Breaking down CPU speed: How utilization impacts performance
The Performance Engineering team at GitHub assessed how CPU performance degrades as utilization increases and how this relates to capacity. The post Breaking down CPU speed: How utilization impacts performance appeared first on The GitHub Blog.
Introduction ⛵
The GitHub Performance Engineering team regularly conducts experiments to observe how our systems perform under varying load conditions. A consistent pattern in these experiments is the significant impact of CPU utilization on system performance. We’ve observed that as CPU utilization rises, it can lead to increased latency, which provides an opportunity to optimize system efficiency. Addressing this challenge allows us to maintain performance levels while reducing the need for additional machines, ultimately preventing inefficiencies.
Although we recognized the correlation between higher CPU utilization and increased latency, we saw an opportunity to explore the specific thresholds and impacts at various stages in greater detail. With a diverse set of instance types powered by different CPU families, we focused on understanding the unique performance characteristics of each CPU model. This deeper insight empowered us to make smarter, data-driven decisions, enabling us to provision our infrastructure with greater efficiency and confidence.
With these goals in mind, we embarked on a new journey of exploration and experimentation to uncover these insights.
