API Governance at Scale

The pilot episode of Research Insights Made Simple examines API Governance at Scale. Alexander Polomodov and Daniil Kuleshov discuss Google, where thousands of APIs require shared language, rules, and automation. At that scale, interface design becomes an engineering process rather than a local team preference.

Manual design review creates a bottleneck, especially when a violation is found after implementation. Google's answer is API Improvement Proposals, inspired by Python Enhancement Proposals. They codify rules and the change lifecycle, while linters and IDE tooling return feedback earlier.

Governance is not a set of commandments carved in stone. Rules are discussed by the community, versioned, replaced, and open to justified exceptions. The hosts compare the model with open source: learning, explicit statuses, and decision history matter as much as automated validation.

The research combines surveys, logs, and observation of API-design work. Newcomers find the process long, while experienced participants see acceleration and ready answers. Some want simpler rules and others need more detail, requiring a balance of speed, completeness, and continuous improvement.