Azure IaaS: Deploy high-performance workloads with a system-level approach
This blog post is the third part of a blog series called Azure IaaS which will share best practices and guidance to help you build a trusted infrastructure platform—from performance, resiliency, and security to scalability and cost efficiency.
Performance has become one of the most defining factors in how applications succeed or fail in the cloud. Whether you’re training AI models, scaling a Kubernetes platform, or running a business-critical database, performance is no longer a single decision about CPU, storage, or networking. It’s the outcome of how all three work together and requires a system-level approach.
Many organizations still approach performance by provisioning more resources—larger virtual machines (VMs), faster disks, or higher network bandwidth. But modern workloads don’t behave predictably enough for that strategy to hold. Bottlenecks shift dynamically. A database may be constrained by storage latency at one moment and network bandwidth shortly after that. An AI pipeline may...
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