SPONSORED POST: Hyperscaler adoption and AI workloads are accelerating multi-architecture infrastructure

Five years ago, most cloud workloads ran on a single CPU architecture by default. No more. Today every major hyperscaler offers Arm-based compute, so what began as an option is now a core part of modern cloud infrastructure.

The reason is straightforward. As AI workloads scale and cloud demand continues to grow, providers are under pressure to deliver more performance while controlling power consumption, cost, and datacenter footprint. Meeting those demands is forcing a rethink of the hardware foundations of the cloud.

Arm-based silicon now powers many of these platforms. AWS offers Graviton processors, Google Cloud introduced Axion, Microsoft Azure runs Cobalt-based instances, and Oracle Cloud Infrastructure deploys Ampere Arm processors. Across these environments, the focus is consistent: improving performance while reducing power consumption and overall cost.

The economics can be significant. Arm-based cloud instances have demonstrated up to 65% better price-performance and as much as 60% greater energy efficiency across various workloads, including databases, AI inference, and networking services.

These advantages are already influencing large-scale production environments. Spotify has reported roughly 250 percent in performance improvements on Arm-based Axion processors while reducing compute costs. Meanwhile, using Arm-based AWS Graviton processors, Pinterest achieved 47 percent infrastructure cost savings and reduced carbon emissions by 62 percent for a major workload.

At Uber, engineers have taken the multi-architecture approach even further. The company is integrating Arm-based hosts alongside x86 infrastructure across thousands of microservices as part of a broader migration to the cloud. It is shooting for increased hardware flexibility, improved price-performance, and support sustainability objectives while continuing to scale globally.

Shifting toward heterogeneous cloud infrastructure doesn't necessarily mean rewriting applications from scratch. Modern cloud-native stacks already support multi-architecture environments through container tooling and orchestration platforms like Kubernetes. Many common frameworks, languages, and open-source packages now run natively on Arm.

Arm is also expanding developer resources that simplify the migration process. The Arm Cloud Migration Program offers guidance, tooling, and technical expertise to help organizations move workloads to Arm-based platforms across major cloud providers.

As AI infrastructure spending accelerates and cloud efficiency becomes a competitive priority, the industry is increasingly embracing heterogeneous compute strategies. Instead of relying on a single architecture, developers are designing systems that take advantage of multiple processor types optimized for different workloads.

In that environment, Arm is quickly becoming a core component of the modern cloud stack.

Learn more about the Arm Cloud Migration Program and resources for developers by visiting Arm today.

Sponsored by Arm.