The AI & Cloud-Native Infrastructure Blog

Demystifying Fractional GPUs in Kubernetes: MIG, Time Slicing, and Custom Schedulers

As GPU acceleration becomes central to modern AI/ML workloads, Kubernetes has emerged as the orchestration platform of choice.

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Custom GPU Resource Classes in Kubernetes

In the modern era of containerized machine learning and AI infrastructure, GPUs are a critical and expensive asset.

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What Are AI Agents and How Do They Work?

Artificial Intelligence (AI) has moved far beyond simple chat bots and rigid automation. At the frontier of this evolution lies a powerful new paradigm : AI Agents.

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Configure and Manage GPU Resource Quotas in Multi-Tenant Clouds

In multi-tenant GPU cloud environments, effective resource management is critical to ensure fair usage and prevent contention.

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Enforcing ServiceNow-Based Approvals with Rafay

Enterprises often require explicit approvals before critical actions can proceed especially when provisioning infrastructure or making configuration changes.

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Slash EKS Cluster Costs by 20-30% Instantly with AWS Graviton

If you’re running Kubernetes workloads on Amazon EKS backed by Intel-based instances, you’re leaving significant savings on the table.

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What Is a Sovereign Cloud and Why Does It Matter?

A sovereign cloud is a cloud computing solution that ensures data remains within a country’s borders and complies with local laws.

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Introduction to Slurm-The Backbone of HPC

This is part-1 in a blog series on Slurm. In the first part, we will provide some introductory concepts about Slurm. We are not talking about the fictional soft drink in the world of Futurama.

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Self-Service Slurm Clusters on Kubernetes with Rafay GPU PaaS

Project Slinky and Rafay’s GPU Platform-as-a-Service (PaaS) combined provide enterprises and cloud providers with a transformative combination that enables secure, multi-tenant, self-service access to Slurm-based HPC environments on shared Kubernetes clusters.

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Project Slinky: Bringing Slurm Scheduling to Kubernetes

As high-performance computing (HPC) environments evolve, there’s an increasing demand to bridge the gap between traditional HPC job schedulers and modern cloud-native infrastructure.

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Using Cilium as a Kubernetes Load Balancer: A Powerful Alternative to MetalLB

In Kubernetes, exposing services of type LoadBalancer in on-prem or bare-metal environments typically requires a dedicated “Layer 2” or “BGP-based” software load balancer—such as MetalLB.

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Unlocking Sovereign AI: Rafay’s Role in NVIDIA and Accenture’s Strategic Alliance

In the rapidly evolving landscape of artificial intelligence (AI), nations and enterprises are increasingly prioritizing sovereignty—gaining control over their data, infrastructure, and AI capabilities.

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Accelerating Sovereign AI: Rafay’s Strategic Integration with NVIDIA’s Enterprise AI Factory

In the rapidly evolving landscape of artificial intelligence (AI), enterprises and nations are increasingly prioritizing sovereignty—gaining control over their data, infrastructure, and AI capabilities.

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Cost Management for SageMaker AI: The Case for Strong Administrative Guardrails

Enterprises are increasingly leveraging Amazon SageMaker AI to empower their data science teams with scalable, managed machine learning (ML) infrastructure.

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Simplifying AI Workload Delivery for Platform Teams in 2025

AI workloads are growing more complex by the day, and platform teams are under immense pressure to deliver them at scale—securely, efficiently, and with speed.

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Product

Get Started with BioContainers using Rafay

In this step-by-step guide, the Bioinformatics data scientist will use Rafay’s end user portal to launch a well resourced remote VM and run a series of BioContainers with Docker.

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BioContainers: Streamlining Bioinformatics with the Power of Portability

In today’s fast-paced world of bioinformatics, the constant evolution of tools, dependencies, and operating system environments presents a significant challenge.

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Why GPUs Are Essential for AI Workloads

As artificial intelligence and machine learning continue to evolve, one thing has become clear: not all infrastructure is created equal.

