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Kubernetes Engine

STACKIT Kubernetes Engine (SKE) is a robust, scalable, and managed Kubernetes service. SKE supplies a CNCF-compliant Kubernetes cluster, and makes it easy to provide standard Kubernetes applications and containerized workloads.

Features

STACKIT Kubernetes Engine offers a range of features to simplify application development and deployment:

  • Self-service cluster creation (Portal): Create Kubernetes clusters quickly and easily via the self-service user interface in the STACKIT Cloud Portal.
  • Infrastructure as code & automation: Provision and manage clusters using the Terraform provider, SKE API, or STACKIT CLI for repeatable automated workflows.
  • Managed control plane: The Control Plane of the clusters is managed and highly available.
  • Auto-updates: Kubernetes and operating system versions are automatically updated to keep clusters up to date.
  • Automatic repair functions: Detect and repair problems on the cluster automatically.
  • Event-driven autoscaling: Pod and node autoscaling elastically adjust clusters based on workload.
  • Temporary cluster shutdown: Clusters can be automatically switched off if the application is only to be accessible at certain times of the day.

Use cases

Popular use cases for STACKIT Kubernetes Engine are the following:

  • Migration of existing applications: Quickly and easily containerize existing applications and run them on SKE in the European cloud without worrying about the underlying infrastructure.
  • Operation of cloud-native applications: Create new cloud-native applications in the form of microservices, utilizing the Kubernetes ecosystem for service meshes, serverless applications, and CI/CD pipelines.
  • Creation of stateful applications: Operate stateful applications on SKE clusters using persistent block storage.
  • Development and testing environments: Set up isolated environments for development and testing to ensure consistency and reliability across different stages of application deployment.
  • Scalable web applications: Deploy web applications that can automatically scale based on demand, ensuring high availability and performance.
  • Machine learning workloads: Run machine learning models and data processing tasks efficiently using Kubernetes orchestration and resource management.
  • announcement

    API Update: Cluster status includes Kubernetes & node pool version expiry dates

    Section titled “API Update: Cluster status includes Kubernetes & node pool version expiry dates”

    We have updated the STACKIT Kubernetes Engine (SKE) API to provide better visibility into your cluster’s lifecycle.

    When interacting with the “get a cluster”, “list all clusters”, or “create or update a cluster” endpoints, the API response now includes the expiry date of the currently used Kubernetes and node pool versions, but only if an expiration date exists for that specific version.

    This enhancement makes it easier to automate lifecycle monitoring and plan your manual updates well before a version reaches its expired state and triggers a mandatory update.

    For more details on how SKE handles version lifecycles and expiration, see our Version updates documentation.

  • announcement

    Access your clusters using your STACKIT IDP users

    Section titled “Access your clusters using your STACKIT IDP users”

    We would like to inform you that STACKIT Kubernetes Engine (SKE) now supports accessing your clusters with user and service accounts managed in the STACKIT IDP. This simplifies granting fine-grained permissions to individual users.

    Refer to our documentation for instructions on how to enable and use the feature.

    Our Help Center is always at your disposal if you have any questions.

  • deprecated

    Kubernetes version 1.32 is getting deprecated in SKE

    Section titled “Kubernetes version 1.32 is getting deprecated in SKE”

    Kubernetes version 1.32 reaches the end of its official maintenance support on 28 February 2026.

    This version will be removed from SKE on 15 April 2026 at 8 AM UTC. Starting with the date of removal, all clusters that are still using 1.32 will be automatically upgraded to 1.33 during the cluster’s maintenance time window.

    For detailed information, refer to:

    Our Help Center is always at your disposal if you have any questions.