Microsoft Azure Cobalt 100 VMs powered by Arm Neoverse are transforming performance and efficiency in the cloud, achieving up to 99% better price-performance across key real-world workloads. Customers like OneTrust and Databricks are seeing measurable gains in performance, efficiency, and cost savings, while Microsoft’s own services, such as Teams and Defender Endpoint, achieved up to 45% better performance from these instances. Together with Microsoft, we’re building purpose-built infrastructure that delivers real-world value and helps customers scale efficiently, sustainably, and confidently into the future. https://okt.to/lJiTsn
Impressive results. Curious how much of this improvement comes from Neoverse’s architecture vs Azure’s optimization layer. Huge implications for ML workloads, especially inference at scale.
Director of Engineering | AI Generalist & Builder l Strategic Leader in DevSecOps, Cloud, Mobile, Web, Product & QA | Expert in Vendor & Offshore Ops | Ex-Oracle, Macy’s, Broadcom, IBM | Driving Scalable Tech Impact
3dThe real signal here isn’t the perf bump but what it exposes: teams finally feel the tax of architectures that were never designed for AI-heavy workloads. I’ve seen this at scale in cloud stacks where the bottleneck wasn’t code, it was the shape of the infrastructure itself. Where do you see the next constraint shifting as more of these AI-first VMs roll out?