Disaster Recovery Journal Summer 2026

In database environment, this trend is especially clear. SQL Server on Windows was the default choice, for years. Today, in order to align with modern infrastructure strate gies, more enterprises are running SQL Server on Linux and in containers. The motivation is practical: n Lower operating costs n Reduced platform complexity n Easier automation n Better alignment with cloud-native tools This is about harmonization. Fewer platforms mean fewer silos and fewer failure points. How Infrastructure Refreshes Are Being Driven By AI Artificial intelligence (AI), as you likely already know, has become the common catalyst that turns long-dis cussed modernization plans into immedi ate priorities. Companies are deploying AI in customer service, analytics, opera tions, and more, and they are quickly realizing how dependent these systems are on reliable, secure, and scalable data platforms. Most enterprise AI initiatives rely on proprietary data ... which cannot simply be pulled from public sources. It must be stored, protected, governed, and accessed at scale. Early AI projects were often small experiments. However, today organiza tions are building systems they expect to depend on for core business operations. That changes the infrastructure conversa tion entirely. Why Agentic AI Raises Governance Challenges For tasks like summarization, drafting, and analysis, generative AI has already become common. However, agentic AI, the next phase, introduces much deeper operational questions. These systems are designed to perform multi-step actions across environments — examples include provisioning servers, configuring net works, managing storage, and deploying applications. Much of this is already possible, technically.

AI Is Stress-Testing Your IT Stack. Are You Ready? By DON BOXLEY Jr. F or many organizations, the biggest barrier to adopting artificial intel ligence is not access to models or talent. Its infrastructure. I have seen firsthand how mance, and operational continuity were required with each shift. This pattern reflects what I see across the industry — organizations rarely transform overnight. They respond to business realities, cost structures, and workforce constraints, moving incrementally. Companies move when business pres sure makes change unavoidable. From Windows to Linux, the Quiet Migration

deeply legacy systems are embedded in daily operations, after working with enterprises for more than a decade. Most companies are not starting from scratch – they are modernizing platforms that have been running reliably for years. Today, evolving those systems without introduc ing unacceptable risk is the challenge. Today’s AI initiatives are accelerating that pressure. In 2010, our focus was on helping cus tomers make Windows-based applications more resilient and portable. Customer needs have changed, over time. First came cloud adoption. Then Linux. Then containers. Then Kubernetes. New approaches to availability, perfor

The steady migration from Windows centric environments to Linux-based platforms is one of the most important shifts underway today. This trend is being driven by the need to reduce licensing costs and simplify operations, as well as streamline support. In other words, rather than maintaining multiple parallel systems, they are standardizing on Linux, containers, and Kubernetes.

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