Enterprise IT Insights, Product Reviews & Strategy!
Artificial intelligence is pushing data center infrastructure beyond traditional limits. Modern AI workloads rely on dense clusters of GPUs that generate intense heat in a confined space, far exceeding what conventional systems were designed to handle. Air cooling, once the
AI data center networking is now a direct driver of AI performance. In a traditional data center, the network mainly supports application traffic, storage access, and routine east-west communication. In an AI cluster, the network affects how quickly GPUs can
Enterprise IT teams are under pressure to do more with tighter budgets, shorter timelines, and less predictable hardware availability. Server refresh projects that once followed a clear plan can now face higher costs, delayed shipments, and limited access to the
Traditional perimeter-based security no longer reflects how modern organizations operate. Cloud platforms, remote work, SaaS applications, and hybrid infrastructure have dissolved the idea of a fixed network boundary and attackers have adapted accordingly. The cost of this gap is high.
Enterprise IT teams are under pressure to expand capacity without stretching budgets or waiting months for new equipment. Hardware refresh cycles, data growth, virtualization, backup needs, and edge deployments all create demand for reliable servers. But new infrastructure can come
Modern IT environments no longer operate within a single, defined network. Users connect from home, offices, and mobile devices. Applications run across cloud platforms, on-prem systems, and hybrid environments. Data moves between all of them constantly. This shift has made
10 Gigabit Ethernet (10GbE) SFP+ SR optics remain a core component in modern enterprise and data center networks. Even as higher-speed interfaces evolve, short-range 10G connectivity continues to support switch uplinks, server communication, and aggregation layers with predictable performance and
Modern data infrastructure decisions are no longer driven by capacity alone. Performance, scalability, and resilience now determine whether AI pipelines run efficiently or stall under pressure. Enterprises building for analytics, virtualization, and AI workloads need storage systems that align with
Server memory decisions have become more important in 2026. Many organizations still run stable DDR4 servers, while newer platforms are moving toward DDR5 for higher bandwidth, larger capacity, and better long-term support. The challenge is simple: DDR5 is not always
Upgrading an HPE ProLiant server is rarely just a parts swap. It is a chance to fix bottlenecks, add resilience, and extend the useful life of a platform that already supports core business systems. For most IT teams, the real
A server upgrade solves one problem but creates another: what happens to the old enterprise servers left behind? These systems may no longer run production workloads, but they can still contain sensitive data, useful parts, resale value, and environmental risk.
Education IT budget allocation is no longer a simple device plan. Schools, libraries, and SLED buyers now fund laptops, Wi-Fi, switching, internet, cloud tools, cybersecurity, storage, licensing, support, and hardware refresh cycles at the same time. That creates pressure for
