We are excited to highlight the new updates and improvements in the Red Hat OpenShift 4.18 release for developers. We will describe the new features, improvements, and fixes and changes to the previous version. OpenShift is based on Kubernetes 1.31 and CRI-O 1.31 releases. You can find all the information you need and more in the release notes and Red Hat OpenShift 4.18: What You Need to Know.
The developer experience improved
The following updates in OpenShift 4.18 boost the developer experience:
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With the Developer Perspective in OpenShift Console, you can now add color to Tekton Pipelines logs for PipelineRun and TaskRun logs, making the logs easier to view.
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Import YAML from OpenShift Lightspeed into the OpenShift UI Editor with a single click.
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In addition, dark and light mode support has been added to the YAML Editor.
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The Knative Event catalog is now available to discover different event types.
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You can create an AI ChatBot in OpenShift with the new AI Sample deployed via Helm. It comes with a full continuous integration and continuous delivery (CI/CD) pipeline and runs on clusters without a GPU.
Cluster updates
Red Hat OpenShift Dev Spaces 3.17, based on Eclipse Che 7.92, adds an option to deploy operands (such as gateway and dashboard) managed by the operator on specific cluster nodes using the dedicated nodeSelector and tolerations properties. Specify the list of allowed sources based on which Cloud Development Environments (CDEs) started using the dedicated optional parameter, allowedSources. You can also assign endpoint annotations in the devfile.
Use the maxNumberOfRunningWorkspacesPerCluster CheCluster CR property to restrict the total number of ‘Running’ workspaces on a cluster.
Release 3.18, based on Eclipse Che 7.95, adds the ability to configure two Gitlab OAuth providers on a single Dev Spaces instance. This helps developers working with codebases hosted on GitLab in the cloud and on-premises. Create or import the gitconfig file from the User Dashboard no matter what authentication method used on the cluster. Please see the release notes to discover all of these updates.
The OpenShift Toolkit IDE extension by Red Hat for VS Code and IntelliJ 1.17.0 makes it easier to configure the Developer Sandbox in a single click. Select the devfile version to add to the Devfile Registry editor. The Helm UI page is included with tag-based filtering. Quarkus Tools & EAP for VS Code and IntelliJ 1.20.0 adds support for four areas: global namespace, multiple Qte template roots, data model template matcher, and Roq DataMapping.
Podman Desktop 1.15 with the BootC extension 1.6 has added support for events on resources (services, pods, and nodes) to keep track of what is happening in a cluster. In addition, it has a revamped task manager for testing and lets you connect directly to your Podman machine via Podman Desktop with SSH access. It also converts a standard container image to a fully bootable operating system (OS) on a USB stick with bootc. To learn more, refer to the Podman Desktop release notes.
Red Hat Developer Hub new features
Red Hat Developer Hub, based on the Backstage project, provides software templates and plugins for OpenShift deployments, access to pipeline runs, viewing clusters from OCM, and more.
Red Hat Developer Hub 1.4, based on Backstage project 1.32.6, has added support for OpenShift Dedicated, added middleware functions to the RootHttpRouter, and support for the installation on GKE (in addition to OpenShift, AKS, and EKS).
There is now a Notification plugin, support for OpenTelemetry to monitor your environment, and an example AI template for OpenShift. The Red Hat Developer Hub is integrated with the Red Hat build of Quarkus 3.15 making it easier to create new Quarkus applications.
For an in-depth review of all of the latest features, including updates for plug-ins and templates, refer to What’s new in Red Hat Developer Hub 1.4.
Red Hat OpenShift Virtualization Engine
Red Hat OpenShift Virtualization Engine is an edition of Red Hat OpenShift made for hosting and running virtual machines. It is optimized for bare metal operating in a limited space and supports 128 cores per bare-metal socket pair. Check out Getting Started with OpenShift Virtualization, Red Hat OpenShift Virtualization Engine to learn more.
New OpenShift Pipelines features
OpenShift Pipelines is a cloud-native continuous integration and continuous delivery (CI/CD) solution based on Kubernetes. It automates deployments using Tekton building blocks across multiple platforms by removing the hidden implementation details. OpenShift Pipelines provide an integrated user experience with the developer perspective of the Red Hat OpenShift Container Platform web console.
