Red Hat OpenShift 4.22 tackles cloud costs, AI workloads

Red Hat released OpenShift 4.22, a hybrid cloud platform update that reduces cloud costs, secures AI workloads with confidential computing, and simplifies virtualized operations. The update introduces confidential AI as a technology preview, a minimal UBI for reduced attack surface, and the JobSet operator for distributed AI training.

Red Hat OpenShift 4.22, an update to the company’s hybrid cloud application platform, is now generally available. The release focuses on cutting cloud infrastructure costs, simplifying operations of virtualized workloads, and securing sensitive data. Announced July 14 https://www.redhat.com/en/blog/navigate-ai-and-scale-red-hat-openshift-422 , Red Hat OpenShift 4.22 continues to harden the platform foundation to meet growing security standards, helping reduce the manual effort of compliance and risk mitigation, Red Hat said. The introduction of a minimal Red Hat Universal Base Image UBI strips away non-essential packages to reduce the overall attack surface. With Red Hat OpenShift sandboxed containers 1.12, OpenShift 4.22 makes support for confidential containers on bare metal generally available. The OpenShift 4.22 release also introduces confidential AI as a technology preview. With confidential AI, organizations can isolate and run highly sensitive workloads and proprietary AI algorithms inside a cryptographically isolated slice of memory and CPU, providing data privacy even during runtime execution, according to Red Hat. OpenShift 4.22 also brings new Red Hat OpenShift Virtualization capabilities. A new Ethernet virtual private network integration with user-defined networks allows teams to connect containerized and virtualized workloads to external infrastructure. Volume groups now can be used to execute multi-volume snapshots for VMs, providing a crash-consistent backup mechanism that simplifies disaster recovery. And the introduction of two-node OpenShift with fencing provides a highly resilient and resource-efficient option for constrained edge environments, Red Hat said. In addition, OpenShift 4.22 offers new platform capabilities designed to optimize resource usage and lower operational overhead. The Red Hat build of Karpenter, an open source auto-scaler https://karpenter.sh/ that right-sizes compute instances for Kubernetes clusters, is now generally available for Red Hat OpenShift Service on AWS with hosted control planes. And customers running Red Hat OpenShift Service on AWS with hosted control planes now can integrate AWS EC2 Spot Instances for fault-tolerant workloads to save on costs. Finally, Red Hat OpenShift 4.22 introduces the JobSet operator to streamline large-scale distributed training runs and LLM fine-tuning. This framework coordinates multiple related jobs as a single unit, maximizing the use of expensive GPU compute.