Blog

Our July’s digest describes how our customers like Stanford and Shopify use flexible compute capacities and the steps we are taking to boost performance. Nebius’ first anniversary also took place in July, marked by Nasdaq in Times Square, and there was news from across the ocean as well.

Slurm Workload Manager is a cornerstone of high-performance computing (HPC) infrastructure, trusted by supercomputing centers worldwide for its scalability and flexibility. As AI workloads grow in size and complexity, Slurm is gaining traction among ML teams as well. In this article, we will look at why it remains relevant, how it supports GPU clusters and what to consider when using it in AI workflows.

Skip the CLI commands and web console clicks — just ask Claude about your cloud infrastructure. Today, we’re excited to announce the Nebius MCP Server, our integration that connects Claude by Anthropic, or other AI chatbots, to the Nebius AI Cloud infrastructure.

Welcome back to our quarterly roundup featuring all the improvements and updates delivered on Nebius AI Cloud over the past three months. This overview highlights the key developments we’ve made to enhance your AI infrastructure experience.

To go from prototype to production, AI agents need more than just a good model. In this guide, we break down the four components that matter most: reliable LLMs, orchestration frameworks, evaluation tools, and memory systems. We cover how teams are using Nebius AI Studio with CrewAI, ADK, LangChain, and more to ship scalable, observability-friendly agent workflows, all powered by fast, cost-efficient inference.

Our standout moment in June was NVIDIA GTC Paris, where Nebius was recognized multiple times. To mark the conference, we announced the opening of the UK cloud region and introduced integration with NVIDIA DGX Cloud Lepton, NVIDIA AI Enterprise stack and other systems. Also, our ISEG2 is #13 on the Top500 of supercomputers; we held the AI Discovery Award, and launched Managed Soperator for Slurm-based workloads. Read these and other news in today’s digest.

We kicked off Q2 with a single mission: turn raw compute horsepower into concrete business outcomes. With numerous launches, including groundbreaking models, streamlined fine-tuning, scalable throughput and seamless integrations, Nebius AI Studio has been updated significantly.

As part of NVIDIA GTC Paris at VivaTech, Nebius has announced deeper integration of the NVIDIA AI Enterprise software suite. This includes NVIDIA BioNeMo, a collection of tools, applications, generative AI solutions, and pre-trained microservices (NVIDIA NIM) designed squarely for the biopharma sector.

Learn the fundamentals of object storage, how it differs from traditional block storage solutions and why it is becoming the go-to choice for modern data management. With data volumes exploding and cloud systems becoming the norm, traditional systems are struggling to keep up with today’s data chaos. That’s where object storage comes in — built for the cloud, made to scale and ready for anything. This guide cuts through the jargon to show you why object storage is the future and how it outperforms block storage where it counts.

Managed Soperator, our fully managed Slurm-on-Kubernetes solution, is now available for everyone in self-service. It provides you with a ready-to-work Slurm training cluster, powered by modern hardware and delivered with all necessary pre-installed libraries and drivers — allowing you to start ML training immediately.

Building and deploying AI systems at scale means juggling complex infrastructure — and that’s where Kubernetes shines. From managing GPU resources to scaling inference endpoints, Kubernetes brings structure and automation to the chaos of machine learning pipelines. In this article, we’ll break down how Kubernetes works, why it’s a natural fit for AI workloads and what best practices help keep things resilient, reproducible and production-ready.