Build times, especially in enterprise software projects, are often an overlooked bottleneck that leads to significant inefficiencies. While working on a production ERP, deployments taking hours after merging a new feature branch became a problem that tested developers' patience and slowed down our delivery speed. Building from scratch with every small change was both a waste of resources and a major operational burden.
To solve this problem, I implemented various build cache strategies. My goal was not only to speed up builds but also to manage the operational complexity that comes with this speed. Because speed often brings new problems; issues like the correct functioning, management, and security of the cache require constant attention.
Why Were Build Times a Problem? Symptoms and Initial Observations
In a client project, especially when we transitioned to a microservices architecture, build times started to increase exponentially. Each service had its own dependencies, its own compilation steps, and these were built from scratch every time a CI/CD pipeline ran. The average deployment time after a git push, even for a small change, reached 45 minutes. Sometimes, when there was a major dependency update, this could even extend to 1.5 hours.
