Azure IaaS performance requires a system-level approach that aligns compute, storage, and networking rather than tuning each layer in isolation. For AI workloads, Azure Boost offloads hypervisor overhead while Blob Storage and ExpressRoute prevent data pipeline bottlenecks. For cloud-native apps on AKS, Azure Container Storage provides sub-millisecond NVMe latency and Cilium with eBPF reduces inter-service communication overhead. For business-critical systems, Ultra Disk and Premium SSD v2 offer independently tunable IOPS and throughput, while Accelerated Networking, proximity placement groups, and Instant Access Snapshots ensure predictable latency and fast recovery. The key takeaway is that performance gains in one layer must be matched by capabilities in others to avoid shifting bottlenecks.
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Rethinking performance in the cloudAccelerating AI workloads with system-level performanceScaling cloud-native applications without sacrificing performanceSustaining performance for business-critical systemsPerformance as a coordinated systemPractical guidance: Optimizing for your workloadBuild on a foundation designed for performanceCreate a resilient infrastructure with AzureSort: