The Onug Blog
Enterprise Cloud 2.0 Technology Solutions, Strategy and Use Cases
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Agentic AI—intelligent systems capable of proactive, context-aware decision-making—is reshaping how corporations operate. Rather than forcing organizations to rely on rigid, feature-laden enterprise software that only fulfills a fraction of their needs, Agentic AI learns a company’s unique business logic to generate predictive, customizable workflows in real time. This shift not only enables “digital twin” simulations of corporate operations—letting leaders test new ideas or products in a virtual environment before rolling them out—but also demands a radical rethinking of enterprise compute infrastructures. To fully harness Agentic…
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…
For years, enterprise network and security management has relied on a centralized model that’s starting to feel like a relic of a bygone era. Picture this: every networking device, every security appliance, every switch, router, and firewall diligently sending a flood of system logs, SNMP data, alerts, and threat indicators to a massive, centralized data lake. It’s a digital haystack—overflowing with terabytes of information, growing daily, and hiding the critical insights engineers need to keep the infrastructure humming and secure. When an incident strikes—say, a…
Lightyear’s new report highlights telecom industry and pricing trends observed in its proprietary dataset, illustrating how these factors may impact enterprise IT infrastructure strategies. Lightyear, the leading provider of enterprise telecom management software, release its highly anticipated 2025 State of Connectivity Report. This comprehensive report utilizes Lightyear’s proprietary dataset to provide timely insights on telecom industry and pricing trends. “We at Lightyear are rethinking the enterprise telecom experience from first principles, and a significant component of doing so involves helping enterprises better inform telecom decisions with…
In a recent interview with Chris Drumgoole, President of DXC Technology’s operating unit and former Global CIO at GE, Nick Lippis of ONUG explored the transformative shifts across the internet, cloud, and AI eras. These technological epochs, while interconnected, differ significantly in deployment dynamics, cultural impact, and operational challenges. Here are five key areas of distinction and an analysis of why AI’s adoption mirrors the internet era, accelerating its rollout and challenging IT teams to adapt rapidly. Speed of Adoption: The internet era emerged organically,…
Artificial Intelligence (AI) is sparking innovation and transforming the data center landscape. Massive buildouts are required to support each new AI model, introducing increasing scale and complexity with every iteration. Staying competitive demands innovative approaches to boost operational efficiency and manage rising costs. In this blog, we’ll explore how a Network Source of Truth (NSoT), combined with a comprehensive automation strategy, can be a cornerstone of this transformation. The scale of AI computational power, and consequently energy consumption, is expected to surge in the coming…
As technology progresses and permeates all facets of modern life, the sophistication and scale of cyber threats continue to grow, presenting a formidable challenge to businesses worldwide. The consequences of a data breach can be catastrophic, meaning cybersecurity is at the top of the priority list. As such, it’s imperative for organizations to find efficient and effective solutions to protect their networks, safeguard sensitive data, and ensure business continuity. Cybersecurity Challenges in Modern Networks With your watch, refrigerator, and car all connected online, malicious actors…
Why has network automation failed to live up to expectations? After more than two decades of effort, millions of man-hours, and hundreds of tools created, network automation has largely not achieved its intended objective of eliminating manual operations. Multiple industry association surveys (e.g., Enterprise Management Association, Gartner) show that most enterprises have automated less than half of their data center tasks. Why is this so? When asked, most IT network operators would say that “automation” should help them do manual, repetitive tasks faster. But fast…
