaaS, and hybrid work is no longer breaking news. What is surprising? How many IT and network teams are still trying to stitch together architectures that weren’t designed for today’s distributed world. Data is everywhere. Users are everywhere. Applications live across SaaS, public cloud, and private data centers. Yet too often, traditional network and security architectures can’t keep up, creating bottlenecks, security gaps, and user frustration. Modern SASE and SD-WAN architectures promise agility, resilience, and better performance, but only when they’re…
AI infrastructure is growing at an unprecedented pace. Enterprises are racing to build clusters of GPUs, scale up AI workloads, and modernize their data pipelines. Yet one critical layer is often overlooked in these initiatives: the network. While AI and data leaders focus on compute, storage, and models, the network quietly becomes the bottleneck. Traditional, static networks—built for legacy application traffic—can’t handle the dynamic, latency-sensitive, high-throughput demands of distributed AI workloads. And without visibility, orchestration, and automation across the full stack, enterprise IT leaders are…
