ci-workflow-guide

To accelerate PR feedback, design a CI pipeline with stage-based orchestration, matrix-driven partitioning, and root-cause fast-fail to prune failures early. This approach minimizes wasted compute by gating stage execution and stopping downstream jobs upon detecting critical failures.

Stage partitioning is a CI orchestration technique that uses matrix-driven workload balancing across defined stage sequences. You need it when running large test suites that require parallel execution to maintain fast feedback loops on pull requests and scheduled runs.

To add new stages to an SGLang CI pipeline, follow the stage A/B/C sequence definitions and integrate health checks with wait-for-stage gating. This ensures the new stage scales properly without breaking existing workflow orchestration or fast-fail dependencies.

Root-cause fast-fail works by identifying the originating failure in a CI pipeline stage and immediately pruning dependent downstream jobs. This mechanism prunes wasted compute by ensuring only the root cause is debugged, preventing cascading test failures from consuming runner resources.

This CI orchestration guide supports both scheduled runs and pull requests. It explicitly defines stage ordering, gating, and fast-fail strategies that apply to both PR validation and scheduled CI workflows to accelerate feedback consistently.

Matrix partitioning in CI requires runner configurations that support parallel stage execution and explicit health check actions. The guide enumerates specific workflows, action helpers, and runner setups needed to satisfy workload balancing and fast-fail debugging tasks.