We’re thrilled to announce the release of the Kubermatic Kubernetes Platform (KKP) 2.27! This version introduces several exciting features and improvements to elevate your journey with Kubernetes. With Cluster Backup across KKP instances for disaster recovery, AI Kit and support for Kubernetes 1.32, KKP 2.27 ensures you’re up-to-date with the latest advancements. Let’s explore the best improvements of this version.
Highlighted Features
Cluster Backup: Restore to Another KKP Cluster
Disaster recovery and migration just got easier! With KKP 2.27, users can restore cluster backups to a completely different KKP instance. This enhancement enables greater flexibility in handling failures, transitions between environments, or even planned migrations. By decoupling the backup-restore process from a single KKP instance, users gain an additional layer of resilience and operational agility.
Admin Announcement Feature: Seamless Communication Across the Platform
Keeping all users informed is crucial in any Kubernetes environment, and with the new admin announcement feature, KKP administrators can now broadcast important messages directly within the platform. Whether it’s planned maintenance, policy updates, or alerts, this feature ensures that all users are aware of critical information without relying on external communication channels.
AI Kit in KKP: Deploying AI, GenAI, and LLM Workloads at Scale
KKP now includes AI Kit as an application in the App Catalog, enabling seamless deployment of AI, Generative AI (GenAI), and Large Language Model (LLM) workloads in Kubernetes environments. AI Kit simplifies running inference and fine-tuning LLMs and machine learning models with optimized performance for both CPU and GPU-based workloads. With support for multi-modal models, air-gapped environments, OpenAI API compatibility, and Kubernetes-ready configurations, AI Kit allows enterprises to efficiently deploy LLM-based AI applications, chatbots, and fine-tuning workflows in production. Leveraging KKP’s multi-cloud automation and GPU acceleration, users can easily integrate edge AI inference, scalable AI APIs, and secure, high-performance model serving across their clusters. KKP provides a reliable, scalable platform for AI-driven innovation in cloud-native and edge AI environments.
Cluster Autoscaler as an Application: More Flexibility in Scaling
KKP 2.27 shifts the cluster-autoscaler from being an add-on to an application, giving users better flexibility and control over its deployment and lifecycle. By treating the autoscaler as an app, KKP allows for easier updates, customization, and integration with existing application management workflows. This change ensures that clusters can dynamically adjust to workload demands in a more streamlined manner.
Kubernetes 1.32 Support: Keeping Up with the Latest Advancements
Kubermatic Kubernetes Platform (KKP) now fully supports Kubernetes 1.32, ensuring compatibility with the latest upstream improvements, security patches, and performance optimizations. This update provides users with cutting-edge enhancements in scalability and reliability while maintaining seamless operations across cloud and on-prem environments. With this upgrade, KKP continues to offer enterprise-grade Kubernetes management with minimal friction when adopting new versions.
Other Valuable Features
KubeVirt Improvements: Better Virtualization Experience
KKP 2.27 introduces a series of KubeVirt improvements, further solidifying its support for running virtual machines alongside containers. These enhancements include better UI integration, performance optimizations, and refined network handling, making KubeVirt a more reliable solution for hybrid workloads within Kubernetes clusters.
RHEL 9 Support: Expanding Compatibility
KKP 2.27 adds support for Red Hat Enterprise Linux 9 (RHEL 9), enabling users to deploy clusters on the latest enterprise-grade Linux distribution. This ensures compatibility with modern workloads and security standards while allowing organizations to take advantage of RHEL’s stability and support. Furthermore, in alignment with the industry-wide shift, CentOS support has been removed from KKP.
Applications improvements
Default Namespace for Applications
To enhance consistency and streamline application deployment, KKP now supports default namespaces for applications. This improvement allows users to define a standard namespace when installing applications, reducing the risk of misconfigurations and improving overall cluster hygiene. To learn more about namespaces, visit our previous blog.
Pre-Defined KKP Variables in Applications
Users can now leverage pre-defined KKP variables within applications, simplifying configuration management and ensuring dynamic values are applied without manual intervention. This enhancement reduces human error and makes it easier to standardize application deployments across multiple clusters.
Application Versions Refreshed
In KKP 2.27, the default App Catalog has been refreshed with the latest versions of its applications. This update ensures that users have access to the most recent features and security patches when deploying applications from the catalog. While this enhancement improves the baseline for new deployments, users are encouraged to review and manage application versions to maintain optimal performance and security within their clusters.
ArgoCD-Based KKP Apps Helm Chart (Alpha)
KKP 2.27 introduces an initial ArgoCD-based Helm chart for managing KKP applications, providing a GitOps-friendly approach to application lifecycle management. This allows users to leverage ArgoCD’s declarative model to maintain consistency and control across their Kubernetes applications.
Platform Administration Improvements
Display Only Admin-Allowed OS in Project Add/Edit Dialog
For enhanced control, KKP now ensures that only administrator-approved operating systems are displayed when adding or editing projects. This prevents unauthorized OS choices and enforces compliance with internal policies.
Seed CR: Default Image ID Specification
KKP now allows users to optionally specify a default image ID in the Seed Custom Resource (CR), providing greater control over how nodes are provisioned within clusters. This feature simplifies cluster setup and ensures consistent image usage across deployments.
Secure UserCluster NodePorts by Default
To bolster security, KKP gives the option to override the default setting (0.0.0.0/0), by setting NodePortsAllowedIPRanges on the OpenStack datacenter level. This change minimizes potential attack vectors by enforcing strict access controls while maintaining flexibility for administrators to fine-tune access policies as needed.
Technical improvements
New Dex Helm Chart for OAuth Authentication
A new Dex Helm chart replaces the previous OAuth chart, improving authentication and identity management capabilities in KKP. This change ensures a more streamlined and secure authentication process for users integrating with external identity providers.
API Server Service Type Configuration
KKP now allows users to configure the API server service type, offering greater control over networking and accessibility. This feature provides more flexibility when deploying clusters in different environments, improving the overall deployment experience.
We’re excited to see how these features will empower your Kubernetes operations and look forward to accompanying you on your cloud-native journey. Stay tuned for future updates and don’t hesitate to reach out with any questions or suggestions via Contact Us form.
