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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

While many organizations have recently adopted a cloud-first strategy, a significant number of those have since pivoted to operating in an open hybrid cloud environment. For insurance organizations, adopting a hybrid cloud strategy was largely because moving all operational data to the public cloud environments was impossible due to strict regulatory requirements and legal data privacy concerns.Insurers hold a vast amount of proprietary, personally identifiable data. In addition to basic financial data, insurers need to have sensitive information about policyholders so they can accurately ass

Red Hat AI 3.4 is officially available. While it is packed with incredible engineering milestones, business leaders care less about the underlying code and more about one critical question: How does this platform help scale the business?For organizations currently struggling to push AI past the proof-of-concept (PoC) stage and into fully operational, revenue-driving production environments, this update addresses those exact challenges. A recently commissioned Forrester Consulting Total Economic Impact™ (TEI) study highlighted that Red Hat AI delivered an impressive 233% ROI by drastically dr

Edge computing environments present distinct hurdles as companies move processing capabilities nearer to where data is generated. Customers across industries, especially in retail, industrial, and telecommunications sectors, are increasingly demanding high availability for their edge deployments.However, achieving high availability traditionally requires a three-node cluster to establish a reliable quorum. The primary factor driving organizations toward alternative topologies for large-scale edge deployments is the prohibitive cost of powering, maintaining, and deploying a third node across hu

Every company that depends on physical operations is dealing with the same set of problems today. The infrastructure that was built years ago demands changes faster than operations teams can adapt. Repetitive tasks done by humans at high speed produce errors. The system wasn't designed to be monitored at scale. On top of all that, competitive pressure keeps growing, regulatory requirements are increasingly strict, and many organizations are locked into rigid automation systems that can't evolve with their needs.These are structural problems, and incremental improvements within the current mode

In many cases, using agentic AI for incident response automation means sending infrastructure logs to frontier AI models. Every job failure log (complete with hostnames, IP addresses, and system topology) would leave infrastructure the moment it hit a large language model (LLM) endpoint, which would raise huge red flags for compliance teams in heavily regulated industries like financial services and healthcare.As an alternative, these organizations could use open source models hosted on their own infrastructure, addressing data residency and compliance problems. But are open source AI models g

As modern applications expand across multiple clusters, clouds, and hybrid regions, traditional security mechanisms, such as long lived secrets, static certificates, or cloud provider specific identity and access management, struggle to keep up with the scale, velocity, and ephemeral nature of microservices. Red Hat’s zero trust workload identity manager is designed to resolve this by dynamically issuing temporary, cryptographically attested identities to workloads at runtime. This enables your applications to systematically prove what they are, not just where they run.Zero trust workload id

Navigating the complexities of 5G and AI requires telecommunications service providers to move beyond the restrictive, vendor-locked vertical architectures of the past. Legacy, single-vendor vertical stacks, once the industry standard, have become the primary bottleneck to growth. These rigid architectures lock operators into slow innovation cycles and unsustainable operational expenditure (OpEx). As network complexity explodes at the edge, the traditional model of "one vendor per domain" creates isolated silos that are impossible to automate at scale and too expensive to maintain.To thrive, t

We continue to see many organizations accelerate their infrastructure modernization plans and choose Red Hat OpenShift Virtualization as their future-ready foundation for traditional virtual machine (VM) workloads. That being said, when you’re tasked with moving hundreds or thousands of legacy VMs into a cloud-native environment, speed and security are critical.The latest release of Red Hat’s migration toolkit for virtualization is version 2.12, and is in line with Red Hat OpenShift 4.22. This new release focuses on advanced storage processing, extending source provider support, and AI opt

Red Hat OpenShift 4.22 delivers a platform designed to meet the necessary balance of agility, security, and efficiency for your IT team. This release introduces significant advancements across the board, from hardening zero-trust security and streamlining hybrid cloud virtualization to automating complex cluster operations and providing a robust, production-ready foundation for AI/ML workloads. By shifting the focus from manual management to intelligent, platform-native automation, OpenShift 4.22 empowers organizations to modernize their infrastructure without the operational friction, ensurin

