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We present Conveyor, Meta's software deployment tool, along with the valuable data obtained from managing over 30,000 deployment pipelines that deploy all kinds of services at Meta across millions of machines. We describe a wide range of deployment scenarios that Conveyor supports to achieve universal coverage. At Meta, out of all the deployment pipelines for services deployed via containers, 97% of them employ fully automated deployments without manual intervention: 55% utilize continuous deployment, instantly deploying every code change to production after passing automated tests, and the remaining 42% are automatically deployed on a fixed schedule (mostly daily or weekly) without manual validation. We highlight several distinguishing features of Conveyor, including safe in-place updates to reduce hardware costs, analysis of code dependencies to prevent faulty releases, and the capability to deploy complex ML models at scale.