Designing Sequential Servicing Algorithms for High-Throughput Enterprise Build and Test Pipelines

Abstract

Software delivery pipelines for enterprises require deterministic execution and resource consumption across a distributed build and testing environment. As CI/CD workflows grow in size and complexity, the servicing algorithms that provide these capabilities also become important factors in engineering productivity. This article focuses on the sequential servicing algorithms for distributed pipelines for jobs that include the checkout, build, test, and commit validation. Constraint-aware scheduling attempts a trade-off between optimizing the latency of a single job and the overall throughput of a system. The time windows for which resources are available and service constraints are considered. It provides a model describing identity and duration properties of the service and methods for selecting slots based on availability. Overall, this system helps create advanced orchestration engines, but existing schedulers don't handle batch optimization and sensitivity to arrival rates well. This method addresses both issues by employing threshold-based decision-making, providing users with a clear approach to designing pipelines that optimize resource usage while ensuring the system remains responsive to new tasks. The pipeline is strong against varying loads, and the sequential scheduling architecture makes the most effective use of the infrastructure while remaining responsive to developers.