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Red Hat OpenShift Commons Gathering Salt Lake City 2026Register for the in-person Red Hat OpenShift Commons Gathering alongside KubeCon + CloudNativeCon North America. This event brings together the global OpenShift community-including users, contributors, partners, and Red Hat experts-to share knowledge, build connections, and learn from real production experiences. Learn more 5 new ways Red Hat helps partners maximize business valueRed Hat is rolling out updates to the Red Hat Partner Program designed to streamline your daily operations, safeguard your investments, and give you a clear fin

Agencies are keeping missions moving while technology, security requirements, data demands, and public expectations all continue to shift at once. That’s why this year’s Red Hat Government Symposium couldn’t have come at a better time. Bringing together leaders from federal, state, and local government agencies and higher education, panelists focused on how their organizations are managing disruption without losing momentum. Across sessions, speakers shared practical examples of how agencies are making thoughtful technology decisions to strengthen security, improve service delivery, and

At Red Hat, our goal for the ecosystem has always been simple: build a predictable, profitable partner program for our partners to scale their business. As always, we remain committed to the future of open source, and that means continuously investing in the partners who help us bring that future to life.Now, we are rolling out a series of updates to the Red Hat Partner Program designed to streamline your daily operations, safeguard your investments, and give you a clear financial runway to build new pipeline. Here are five ways we are enhancing the global partner experience to help you maximi

A secured agent that can't reach anything is just expensive autocomplete with a badge. In "Why prompt-level guardrails aren't enough," I walked through how Red Hat AI allows you to give each agent a cryptographic identity and lock down what it can touch. That solves the trust problem, but it doesn't solve the connectivity problem, and the connectivity problem is where I see most enterprise agent rollouts stall—not because the model fails, but because the plumbing does.In our previous articles, we talked about how 3 failures hit a single AI agent deployment overnight—43 duplicate tickets, $

Insurance remains an incredibly data-heavy industry with deep roots. Based on product offerings and strict regulatory data retention rules, a significant number of existing systems, some decades-old, are still in operation. It's not uncommon to find COBOL-coded applications or AS/400s continuing to run mission-critical workloads.There's a valid reason for this: the insurance sector was an early adopter of these data-heavy environments, and the technology worked well.However, managing this data over decades created heavy technical debt. For example, liability insurance policies often require da

For system administrators and IT leaders, keeping infrastructure secure while strictly aligning with corporate compliance standards is a continuous, high-stakes balancing act. This challenge escalates dramatically when environments span legacy workloads or platforms locked into extended operational lifecycles.Managing disparate software repositories manually or trying to lock package versions across older, fragmented systems is highly time-consuming and introduces a severe risk of operational drift. When systems drift, predictability drops, compliance fails, and security vulnerabilities multip

An agent charged $4,000 to the wrong customer billing account. Nobody noticed until Monday. The agent wasn't broken—it was working exactly as designed. It had broad API credentials, the model picked a plausible but wrong account identifier, and nothing in the infrastructure stopped the call from going through. No identity boundary. No scope limit. No audit trail.I've seen teams react to failures like this by adding more checks inside the agent code—if-else blocks, hardcoded allowlists, manual credential rotation. That approach doesn't scale. When 3 failures hit a single AI agent deployment

The arrival of a cryptographically relevant quantum computer, often referred to as Q-day, is moving from a distant theoretical mathematical challenge to an urgent timeline that security teams must plan for today. Bad actors are already engaging in harvest now, decrypt later activities. This means they are capturing and storing encrypted enterprise traffic, intellectual property, and data logs today with the intention of running them through quantum hardware as soon as it becomes available.At Red Hat, we believe taking this threat seriously means acting before the crisis arrives. Rather than vi

If you read the first part of this article, you already know that physical AI isn't just another wave of automation. You saw how intelligent systems are solving real problems in operations, security, and maintenance in ways that traditional robotics simply can't. And you were introduced to the loop that makes it all work: perceive, reason, act.In this second part, we go deeper. We look at why AI is such a transformative ingredient for robotics specifically, why edge computing isn't an optional add-on but a hard requirement, and how Red Hat helps organizations build the open, enterprise-grade f

In our previous post, we talked about the API key lifecycle in MaaS. In this article, we'll set up the governance layer those keys bind to, focusing on 2 core controls: managing token quotas (via MaaSSubscription) and defining model access rules (via MaaSAuthPolicy).Models-as-a-Service (MaaS), an integrated component of Red Hat Openshift AI, aims to give enterprises a flexible GitOps friendly way to set up their policy framework.Both attach to models through a MaaSModelRef:MaaSSubscription defines how much a user can consume in a given time window.MaaSAuthPolicy defines which models a user is

