Red Hat’s A100 tests show why a valid Kubernetes device allocation can still be a bad inference allocation—and how cross-driver topology matching can prevent it.

Red Hat’s Critical advisory covers 32 CVEs and publishes new digests for the Developer Hub application, operator and operator bundle.

Red Hat’s UK CIO survey finds near-universal confidence in agent security despite limited data-flow, dependency and vendor-risk visibility.

The release removes workspace recreation from IDE changes while DevWorkspace Operator 1.0 gives administrators new network-policy and reconciliation decisions.

The update removes broad authenticated-user access and makes approval requirements and approver records immutable after task creation.

The public benchmark tests whether coding-agent and model combinations can move applications among Jakarta EE, Quarkus and Spring without losing working behavior.

A proof of concept uses Asago-generated risk scenarios, a permission recommender and repeat evaluation to narrow what retrieval agents can access.

Red Hat’s new integration pattern exposes existing Camel routes to models while keeping tool visibility, arguments and iteration counts under application control.

A public-sector proof of value used synthetic data, a custom rubric and three L40 GPUs to test specialized models against GPT-4.1.

A new engineering guide asks platform teams to test vendor claims against multi-tenancy, GitOps, failover and storage requirements before deployment.

The Korean payments provider says an OpenShift AI platform using vLLM compression, FP8 quantization and a multi-model design cut GPU inference costs by as much as 70%.

A production Quarkus architecture turns Oracle changes into targeted WebSocket and mobile notifications without polling the system of record.

A new architecture guide argues that catalogs, lineage events, policy translation and semantic safeguards must be designed as one agent-data system.

torch-spyre, a vLLM plug-in and hardware-agnostic model layers give IBM’s inference accelerator a path into the open serving stack.

A new engineering guide connects OpenShift AI, TrustyAI and Edge Manager to a selective telemetry and retraining architecture for distributed models.

Ubicloud measured malformed Kimi tool calls on an unconstrained deployment, then reached 100% schema accuracy by enabling vLLM’s new strictness flag.

Red Hat’s enterprise build adds secrets management, automatic corporate CA import and in-app updates, with a destructive cleanup step for some upgrades.

Red Hat’s Developer Preview replaces the connected advisor pipeline with a single deployment on an Advanced Cluster Management hub.

The release adds operator-enforced upgrade checks, a supported EvalHub control plane and production controls for distributed inference.

A Red Hat quickstart separates agent behavior tests from serving, fans benchmark jobs through EvalHub and keeps the resulting evidence in MLflow.

The field build compiles behavioral memory into a versioned profile, but its stale-state and silent conflict handling make governance as important as token savings.

A GB300 NVL72 study shows that expert placement and host-side scheduling matter as much as kernels when decode steps become short.

Six days remain as of October 24 before the hosted deployment retires; Red Hat points organizations needing an on-premises option to Satellite documentation.

A runnable incident assistant shows how Camel 4.22 can expose vector retrieval and live web search as bounded tools for a local model.

OpenShift sandboxed containers 1.13 moves GPU-backed confidential AI to GA while a new Agent Sandbox preview isolates code that autonomous agents generate.

A new IBM lab blueprint joins DCGM workload signals, cloud cost data and alerts-as-code so platform teams can separate useful accelerator work from paid-for idle capacity.

Red Hat and vLLM engineers combine token-parallel prefill, sharded KV cache and host-memory decode to fit contexts that standard parallelism cannot hold.

MiniMax-M3.1-Flash arrives with sparse-attention, MoE and speculative-decoding paths for NVIDIA and AMD accelerators, plus reproducible recipes.

Red Hat’s OpenShift walkthrough separates browser login from server-side token introspection and documents the operator-era replacement for legacy SSO.

An OpenShift pattern combines gateway isolation, network policy, identity-aware tool permissions and rate limits instead of treating authentication as sufficient.

Red Hat’s walkthrough shows how to trade Keycloak’s SSO layer for direct directory binding—and where TLS becomes non-negotiable.

RHEL CoreOS 10 is a Technology Preview in OpenShift 4.22; Red Hat’s planned mixed-stream model would let administrators validate and move nodes gradually.

The clinical-simulation project joins OpenShift orchestration, IBM Fusion storage and NVIDIA inference in a permission-aware, on-premises architecture.

The release gives Kubernetes operators explicit control over pod metadata, adds standards-based OCSF export and hardens failure paths around sandbox policy enforcement.

A new engineering guide joins Podman, Red Hat AI Inference, GuideLLM and Open WebUI into a repeatable local evaluation loop.

A four-stage method moves OpenShift chaos testing from one-off pod failures to measurable workflows that teams can replay before releases and infrastructure changes.

The reference deployment lets an agent inspect current Azure resource state through MCP while OPA, read-only credentials and audit logs constrain its reach.

Red Hat and NEC built a shared inventory and validation framework for more than 200 certificate-related artifacts across the platform.

The open-source plug-in captures and edits model internals during CUDA Graph replay, avoiding the eager-mode penalty that keeps many safety tools out of production.

Red Hat’s new benchmark replaces Python-heavy toy problems with reproducible Go, Python and C tasks drawn from Podman, etcd, Ansible, KubeVirt and related projects.

The first beta moves the Java baseline, networking stack, serialization layer and persistence defaults at once, making early testing more than a compatibility exercise.

A production case study shows how queue-aware and prefix-cache-aware routing can turn idle accelerator capacity into predictable training-data output.

The new open-source library separates quantization descriptions from GPU execution choices, then compiles a tuned kernel for each workload.

A first-party reference design joins simulation, evaluation, signed OCI artifacts and fleet delivery on one AI workstation.

A troubleshooting-assistant design replaces flat fan-out with layered orchestrators, trading additional model calls for narrower routing decisions and contained failures.

Red Hat’s two-site OpenShift lab preserved OIDC sessions during site failure, but the Keycloak 26.7 stateless work remains a preview that operators must validate.

Red Hat says moving back to 26.4 can fail after Kubernetes records v2beta1 as a stored version, so operators need a tested rollback path before upgrading.

The validated architecture joins IBM’s sovereignty control plane and integrated infrastructure on Red Hat OpenShift, targeting regulated enterprises and service providers.

Clusters moving from a 4.21 multi-architecture payload should verify the payload type and avoid the affected 4.22.15–4.22.17 targets; the Machine Config Operator fix is present from 4.22.18 onward.

The partners say they will validate new MiniMax serving paths before weights arrive, then feed production lessons back into upstream vLLM.