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Empowering Platform Teams: Doing More with Less in the Kubernetes Era

This blog details the specific features of the Rafay Platform Version 4.0 Which Further Simplifies Kubernetes Management and Accelerates Cloud-Native Operations for Enterprises and Cloud Providers

Part 2: Self-Service Fractional GPU Memory with Rafay GPU PaaS

In Part-2, we show how you can provide users the means to select fractional GPU memory.

Self-Service Fractional GPUs with Rafay GPU PaaS

This is Part-1 in a multi-part series on end user, self service access to Fractional GPU based AI/ML resources.

Unlock the Next Step: From Cisco AI PODs to Self-service GPU Clouds with Rafay

Kubernetes v1.34 for Rafay MKS

Users of the Rafay platform can provision new clusters based on Kubernetes v1.34 using the supported interfaces.

Dynamic Resource Allocation for GPU Allocation on Rafay's MKS (Kubernetes 1.34)

Deploy Workload using DRA ResourceClaim in Kubernetes

In this second blog, we installed a Kuberneres v1.34 cluster and deployed an example DRA driver on it with "simulated GPUs". In this blog, we’ll will deploy a few workloads on the DRA enabled Kubernetes cluster to understand how "Resource Claim" and "ResourceClaimTemplates" work.

GPU/Neocloud Billing using Rafay’s Usage Metering APIs

Cloud providers offering GPU or Neo Cloud services need accurate and automated mechanisms to track resource consumption.

Upstream Kubernetes on RHEL 10 using Rafay

Support for Parallel Execution with Rafay's Integrated GitOps Pipeline

Simplifying Day-2 Operations with Agent Pools

What is Agentic AI?

Agentic AI is the next evolution of artificial intelligence—autonomous AI systems composed of multiple AI agents that plan, decide, and execute complex tasks with minimal human intervention.

Deep Dive into nvidia-smi: Monitoring Your NVIDIA GPU with Real Examples

Whether you’re training deep learning models, running simulations, or just curious about your GPU’s performance, nvidia-smi is your go-to command-line tool.

Introduction to Dynamic Resource Allocation (DRA) in Kubernetes

In this post, we’ll look at how a new GA feature in Kubernetes v1.34 — Dynamic Resource Allocation (DRA) — aims to solve these problems and transform GPU scheduling in Kubernetes.

Rethinking GPU Allocation in Kubernetes

Kubernetes has cemented its position as the de-facto standard for orchestrating containerized workloads in the enterprise.

Neocloud Providers: Powering the Next Generation of AI Workloads

Artificial intelligence teams face critical challenges today: Limited GPU availability, orchestration complexity, and escalating costs threaten to slow AI innovation.

GitOps Without Borders: Running Argo CD Across Isolated Security Domains with Rafay’s Zero-Trust Kubectl

In this blog, we will describe how Rafay Zero Trust Kubectl Access Proxy gives Argo CD a secure path to every cluster in the fleet, even when those clusters sit deep behind corporate firewalls.

Drift Prevention vs Detection: Does a Polling Approach make sense At Scale?

Learn about Rafay's approach to drift prevention and detection in this blog.

ArgoCD Reconciliation Explained: How It Works and Why It Matters

ArgoCD is a powerful GitOps controller for Kubernetes, enabling declarative configuration and automated synchronization of workloads.

The Hidden Costs of Running Generative AI Workloads—And How to Optimize Them

Generative AI has revolutionized what’s achievable in modern enterprises—from large language models (LLMs) powering virtual assistants to diffusion models automating complex image generation workflows.

Accelerating AI App Delivery with the Right Infrastructure Orchestration Strategy

AI application delivery is fundamentally more complex than traditional software delivery for cloud-native workloads.

Choosing the Right Fractional GPU Strategy for Cloud Providers

As demand for GPU-accelerated workloads soars across industries, cloud providers are under increasing pressure to offer flexible, cost-efficient, and isolated access to GPUs.

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.

Custom GPU Resource Classes in Kubernetes

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