Long before LinkedIn, my professional network consisted of the Yellow Pages and a landline. At the age of 15, I had the brainwave (and the audacity) to cold call every business I could find until I landed my 1st job. After making around 25 calls, a local specialty hair salon near my home asked me to come in, and shortly after, I was hired! I worked as an unofficial janitor, sweeping and cleaning up the space after school three times a week. From day one, I closely observed patterns, personalities, customers, the stylists' precision and their individual work styles. Noticing my (very obvious) c

The telecommunications industry is witnessing a shift in domain-specific artificial intelligence (AI). Following the success of the first iteration of the GSMA Open Telco AI initiative, the industry is entering its next phase with the announcement of Open Telco AI 2.0. This announcement marks a significant step in building AI models that truly understand the complex realities of telecommunications service providers.Bringing together Red Hat, ATT, AMD, Dell, Google, Microsoft, and GSMA, this collaboration aims to advance carrier-grade AI. By combining open source methodologies, specifically the

Healthcare payer organizations are navigating a complex intersection of rising member expectations, strict regulatory mandates, and aging technology infrastructures. Modernizing these environments to accelerate claims adjudication and improve the member experience is a key priority for many executives. However, the path to modernization is often blocked by isolated team structures and technical debt.To bridge this gap, many payers are turning to automation, such as Red Hat Ansible Automation Platform, as a strategic layer across their enterprise. However, despite the clear business outcomes, s

Your agent works. I know it does. You built it on LangChain or CrewAI or something custom, you tested it against real scenarios, and it handled them. The problem isn't the agent. The problem is everything around it.In "Why good AI agents fail in production: The missing infrastructure layer," 3 failures hit a single AI agent deployment overnight—43 duplicate support tickets, $4,000 charged to the wrong billing account, and a hallucinated refund policy that led to a $280 return the company had to honor. That agent worked perfectly in development, but broke in production because the production

Achieving infrastructure efficiency and controlling compute costs is a continuous effort. While traditional machine pools are effective for steady workloads, scaling diverse applications often requires balancing cloud utilization with the effort spent manually right-sizing instances, all while providing continuous node availability when compute demands spike. To help achieve this balance, we are introducing the Red Hat build of Karpenter, based on the upstream Karpenter project. With the release of Red Hat OpenShift 4.22, Red Hat build of Karpenter can be enabled on Red Hat OpenShift Service o

InfoWorld - Red Hat OpenShift 4.22 tackles cloud costs, AI workloadsInfoWorld looks at Red Hat OpenShift 4.22, the latest version of Red Hat's hybrid cloud application platform. The release focuses on cutting cloud infrastructure costs, simplifying operations of virtualized workloads, and securing sensitive data. Learn more Technically Speaking - Defining sovereign AI with open source ft. Jered FloydWhat happens to your business operations when your AI workflows run on a proprietary black box? Red Hat CTO Chris Wright and Jered Floyd break down the 4 pillars of sovereign AI and challenge com

Red Hat is pioneering the use of agentic AI to shift vulnerability management from volume to precision. By combining the security-hardened foundation of Red Hat OpenShift with advanced AI frameworks from NVIDIA, we're delivering actionable security intelligence that provides genuine business value for the enterprise. Here's the problem: A single software package can trigger hundreds of alerts because one imported function or library within it is theoretically vulnerable. Traditional scanners stop at the package level, generating a flood of false positives for vulnerabilities that are never act

For CIOs across the Middle East Africa, keeping systems online is the foundation of customer trust. As public sector institutions and private enterprises accelerate their digital transformation, maintaining this operational uptime is the top priority. In a complex business landscape, an infrastructure outage immediately halts crucial services, risks public safety, and compromises the user experience. Navigating this need for operational predictability is challenging for organisations operating in highly sensitive environments with strict compliance frameworks and data residency requirements.

Before anything reaches production, you have to test it, validate it, and sometimes learn about it from scratch. All 3 of these steps are necessary to have a properly running environment but your window to complete them is almost always shorter than expected. Building an environment from scratch also eats up more time and resources than any test should.For most teams that run lab sessions regularly, setting up a lab environment manually takes roughly 40 minutes every time. The process always looks the same:Provision a virtual machineRegister the systemConfigure software repositoriesDownload an

Enterprises want absolute clarity on their IT footprint: they want to know exactly what software is running, where it’s running, and how those deployments align with subscription entitlements. For many organizations, Red Hat Hybrid Cloud Console and subscription watch provide that visibility. But what happens when your infrastructure can't (or shouldn't) phone home? Air-gapped networks, government systems, manufacturing floors, and sovereign clouds all require a completely disconnected approach.That is exactly why we built discovery, an open source, agentless scanning tool that is a componen