Managed Kubernetes

Scalable Kubernetes platform for traditional and AI workloads 

Managed Kubernetes
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Overview

Managed Kubernetes platform is designed to support both traditional CPU-based applications and modern AI/ML workloads. With built-in support for GPU acceleration, dynamic scaling, and enterprise-grade automation, you can deploy micro services and AI models on a unified infrastructure.

Seamless integration with popular tools like Kubeflow, MLflow, and TensorFlow enables end-to-end machine learning workflows. Whether you're running APIs, databases, or deep learning models, the platform adapts to your computing needs effortlessly. Get high availability, observability, and security out of the box—so you can focus on innovation, not infrastructure.

Pricing

To know more about the SKUs and pricing click below.

Core Features at a Glance 

AI-Ready Persistent Storage
High-throughput, dynamic storage provisioning for large-scale datasets and model checkpoints, integrated with CSI, NFS, or S3-compatible backends.
AI-Optimised GPU Infrastructure
Optimised GPU infrastructure delivering scalable compute power for modern AI workloads—deep learning, GenAI, and real-time inference.
Integrated AI/ML Workflows
Built-in support for popular AI/ML toolchains including Kubeflow, MLFlow, and TensorFlow. Scalable environments for Jupiter Notebooks and distributed model training.
Container Threat Detection
Managed cloud Kubernetes service with Container Threat Detection as inbuilt service with dashboard.
Scaling
Automatically adjusts the number of pod replicas in a deployment, replica set, or stateful set based on observed metrics. (Horizontal Pod autoscaler - HPA)
Node Auto upgrade
Enables automatic updates of Kubernetes clusters to the latest supported minor and patch versions without manual intervention.

What You Get

Train Faster. Store Smarter
Seamlessly handle large datasets and model artifacts with high-performance, scalable storage that adapts to your AI workload needs—ensuring data availability and faster training cycles.
Built to Train Fast. Built to Think Deep.
Accelerate your AI/ML projects with dedicated, high-performance GPU resources tailored for training deep learning models, running inference, and supporting GenAI workloads at scale.
Integrated Tools for the Entire ML Lifecycle
Jumpstart your AI journey with pre-integrated tools and environments. Simplify experimentation, model lifecycle management, and team collaboration with built-in support for popular ML frameworks.
Detect Fast. Act Faster.
Stay in control with unified observability. Instantly detect and troubleshoot issues using real-time metrics, logs, and alerts—ensuring reliability, performance, and operational efficiency.
Build Fast. Scale Confidently. Operate Effortlessly.
Spend less time managing infrastructure and more time delivering innovation. Enjoy a production-grade, always-on Kubernetes environment without manual upgrades or maintenance.

Still have questions?

AI-Enabled Managed Kubernetes is a fully managed Kubernetes platform that supports both traditional (CPU-based) and AI/ML (GPU-based) workloads. It offers seamless scalability, integrated MLOps tools, GPU acceleration, and observability features—built for enterprises running critical applications and intelligent services.
Unlike standard Kubernetes offerings, this platform is pre-integrated with AI/ML tooling, GPU infrastructure, auto-scaling capabilities, and built-in observability. It supports deep learning, generative AI, and high-performance compute workloads alongside typical cloud-native applications.
Yes. The platform supports mixed workloads efficiently by offering isolated node pools, workload-specific autoscaling, and optimised resource scheduling for both CPU and GPU-based tasks.
GPU-accelerated infrastructure ensures faster training, inference, and real-time processing for compute-intensive workloads like deep learning, LLMs, and generative AI, significantly reducing time-to-insight.
The platform offers real-time visibility into nodes, pods, and utilisation. Integrated logging, alerting, and tracing tools help detect, troubleshoot, and resolve issues quickly.

Resources

Deploy and manage containerised applications at scale with Kubernetes.
Video
Deploy and manage containerised applications at scale with Kubernetes.
Fully managed Kubernetes for secure, scalable container orchestration.
Brochure
Fully managed Kubernetes for secure, scalable container orchestration.

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