Understanding how workloads interact with compute resources is essential for effective DevOps practices. In this chapter, you will explore the major types of workloads—CPU-bound, memory-bound, I/O-bound, and network-bound—and learn how each one places unique demands on a system. Each workload type utilizes system resources differently, which directly impacts performance, scalability, and cost.

A CPU-bound workload is limited mainly by the processing speed of the CPU. Tasks such as data encryption or video rendering often fall into this category, where the processor is the primary bottleneck. In contrast, memory-bound workloads are restricted by the available RAM. Applications like large-scale data analytics or in-memory databases require significant memory to function efficiently.

I/O-bound workloads depend heavily on input/output operations, such as reading from or writing to disk. Examples include file servers and backup systems, where disk speed and throughput are critical factors. Network-bound workloads are constrained by network bandwidth and latency. Services that transfer large amounts of data over the network, such as streaming platforms or distributed applications, illustrate this pattern.

By identifying the dominant workload type in a given scenario, you can make informed decisions about infrastructure, scaling, and optimization. This practical understanding helps you allocate resources more effectively, troubleshoot performance bottlenecks, and design systems that meet real-world demands. Throughout this chapter, you will gain the skills to analyze workload patterns and apply this knowledge to optimize resource utilization in DevOps environments.