Throughput vs IOPS vs Latency Beyond Storage Network, Compute and Cloud Performance Explained

1. Introduction Most engineers first encounter throughput, IOPS, and latency in the context of storage. You provision an EBS volume, you see three numbers, and you move on. This is a mistake — and it compounds over years of building systems that mysteriously underperform. These three metrics are not storage concepts. They are fundamental properties of any system that processes work: disks, network interfaces, CPUs, GPUs, load balancers, container runtimes, and Kubernetes control planes. The same relationship between throughput, operations per second, and response time governs how a NVMe drive handles 4KB random reads, how an ENI processes packets, and how an etcd cluster responds to key-value writes. The reason performance tuning goes wrong is almost always the same: engineers optimize the wrong layer. They increase EBS IOPS when the real bottleneck is cross-AZ network latency. They add more CPU when the application is blocked on memory bandwidth. They scale pods horizontally when etcd