Red Hat

The financial services industry, like many other sectors, is aiming to make best use of their hardware in the age of resource-intensive AI workloads. Financial services companies have come to rely on the advantages of a container-based architecture, but may worry that container orchestration platforms add performance penalties that could exacerbate resource constraints.

AI tools are transforming how system administrators and developers manage their infrastructure,  but when using generic AI assistants to troubleshoot Red Hat Enterprise Linux (RHEL) systems, the advice can sometimes lack distribution-specific context. An AI tool might assume a different Linux environment, suggest commands from other distributions that do not apply to RHEL, or recommend disabling critical security controls to resolve a permissions issue.

NEW YORK, ARMONK, N.Y. and RALEIGH, N.C. - June 26, 2026 — Deloitte, IBM, and Red Hat today announced a collaboration to help protect the software supply chain against increasingly automated cyber threats. Deloitte joins the initiative as an integration collaborator for Lightwell, bringing its broader secured software supply chain architecture and cyber risk services to the large-scale enterprise open source security model deployed by IBM and Red Hat.

-minute read Red Hat, IBM, and Palo Alto Networks have expanded Project Lightwell to combat AI-driven threats. The collaboration delivers rapid, network-level virtual patching alongside open-source software remediation to securely fix vulnerabilities. Learn more Red Hatter Mike McGrath joins the podcast to discuss RHEL security best practices, the relationship with CentOS Stream, and how Red Hat balances open-source values with enterprise AI innovations.

AI models are outpacing human-scale security operations. AI can surface vulnerabilities across major systems faster than teams can act, and most organizations lack the patching capacity to keep up. The solution isn't more intelligence—it's a smarter approach to remediation and risk management. The bottleneck isn’t intelligence, it’s response. IT teams must react to threats while maintaining a hardened posture, and automation makes that possible at machine speed.

Every network operations (NetOps) professional knows the anxiety of a manual configuration update. Even when you meticulously plan the change, a single unrecorded variable or an ad hoc configuration tweak can cascade into unexpected downtime. Across large enterprises, network teams are constantly fighting a losing battle against configuration drift—the gradual, undocumented departure of live network state from the intended design—caused by these sorts of errors.

Platform engineering, security architecture, and operations teams are being asked to support 2 realities at once: modern application platforms such as Red Hat OpenShift, and long-lived Red Hat Enterprise Linux (RHEL) fleets that still run critical automation. These parallel systems introduce risk, especially around how  users, workloads, or automation identities can be authenticated across environments. But there’s also larger questions at play: What boundary exists after privileged work starts?

AI coding assistants are transforming software development. The debate is no longer about whether to adopt them, but how to integrate them without compromising platform security, code quality, or operational compliance. AI has changed the economics of code production Whether you're developing software in a proprietary enterprise or open source environment, you've witnessed a fundamental shift over the past year.

This past March, the community gathered for Red Hat OpenShift Commons in Amsterdam. As the "zero day" kickoff to KubeCon and CloudNativeCon Europe 2026, there was no shortage of innovative presentations and discussions, but one session stood out, "Sit, Stay, Deploy: Teaching a Robot Dog with Red Hat OpenShift." Figure 1., ITQ staffers Johan van Amersfoort, Chief Evangelist and AI Lead, and Sander Harrewijnen, Technologist speaking at the OpenShift Commons Gathering in Amsterdam.

As the world prepares for the next era of human spaceflight, ensuring the health of astronauts on missions to the Moon and Mars is a top priority. However, it presents a significant challenge for missions the farther away from Earth we go: providing high-quality medical care when real-time communication with Earth-based doctors could be limited or impossible.