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Deploying cutting-edge AI in U.S. government environments can present a formidable challenge. While the power of accelerated computing is essential for modern workloads, the path to achieving an Authority to Operate (ATO) is paved with the complex and time-consuming demands of applying controls such as the Defense Information Systems Agency’s (DISA) Security Technical Implementation Guides (STIGs). This crucial security hardening process can be a manual, painstaking effort that creates friction between development teams and security mandates, slowing innovation.Today, Red Hat is reducing tha

The most common task facing system administrators is patching infrastructure. It's time consuming, it requires coordination with application teams and stakeholders, and it often must happen in segments over time. These complications make it difficult to maintain environmental consistency, which in turn can lead to instability, performance issues, and more time spent by operations staff. Using Red Hat Insights content templates to patch Red Hat Enterprise Linux (RHEL) helps limit the complexity of these activities while also increasing consistency across an IT estate.Define, instruct, and patch

You’ve trained the model, packaged it on Red Hat OpenShift AI, and it’s ready to work. The next move is exposing it through an API so people and applications can use it. At that moment, your model stops being an internal experiment and becomes a front-door service. And like any front door, somebody is going to knock … sometimes it’s the right user, sometimes not.Your model is no longer just a project in a lab: it’s a production endpoint. And like any endpoint, it’s a target. How do you ensure that only the right applications and users are interacting with it? How do you protect the

These are exciting times for AI. Enterprises are blending AI capabilities with enterprise data to deliver better outcomes for employees, customers, and partners. But as organizations weave AI deeper into their systems, that data and infrastructure also become more attractive targets for cybercriminals and other adversaries.Generative AI (gen AI), in particular, introduces new risks by significantly expanding an organization’s attack surface. That means enterprises must carefully evaluate potential threats, vulnerabilities, and the risks they bring to business operations. Deploying AI with a

Standardizing your company’s operating environment starts with the operating system (OS), but it doesn’t end there. As the number of systems grows, configurations drift, maintenance becomes repetitive, and updates can quickly turn into a headache. At Red Hat, we support your standardization journey by providing you with what you need to deliver a robust, coherent, and integrated solution for your standard operating environment.In this post, I explore the key areas you should take into account along your standardization journey, and how these can be simplified using Red Hat technologies, pr

We are writing to provide an update regarding a security incident related to a specific GitLab environment used by our Red Hat Consulting team. Red Hat takes the security and integrity of our systems and the data entrusted to us extremely seriously, and we are addressing this issue with the highest priority. What happenedWe recently detected unauthorized access to a GitLab instance used for internal Red Hat Consulting collaboration in select engagements. Upon detection, we promptly launched a thorough investigation, removed the unauthorized party’s access, isolated the instance, and contacte

Recently, we’ve shared a lot about post-quantum cryptography, the great work we’re doing to make it available to you through our products, and the importance of preparing for a future with quantum computers powerful enough to break classic RSA-based cryptography. You may have heard about “Q-day,” the day when a cryptographically relevant quantum computer (CRQC) is available to break public-key encryption–the underpinning of our digital world today. If you missed it, this risk is real, and proactive organizations are already preparing for it. Q-day is predicted to occur between 2029 a

From communal effort to legal mandateThe world runs on open source. From the applications you use daily to the critical infrastructure powering our society, open source software is ubiquitous. However, this widespread adoption has brought with it an escalating need for robust security, a reality starkly highlighted by incidents like SolarWinds and the more recent XZ Utils vulnerability. While the open source community often demonstrates remarkable resilience and collaboration in addressing threats, a significant shift in responsibility is now underway, driven in part by legislation, such as th

Red Hat helps organizations embrace AI innovation by providing a comprehensive and layered approach to security and safety across the entire AI lifecycle. We use our trusted foundation and expertise in open hybrid cloud to address the challenges around AI security, helping our customers build and deploy AI applications with more trust.Understanding enterprise AI security risksAs organizations adopt AI , they encounter significant security and safety hurdles. These advanced workloads need robust infrastructure and scalable resources and a comprehensive security posture that extends across the A

AI is one of the most significant innovations to emerge in the last 5 years. Generative AI (gen AI) models are now smaller, faster, and cheaper to run. They can solve mathematical problems, analyze situations, and even reason about cause‑and‑effect relationships to generate insights that once required human expertise. On its own, an AI model is merely a set of trained weights and mathematical operations, an impressive engine, but one sitting idle on a test bench. Business value only emerges when that model is embedded within a complete AI system: data pipelines feed it clean, context‑