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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…
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…
In today’s dynamic network environments, traditional MELT telemetry (metrics, events, logs, and traces) falls short when uncovering “unknown unknowns”—unforeseen issues that can cripple network performance and endanger network security. Packets and metadata generated from the packets data offer a more granular, real-time view, providing the level of detail necessary to identify these undetected anomalies and veiled vulnerabilities. The Shortcomings of MELT Telemetry While MELT telemetry can alert you to “known unknowns”—anticipated issues you’ve prepared for—its reliance on aggregation and predefined triggers leaves it blind to unexpected network events or…
On Oct 23-24 in New York City, we’ll be at the ONUG AI Networking Summit Fall 2024. Join us at the show and talk to Antonio Nearly, an LLM-powered holographic recreation of HPE CEO Antonio Neri that showcases an array of cutting-edge AI technologies. Antonio Nearly is highly knowledgeable about everything HPE, and you can ask him about anything else too — from professional soccer teams to blue whales. All you have to do is press a button and speak your question into a mic. It works…
Out-of-band monitoring techniques are necessary for AI clusters to provide trustworthy inferences. Out-of-band solutions provide latency analysis, decrease points of failure, and do not add additional burden on the network. [1] For AI clusters, the result of high latency are erroneous inferences. AI clusters are nodal network of GPUs that store and process inferences from machine learning models. [2] A slow latency for AI clusters inference is enough to produce incorrect inferences. The nodes of an AI cluster can create incomplete calculations on requests due to…
