Large-scale enterprise applications typically have many microservices that are deployed across numerous cloud providers and various geographic locations. When running a high-demand period (i.e., during peak campaigns), the most significant engineering challenge faced by large-scale enterprise applications is not “slow down,” but rather: “be correct when correctness matters,” “be gracious when correctness doesn’t matter,” and “recover reliably and predictably.”
Below, I present a practical approach to capacity planning and demonstrated load-shedding patterns for large-scale enterprise applications based on historical campaign behavior, with examples and illustrations of actual data points from previous campaigns.