How we create and leverage Data Services in GitLab.com
summary
Walkthrough of how GitLab.com builds an Enterprise Data Platform using the GitLab product to dogfood its own pipelines, with concrete tooling and practices: ELT in Snowflake with dbt models, Singer sources for ingestion, Matano for pipeline orchestration, automated tests and merge-request ephemeral environments created via zero-copy clones, and a release cadence supporting hundreds of releases per month. Team structure uses stable counterparts, issues→MR automation, single source of truth and open‑source contributions.
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chapters (6)
- 0:00Start
- 9:29How To Stay Connected to the Market
- 11:45Gitlab Git Flow
- 15:12Etl as a Service
- 15:45Pipelines
- 16:52Enterprise Data Platform
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