How to design GitLab for enterprise scale

This post details architectural decisions for scaling GitLab at the enterprise level, focusing on deployment models (GitLab.com, GitLab Dedicated, Self-Managed), runner strategy planning (sizing, scope, autoscaling, executors), and high availability/disaster recovery planning (SLOs, RTO, RPO, GitLab Geo). It also outlines where pipeline performance breaks down at scale, emphasizing the importance of establishing performance baselines and testing large repositories/monorepos separately. Key technical considerations include capacity planning for runner fleets based on workload rather than headcount, matching executors (Kubernetes, Docker Autoscaler, Instance) to workload requirements, and defining redundancy and recovery strategies for self-managed deployments. The post also mentions Kubernetes and cloud-native deployment considerations.