With OpenShift Pipelines release 1.17, you can add multiple configurations from the same Git provider or configure multiple Git providers using the Git resolver in the TektonConfig custom resource (CR). Use the configKey parameter to select a Git configuration for task runs and pipeline runs.
The following new fields are available for the affinityAssistantPodTemplate:
1. securityContext specify how a container should be run.
2. priorityClassName maps priority class names used to concurrently schedule PipelineRun pods to the same node so that TaskRuns can be executed while sharing the same volume.
New Prometheus metrics have been added to track the PipelineRun resources per namespace, pipeline, pipeline run level, and cluster level.
OpenShift GitOps 1.15
OpenShift GitOps 1.15 is based on Argo CD 2.13 and Argo Rollouts 1.7.2. OpenShift GitOps provides a declarative way to implement continuous delivery of applications across clusters and development lifecycles. With release 1.15, multi-source applications is Generally Available (GA). This feature provides access to revision history and rollback to a specific version. The new Sources tab displays all source parameters. In addition, users can now see a resource’s associated rollout in the Argo CD dashboard with the addition of the Argo CD extension. Rollout plugins for traffic managers and metrics are available for use. The isolation of applications has been improved with the decoupling of service account privileges of the control plane and application syncs. More information can be found in the release notes.
Performance boosts in OpenShift Serverless
OpenShift Serverless 1.35 is based on Knative 1.15. OpenShift Serverless provides autoscaling and networking for containerized microservices and functions. Go functions using S2I builder are now Generally Available (GA) for developers to implement and build Go functions on Mac and Linux platforms.
Serverless Logic integrates with Prometheus and Grafana to provide enhanced monitoring support. It also supports configuring the Knative Eventing system to produce and consume events for workflows and supporting services.
Enhancements in autoscaling for Knative Kafka subscriptions with Kubernetes Event Driven Autoscaling (KEDA) is in Technology Preview. Autoscaling with CMA/KEDA optimizes resource allocation for Kafka triggers and KafkaSource objects and boosts performance in event-driven workloads by enabling dynamic scaling of Kafka consumer resources. To learn more, please refer to the OpenShift Serverless 1.35 release notes.
OpenShift Service Mesh 3.0 upgrades
Red Hat OpenShift Service Mesh 3.0 is based on Istio 1.24 and Kiali 2.1. OpenShift Service Mesh creates a central point of control in an application. OpenShift Service Mesh 3.0 will be generally available shortly after the OpenShift 4.18 release. It is managed by the Sail operator based on Istio.
New features include:
- Support for Canary control plane upgrades which is safer for in-place upgrades
- Multi-cluster topologies
- Availability of Istioctl, Istio’s command line utility.
More information can be found in these release notes.
Enhanced observability
Red Hat OpenShift Observability provides real-time visibility, monitoring, and analysis. It analyzes system metrics, logs, traces, and events to diagnose issues and troubleshoot before they impact systems or applications. The Cluster Observability Operator (COO) release 1.0.0 (based on Konflux) is now GA.
COO is needed to use the observability UI plugins for visualization capabilities, including the dashboard UI, troubleshooting UI, Distributed Tracing UI, Logging UI, and Monitoring UI. COO is also needed to use the analytics features, like observability signal correlation for traces. With COO, you can create standalone monitoring stacks that are independent of the default in-cluster monitoring.
To read more about the new Cluster Observability Operator, please see the following articles: Get started with the OpenShift Cluster Observability Operator, Brief overview of Cluster Observability Operator, and Step-by-step guide to configuring alerts in Cluster Observability Operator.
Red Hat build of OpenTelemetry based on OpenTelemetry unifies, standardizes, and delivers vendor-neutral telemetry data collection for cloud-native software. The Red Hat build of OpenTelemetry 3.5 based on the OpenTelemetry operator adds the ability to export OpenShift Monitoring metrics, like Kubestats and Hostmetrics, via the OpenTelemetry Protocol (OTLP) and automated role-based access control for OpenTelemtry components.
The Red Hat OpenShift distributed tracing platform 3.5 (based on the open source Grafana Tempo) adds fine grained role-based access Control (RBAC) for stored tracing data providing more granularity for access, support for IBM Cloud Object Storage in Tempo, and Tempo monolithic memory handling improvements.
Discover more new features in the product documentation.
Ready to try Red Hat OpenShift?
To discover more about Red Hat OpenShift 4.18, check out the list of all the new features and fixes:
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