How to design GitLab for enterprise scale

Enterprise GitLab planning requires early decisions about deployment model, runner architecture, availability targets, workload capacity, and operational ownership because small choices can become major constraints as teams, repositories, and pipelines grow. Organizations can use GitLab.com for reduced infrastructure management, GitLab Dedicated for managed single-tenant isolation, or GitLab Self-Managed for direct control with full responsibility for scaling, security, upgrades, and recovery. Runner fleets should be sized by job volume, duration, concurrency, hardware needs, trust boundaries, and peak demand rather than developer count, with autoscaling, executor selection, and runner scope balanced against utilization and isolation requirements. Availability and recovery designs should define SLOs, RTOs, and RPOs while treating high availability, disaster recovery, and backups as separate layers, especially for self-managed environments where failover procedures must be tested. Performance monitoring should distinguish job queue time from execution and pipeline duration to identify runner shortages, inefficient pipeline design, repository-transfer demands, or infrastructure bottlenecks, with large repositories and monorepos evaluated separately. Kubernetes can support either runner workloads or GitLab itself, but requires planning for cluster capacity, scheduling, isolation, external dependencies, observability, upgrades, and recovery. Before rollout, platform teams should validate ownership, sizing, runner capacity, recovery procedures, performance under peak workloads, and scaling thresholds, then continually reassess the architecture as usage evolves.

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