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IaaS vs PaaS vs SaaS: The Cloud Computing Stack Demystified

In today’s cloud-first world, understanding the differences between Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) is essential for IT decision-makers. These three core cloud models form the backbone of digital transformation, each providing unique benefits and levels of abstraction.

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Product

What Is Platform as a Service (PaaS)?

What Is Platform as a Service (PaaS)? Platform as a Service (PaaS) is a cloud computing model, often referred to as the PaaS model, that provides a robust framework for developers to build, test, deploy, and manage applications efficiently.

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Product

What is a GPU PaaS™?

GPU Platform as a Service (GPU PaaS) is a cloud-native model that gives developers and data scientists secure, on-demand access to GPU resources for running AI, GenAI, and ML workloads. Rafay’s GPU PaaS™ stack simplifies GPU delivery across any environment—enabling faster time-to-market and maximum return on GPU investments, allowing you to immediately monetize your GPU (which historically are quite expensive and difficult to access).

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Introducing Serverless Inference: Team Rafay’s Latest Innovation

The GenAI revolution is in full swing, and for NVIDIA Cloud Partners (NCPs), GPU Cloud Providers (aka GPU Clouds), and Sovereign Cloud operators, it presents a significant opportunity. To keep up with market demands, NCPs and GPU Clouds are looking to go beyond simply selling GPUs—they are looking for ways to deliver managed GenAI services to help customers speed up AI adoption, while boosting their operating margins.

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Experience What Composable AI Infrastructure Actually Looks Like — In Just Two Hours

The pressure to deliver on the promise of AI has never been greater. Enterprises must find ways to make effective use of their GPU infrastructure to meet the demands of AI/ML workloads and accelerate time-to-market.

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GPU PaaS™ (Platform-as-a-Service) for AI Inference at the Edge: Revolutionizing Multi-Cluster Environments

Enterprises are turning to AI/ML to solve new problems and simplify their operations, but running AI in the datacenter often compromises performance. Edge inference moves workloads closer to users, enabling low-latency experiences with fewer overheads, but it's traditionally cumbersome to manage GPUs (Graphics Processing Units) in distributed infrastructure.

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Explore the Latest Insights

Featured Blog

Powering GPU Cloud Billing: Rafay + Monetize360 Integration

Demystifying Fractional GPUs in Kubernetes: MIG, Time Slicing, and Custom Schedulers

Custom GPU Resource Classes in Kubernetes

What Are AI Agents and How Do They Work?

Configure and Manage GPU Resource Quotas in Multi-Tenant Clouds

Enforcing ServiceNow-Based Approvals with Rafay

Slash EKS Cluster Costs by 20-30% Instantly with AWS Graviton

What Is a Sovereign Cloud and Why Does It Matter?

Introduction to Slurm-The Backbone of HPC

Self-Service Slurm Clusters on Kubernetes with Rafay GPU PaaS

Project Slinky: Bringing Slurm Scheduling to Kubernetes

Using Cilium as a Kubernetes Load Balancer: A Powerful Alternative to MetalLB

Unlocking Sovereign AI: Rafay’s Role in NVIDIA and Accenture’s Strategic Alliance

Accelerating Sovereign AI: Rafay’s Strategic Integration with NVIDIA’s Enterprise AI Factory

Cost Management for SageMaker AI: The Case for Strong Administrative Guardrails

Simplifying AI Workload Delivery for Platform Teams in 2025

Get Started with BioContainers using Rafay

BioContainers: Streamlining Bioinformatics with the Power of Portability

Why GPUs Are Essential for AI Workloads

IaaS vs PaaS vs SaaS: The Cloud Computing Stack Demystified

What Is Platform as a Service (PaaS)?

What is a GPU PaaS™?

Introducing Serverless Inference: Team Rafay’s Latest Innovation

Experience What Composable AI Infrastructure Actually Looks Like — In Just Two Hours

GPU PaaS™ (Platform-as-a-Service) for AI Inference at the Edge: Revolutionizing Multi-Cluster Environments

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