Managed Service for Kubernetes®
This service provides a streamlined Kubernetes deployment and management experience.
Count on scalability, strong security features and automated updates to simplify the deployment and management of Kubernetes clusters.
Easy maintenance
You create a cluster and node groups, and we take care of maintaining and updating all cluster infrastructure components. Manage clusters using the kubectl command line, or use Helm, Draft, or Brigade to automate application delivery.
Kubernetes Marketplace
Coming soon! Save time and effortlessly integrate ready-made solutions and tools tailored for Kubernetes from our Marketplace: Argo CD, H2O, GPU Operator, Network Operator, CUDA, Jupiter Notebook, TensorFlow.
Identity and Access Management integration
Connect users to Kubernetes clusters using your company’s accounts, without creating multiple configuration files for employee access.
ML/AI cycle use cases where this service is essential
Data processing
Kubernetes, an open-source container orchestration platform, streamlines modern data workflows by integrating with various tools. It offers a flexible, scalable infrastructure suitable for big data, machine learning, and real-time processing. Kubernetes simplifies the deployment and management of data processing tools like Apache Spark, Kafka, and Airflow, optimizing resource use and ensuring high availability. Its native features for autoscaling and updates handle dynamic data volumes, enhancing operational efficiency.
This combination empowers organizations to gain data-driven insights, reduce complexity, and make confident data-informed decisions.
AI model training
Kubernetes stands at the forefront of AI model training, offering scalability and efficiency through open-source tools. By combining frameworks like TensorFlow, PyTorch and Horovod with K8s and orchestration tools like Kubeflow and Airflow, organizations can seamlessly distribute workloads, dynamically allocate resources, and achieve cost-effective AI model training, while focusing on developing AI models rather than the intricacies of infrastructure management.
This powerful combination streamlines the training process, making it an ideal choice for both research and production environments.
AI model inference
Kubernetes, a versatile container orchestration platform, extends its prowess to machine learning model inference. It provides an optimal environment for deploying and managing ML models through open-source integration with TensorFlow Serving, Triton Inference Server, or ONNX Runtime. Kubernetes ensures high availability and scalability, thanks to auto-scaling and load balancing features, improving resource utilization and cost-efficiency. It also offers robust networking solutions for secure model endpoint traffic routing.
Combining open-source tools with Kubernetes streamlines ML model deployment and management, accelerating AI-driven application development.
We take care of almost all stages of the Kubernetes® cluster maintenance
Managed by you
Managed by Nebius
Intuitive cloud console for a smooth user experience
Intuitive cloud console for a smooth user experience
Сreate a Kubernetes® cluster, add a group of nodes to it, and manage them using kubectl.
Questions and answers about Managed Kubernetes
What is the advantage of using a managed service?
What is the advantage of using a managed service?
Managed Service for Kubernetes® fully manages the master node and provides tools for node diagnostics and their recovery.
What Kubernetes® versions are available in Nebius?
What Kubernetes® versions are available in Nebius?
How do I update my Kubernetes® version?
How do I update my Kubernetes® version?
Start your journey
More to know
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