As organizations accelerate AI investments and scale across the hybrid cloud, technology choice only becomes more important. Choice is now a fundamental driver of corporate financial strategy, legal risk mitigation, and long-term asset protection. This means IT infrastructure must do more than just run workloads. It needs to actively protect profit margins and fuel differentiated offerings.Red Hat OpenShift 4.22, now generally available, serves as an engine for IT choice, paired with enhanced security, compliance, and cost control features to keep enterprise environments moving forward. This r

It was 6 AM when the first alert fired. Then the second. Then the third.The on-call engineer opened her laptop to find 3 unrelated failures from a single AI agent. The agent handled support tickets, processed billing adjustments, and answered customer questions. It ran on LangChain. It had passed every test in staging, and it worked—until it didn't.I've watched teams pour months into prompt engineering and model selection only to lose a weekend cleaning up an incident that had nothing to do with either. The failures that follow are not hypothetical. They're the kind of thing that happens the

In our previous post, we walked through the agent mesh for software modernization architecture we built on Red Hat AI for modernizing legacy systems at the scale that mission environments actually require. The post covered the harness pattern, the workflows the harness orchestrates, and the KPI framework for measuring success. It also explained why we run coding agents on Devstral and non-coding agents on Ministral, inside a platform that operates in disconnected environments.This post is about the next layer of that story: the pluggability.In the regulated environments where agent mesh for so

The most recent Red Hat OpenShift release introduces powerful new capabilities for native monitoring, logging, tracing, and dashboarding. Red Hat OpenShift observability has matured into a more seamless ecosystem by merging metrics, logs, traces, and network telemetry into a unified workflow. This integrated approach helps eliminate the common burden of Kubernetes tool sprawl, replacing disconnected dashboards with a hardened, centralized, and fully supported platform.Cluster observability operator 1.5The Cluster Observability operator (COO) functions as a "meta-operator", tasked with deployin

IBM and Red Hat Expand Lightwell with New Offerings to Build the Trust Infrastructure for AI-Era Open SourceDeveloped with leading global financial institutions and backed by a growing partner ecosystem, the new Lightwell offerings help enterprises reduce open source risk without disruptive upgrades. Learn more The new currency of enterprise velocityWith a vast global force of engineers with advanced AI tools, we're delivering the enterprise trust infrastructure for the open source supply chain far beyond our own traditional platform boundaries. It is the largest single commitment to open so

You’ve been asked to adopt AI tools with a promise they will accelerate your time to production and improve the quality of your code. Along the way, you’ve noticed a huge increase in the number of changes submitted to code and you’ve also likely felt the pain of your systems and processes not being able to keep up. The inner loop of development is moving at lightning speed, while the outer loop struggles to keep up. In many CI/CD workflows, a pipeline failure, which is often caused by a security vulnerability or a configuration error, can leave a developer with the manual, time-consuming

At the OpenShift Commons Amsterdam gathering, the premier "Day zero" event for KubeCon + CloudNativeCon Europe 2026, the energy was electric, with a session that perfectly captures the spirit of cloud-native transformation.Joerg Meyer, Software Solution Architect at Diebold Nixdorf, took the stage to deliver a compelling presentation titled, "Diebold Nixdorf Breaks the Shackles of Legacy Payments Infrastructure." Meyer shared how this global leader in banking and retail technology is moving away from the rigid constraints of the past to build a high-availability, future-ready payments platform

For more than 20 years in this industry, the conversation around enterprise software procurement followed a highly predictable script. An organisation would buy a subscription for an open source solution, lock down a certified version, and effectively try never to touch it again unless something broke. Security updates arrived on a slow, linear cadence. That era is officially over.Frontier AI models have fundamentally changed the game in security patching. Automated tools can surface thousands of vulnerabilities across open source software ecosystems in practically no time. Therefore, the secu