IBM & Red Hat on AWS

As digital expectations and AI powered decision making accelerate, organizations are modernizing mainframe applications to move faster, operate‑smarter, and fully realize the value of their core platforms. On the modernization journey, we are seeing customers choose a hybrid cloud strategy that offers a single integrated operating model, with common agile practices and interoperability of applications […]

Overview Customers have adopted Red Hat OpenShift Service on AWS (ROSA) due to it being a managed service. This means Red Hat manage OpenShift, ensuring the cluster is available and the customer can focus on what is critical to the business. Though this sounds great it still means the customer is responsible for the application […]

Running large language model (LLM) inference on AWS Inferentia and AWS Trainium chips requires an operator stack that integrates with Red Hat OpenShift. In a previous post, we introduced the AWS Neuron Operator for OpenShift. Since then, the operator has matured through continued collaboration between Red Hat and the AWS Neuron service team. It now […]

AI models produce better results when they operate on current data. This is especially true for agentic AI systems, which are software components that plan, decide, and act on behalf of users. When the underlying data is stale or incomplete, model outputs degrade and downstream actions become unreliable. With IBM‘s recent completion of its acquisition […]

Introduction Organizations across industries are adopting agentic AI to automate complex processes and reduce manual work. Enterprises are moving beyond simple AI assistants and building autonomous agents that plan, coordinate, and carry out complex business processes with minimal human intervention. These workflows span a wide range of use cases — including intelligent automation, real-time decision […]

Organizations are adopting cloud-based development environments to enhance collaboration, standardize workflows, and accelerate innovation. Red Hat OpenShift Dev Spaces provides developers with consistent, secure, containerized workspaces running on OpenShift, reducing the complexity of local environment setup and configuration drift. Meanwhile, Kiro represents a new generation of agentic IDEs that use AI to transform how developers […]

Effective vulnerability management requires fast detection, clear prioritization, and coordinated remediation as IT environments grow in complexity. Security teams need to detect, understand, and remediate issues at scale. Amazon Inspector delivers powerful automated scanning across your AWS workloads, giving you continuous visibility into risks as they emerge. IBM Concert builds on that foundation by helping […]

Organizations run AI workloads from real-time inference to large-scale model training on GPU-backed Amazon Elastic Compute Cloud (Amazon EC2) instances. As these workloads grow, demand on GPU, memory, and CPU resources shifts throughout the day. Keeping instance capacity aligned with this changing demand is key to maintaining application performance and optimizing costs. IBM Turbonomic on […]

Amazon Web Services (AWS) customers managing infrastructure at scale face a common challenge: automation that works today but becomes a liability tomorrow. As your AWS footprint grows, spanning multiple accounts, regions, and services, the automation scripts that once seemed sufficient begin to show cracks. A missing error message here, an inconsistent module behavior there, and suddenly your deployment pipeline […]

Businesses today face increasing complexities in managing modern commerce, driven by the need to provide unified omni-channel experiences, improve operational performance, and consistently exceed customer expectations. To meet these demands, enterprises rely on advanced Order Management Systems (OMS). These systems are essential for orchestrating intricate order lifecycles across diverse sales channels, maintaining accurate and real-time […]