Performance Testing at
summary
Prototype performance pipeline runs code checked out from a GitHub endpoint, provisions a defined hardware instance, spawns simulated users and measures task latencies so pull requests can be compared to master. An API server stores metrics and serves results while workers poll for tasks, configure servers and drive thousands of clients for workloads modeled from real-customer stats. Setup currently runs manually, proves the approach, and aims to become automated but is resource hungry.
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