Cloud Native AI Infrastructure Solutions — Built for
Flexibility and Scale

The simple and frictionless way to deploy AI/ML workloads, anywhere you need them: Cloud, On-Prem, Hybrid or Edge.


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CUSTOMER SPOTLIGHT

Nebul: The European Sovereign AI Cloud

Discover how leading European private and sovereign AI cloud provider Nebul uses Mirantis k0rdent AI to run AI inference workloads on demand.

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Open source, Kubernetes-native platform engineering

Mirantis k0rdent AI is an enterprise-grade AI lifecycle management solution that accelerates the delivery of AI-powered applications into production at scale.

By streamlining the development and deployment of AI applications and machine learning models, Mirantis k0rdent AI reduces toil for application developers and data scientists, so they can focus on delivering continuous value.


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What customers are saying…

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Using k0rdent enables us to effectively unify our diverse infrastructure across OpenStack, bare metal Kubernetes, while sunsetting the VMware technology stack and fully transforming to open source to streamline operations and accelerate our shift to Inference-as-a-Service for enterprise customers.

— Arnold Juffer, CEO and founder


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AI Infrastructure: Scale Workload Clusters with Security and Control

Keep your AI inference workload clusters secure, compliant, and under control with Mirantis k0rdent AI.

Streamline platform engineering at scale across any infrastructure

Maintain clusters globally with policy enforcement, self-healing capabilities, observability, and automated upgrades

Automate data sovereignty with smart routing technology

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k0rdent: Helping Platform Engineers Meet Modern Infrastructure Challenge

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MLOps Infrastructure: Accelerate the Delivery of AI-Powered Applications

Reduce time to market for AI-powered applications at scale with Mirantis k0rdent AI.

Build composable developer platforms tailored to the unique needs of your ML and dev teams and product use cases

Remove bottlenecks in the MLOps lifecycle with self-service provisioning of Kubernetes clusters across any infrastructure

Rapidly integrate complementary services and AI pipeline components using validated integration templates from a broad ecosystem of open source and proprietary technologies

MORE OFFERINGS
FROM MIRANTIS

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Mirantis
Kubernetes Engine


Drive business-critical AI/ML innovation to run NVIDIA GPU nodes with secure, scalable, and reliable container orchestration.


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Features:

Ease of Optimization: Fully composable architecture to finetune components for the highest levels of security, stability, and performance

Security: Deploy swiftly out of the box with enterprise-grade, FIPS-validated default components or swap in alternatives

Automation: Streamline operations with automation built throughout the stack, using standardized API interfaces and GitOps-based lifecycle management

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Mirantis
Container Runtime


Efficiently execute workflows throughout the MLOps lifecycle with a secure, scalable, and performant container engine.


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Features:

Security: Built-in support for FIPS and Docker Content Trust ensures data and model integrity

Performance: Lightweight and high-performance runtime with GPU support

Reproducibility: Consistent environments for training, optimization, and deployment

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Open source k0s is a minimal Kubernetes distribution that’s perfect for securely running AI inference workloads on any device.


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Features:

Lightweight & Minimal Overhead: Run AI inference workloads close to data sources, even on highly resource-constrained devices

Scalability: Deploy and run AI inference workloads reliably at any scale

GPU Support: Integrate NVIDIA GPU Operator to enable provisioning of GPU resources

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LENS


Accelerate the development of AI-powered cloud native applications with the world’s most popular Kubernetes IDE


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Features:

Developer Efficiency: Make the developer experience great using a powerful Kubernetes IDE with a beautiful UI

Reduce Toil: Developers save tons of time with an easy way to visualize, troubleshoot, and control clusters

Easy to Learn: Accelerate developer onboarding and increase Kubernetes adoption with an intuitive tool everyone can use

LIFECYCLE SOLUTIONS
FOR YOUR AI INFERENCING
PLATFORM

Mirantis Services accelerates time to production for your enterprise
AI initiative by working with you to create a comprehensive solution
tailored to your use cases and workloads.

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FAQ

Q:

What is AI infrastructure?

A:

AI infrastructure is made up of hardware and software components needed to develop, train, deploy, and manage AI models effectively. This includes compute resources like CPUs, GPUs, and other accelerators, as well as storage systems, networking equipment, GPU operators, and specialized software frameworks. These resources can be deployed across public clouds, on-premises data centers, bare metal servers, hybrid environments, or at the edge. All of these elements work together to handle the intensive computational and data processing demands of AI workloads.


Q:

What is an AI infrastructure solution?

A:

An AI infrastructure solution integrates compute, storage, networking, and other components to support one or more phases of the AI lifecycle. It typically provides environments for data ingestion, preprocessing, model training, evaluation, and/or deployment. AI infrastructure solutions are designed to streamline AI operations to aid scalability, efficiency, and ease of management. Enterprise-grade AI infrastructure solutions provide secure, scalable, production-ready offerings for enterprise deployments, complete with enterprise support and choice of services.


Q:

What are the key features of an AI and Machine Learning infrastructure solution?

A:

There are several key features of an AI and Machine Learning infrastructure solution.

  • Scalability: Supports large-scale deployments of AI applications, LLM and ML models across hundreds or thousands of clusters with centralized control.

  • Data Pipeline Management: Tools for ETL, data versioning, and real-time data feeds

  • Networking: Fast and low-latency networking across multi-cluster environments

  • ML Framework Integration: Seamless support for popular ML frameworks like TensorFlow, PyTorch, Keras, etc.

  • Orchestration and Resource Management: Managing workloads, scheduling jobs, and allocating resources efficiently

  • Monitoring and Observability: Real-time monitoring of model performance, hardware utilization, and errors

  • Security and Compliance: Encryption at rest and in transit, access controls, and adherence to industry standards

Q:

How will this solution speed up AI inference or deployment?

A:

Implementing an AI infrastructure solution can significantly speed up AI inference and deployment. By leveraging optimized hardware accelerators and streamlined data pipelines, these solutions reduce latency and increase throughput. This efficiency is crucial for applications requiring real-time or near-real-time responses. Additionally, automated provisioning of environments saves time by eliminating the need for manual intervention, further accelerating AI inference and deployment.


Q:

Why is AI infrastructure important?

A:

AI infrastructure is important because it is the foundation for AI initiatives. A robust infrastructure ensures that AI models operate efficiently and can scale as needed. AI infrastructure supports the complex computations and large-scale data processing that AI applications demand.

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Contact us to learn how Mirantis can accelerate your AI/ML innovation.

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