Red Hat OpenShift 4.21 is now generally available, based on Kubernetes 1.34 and CRI-O 1.34. This release focuses on unifying AI training, containerized microservices, and virtualized applications on a single operational model to reduce costs and eliminate infrastructure silos.
Streamlined training: Data scientists can use a single TrainJob API instead of managing separate machine learning frameworks.
Queue visibility: A new Visibility API for pending workloads provides estimated start times and helps administrators identify resource bottlenecks.
Distributed workloads: The JobSet Operator is now generally available, enabling consistent orchestration of complex, interdependent jobs.
Intelligent GPU allocation: New Dynamic Resource Allocation (DRA) capabilities allow teams to request GPUs by specific attributes (e.g., vRAM size) and define fallback strategies to maximize hardware utilization.
Scaling to zero: Hosted control planes and NodePools can now hibernate during inactivity and resume automatically, eliminating costs for idle infrastructure.
Dynamic right-sizing: Integration with the VerticalPodAutoscaler (VPA) allows control planes to scale based on real-time memory consumption rather than static estimates.
Expanded ecosystem: The release adds support for VMware Cloud Foundation 9, Oracle Database Appliance, and Confidential Containers on Microsoft Azure for high-security, zero-trust workloads.
Zero-downtime migration: Administrators can now move running virtual machines (VMs) between different OpenShift clusters without service interruption.
Cloud flexibility: OpenShift Virtualization on Google Cloud bare metal is now available, providing high performance for latency-sensitive applications.
AI-powered troubleshooting: The Red Hat OpenShift Lightspeed assistant is integrated into the virtualization UI to provide in-context insights for fixing VM errors.
Modern networking: IPv6-only control plane and secondary network support are now generally available to simplify architectures for organizations facing IPv4 address exhaustion.
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