CPU architectures for enterprise applications have been a monoculture dominated by x86 since the advent of the modern PC and server in the 1990s. But in the past decade, things have been changing fast. Availability of easy-to-use Arm64 sillicon at a low price point with Raspberry Pi advanced the open source ecosystem and vastly improved Arm64 support and performance by distributions like Fedora and Debian. Apple choosing Arm64 as the architecture for their laptops, combined with the popularity of Arm hardware with cloud application developers, really raised developer awareness. And the advent of server-grade Arm64 silicon in cloud server providers - either home-grown or based on Ampere CPUS - at a price point typically 20-30% cheaper per core hour than equivalent x86 instances has massively increased adoption of Arm64 in the cloud, and given a boost to enterprise support for the architecture through the cloud native ISV ecosystem.

Adding a new architecture to your application infrastructure brings some risk. Some of the questions I hear all the time are:

• What are the benefits of running my cloud applications on Ampere or other Arm64 instances?
• What workloads should I move first, and how can I pick & choose which application components run on which architecture
• How do I know if this architecture is supported by all of my dependencies?
• What do I need to do to rebuild and requalify my software for Ampere servers?
• How can I containerize my software for multiple architectures, and how will workload placement on Kubernetes work?
• Are any of the supporting functions for cloud applications (log management, observability, service mesh, etc) impacted?

This presentation will answer all of these questions. We will walk through a couple of case studies of people who saw both performance improvements and cost reduction when moving to Ampere-powered Arm64 instances. Then we will look at how, practically, you can update your CI processes to make multi-architecture containers using Podman and friends. Finally, we will talk about workload placement on Kubernetes, and how to use ArgoCD Rollouts to give yourself a safety net and incrementally migrate your application to Arm64.