A new engineering guide traces false-positive and flaky tests to route structure, serialization, timing and infrastructure startup—not just test code.
The guidance connects admission-webhook conflicts, rootless Podman SCCs, GitOps configuration, capacity monitoring and five disconnected dependencies.
The hands-on workflow takes teams from a containerized OpenAI-compatible endpoint through concurrency tests and a local chat interface before they scale out.
The new guidance separates fixed-capacity deployments from demand-driven scaling and points operators toward service-level inference metrics rather than GPU utilization.
The guidance covers centralized SCM authentication, private extension registries, certificate trust and restricted-network IDE workflows.
A concrete device-plugin pattern turns mainframe cryptographic hardware into a schedulable OpenShift resource, with explicit limits around host setup and pod privilege.
Red Hat’s walkthrough uses the same bootc image for disposable checks, persistent libvirt development and qcow2 disk output.
The project’s new recipes belong after dependency and template updates, while larger migrations such as MUI-to-BUI remain deliberate, review-heavy work.
The PeopleMesh quickstart combines Docling, Granite, pgvector and Keycloak, while exposing the design choices behind structured extraction and semantic reranking.
A joint engineering guide puts Confluent for Kubernetes, hosted control planes and OpenShift security controls into one event-streaming pattern.
The practical work is familiar—security policies, release documentation, MFA and protected branches—but the legal responsibility stays downstream.
The validated design separates Cloudera Base VMs from containerized Data Services and gives platform teams a concrete, versioned sizing baseline.
A new field guide turns production lessons from OpenShift 4.20 and Dev Spaces 3.26 into a multi-tenant design for isolation, chargeback and etcd health.
The Red Hat Summit build joined Lightspeed, Satellite and RHEL behind one client, then hit model accuracy, token-capacity and cost limits.
Red Hat’s lab shows how an HTB hierarchy can protect production traffic without wasting idle bandwidth, while a declarative OVN-Kubernetes API remains in development.
Red Hat’s worked example pairs a smaller distroless runtime with signed builds, SBOMs and automated daily redeployment—but teams still need to test each rebuilt artifact.
Red Hat’s new hands-on path turns prompt-injection testing into a repeatable OpenShift AI workflow, but the first scan is a baseline rather than a safety certificate.
The command-line tool and library wrap Pack, choose Podman or Docker, run the resulting image and expose cleanup controls to test code.
Red Hat’s Emerging Technologies team packages vLLM serving, Podman and a repeatable cpueval workflow into an x86 evaluation pattern.
IBM’s walkthrough turns a ppc64le ASP.NET Core image into a user-scoped systemd service, but persistence, boot behavior and single-host limits remain platform decisions.
Red Hat combines HyperShift, OpenShift Virtualization, Advanced Cluster Management and Argo CD ApplicationSets into a cluster-as-a-service workflow.
A new engineering guide separates cloud-side model preparation from edge inference and treats model packaging, validation and signing as a software supply-chain problem.
Red Hat’s new workflow turns zero trust from a perimeter slogan into an inventory, policy and event-response discipline.
Red Hat’s example keeps LangGraph in charge of reasoning and tools while moving input, output and topic policy into a TrustyAI-managed service.
Red Hat’s runtime trace shows why a capability accepted by an SCC and requested in a PodSpec may still disappear when the container process changes UID.
A reproducible Podman run starts by proving host drivers, rootless device access, endpoint health and workload comparability—not by collecting a headline throughput number.
Red Hat build of Kueue 1.4 maps device classes to queue quotas and can account for partitioned GPUs by memory rather than raw device count.
The Open Data Hub library combines kubeconfig, service accounts, OIDC and OpenShift OAuth while retaining strict TLS and standard Kubernetes clients.
Eight MI300X GPUs exposed 64 schedulable SR-IOV virtual functions, while Red Hat documented performance, topology and production-support boundaries.
A Red Hat Developer workflow turns ephemeral trigger checks into durable positive, near-miss and negative tests that can graduate into a blocking CI gate.
The new Quarkiverse extension packages decades-old Java desktop APIs for Quarkus dev mode and GraalVM native executables across three operating systems.
Operators must stop the fleet, preserve data and encryption material, migrate schema and credentials, then recreate sandboxes before validating clients and extensions.
The reference application spans custom YOLOv8 training, CPU or GPU model serving, video tracking, event storage and tightly scoped natural-language analysis.
Red Hat’s walkthrough turns one prompt-injection probe into reproducible evidence while showing why a pass/fail label needs context.
Red Hat’s two-phase test shows what Kubeflow Trainer v2 automates—and when teams still need the lower-level JobSet API.
The new guide isolates host, container and workload variables, but its local single-node design is a baseline—not a production result.
The new reference repository offers four ready-to-try document-conversion patterns and clearly quarantines four more that still need cluster validation.
A Red Hat AI Americas reference build connects distributed fine-tuning, MLflow tracking, shared storage and vLLM serving around a strict banking-intent task.
A Red Hat engineering demo shows why teams should rank imbalanced classifiers by business loss before scaling the workflow with OpenShift AI AutoML.
Red Hat’s JWS 7 upgrade guide separates the relatively small Jakarta EE 11 move from the runtime, request-parsing and container changes that can break existing deployments.
The OpenShift AI guide shows where extraction, deterministic calculations, evidence trails and human escalation fit—and where the demo stops short of production.
The reference build connects cluster sizing, GPU enablement, model serving, MaaS, storage, pipelines and shared GPU queues—and makes its lab assumptions visible.
A worked example turns a Backstage template into a self-service route through GitHub, Tekton, Argo CD, Quay and OpenShift.
A new practitioner guide separates the common services, RHEL fleet controls and OpenShift cluster controls needed to run distributed edge estates.
A Fedora Rawhide walkthrough combines dm-verity, TPM2-sealed dm-crypt and a writable overlay, while documenting the integrity gaps that remain.
A new playbook moves teams from containerization through operational maturity, modernization and optimization—with different workloads allowed to advance at different speeds.
Red Hat’s walkthrough shows how teams can reproduce OpenShift-style Java image assembly locally, inspect it and carry configuration forward.
Edwin AI supplies incident context and playbook recommendations; Ansible keeps credentials, policy, approvals and audit around the resulting action.
The blueprint grounds Developer Lightspeed in MTA rules while MTV and Ansible handle infrastructure migration, but teams still own validation and rollout design.
Red Hat directs affected organizations to move analytics into Satellite, where host data stays local but the Compliance service is not available.