From Click‑Ops and Custom Apps to Code
Managing the dbt at scale isn't about creating projects; it's about building a data foundation all teams can trust.
Our organization supports ~3,000 dbt platform projects across 6 accounts and two VPCs: one for DEV, one for PROD. Until recently, deployments depended on a custom-built promotion system we'd cobbled together to work around restricted UI access in PROD. Every new feature dbt Labs shipped meant we had to rebuild internal components before our teams could use it.
This session walks through how we replaced that entire system with a full Terraform implementation built on the official dbt platform provider. We'll cover our design decisions, module patterns, drift-elimination strategies, and the onboarding model that lets teams own their infrastructure through GitOps with consistency, auditability, and self-service built in.
Check out more sessions
- Breakout session
Optimizing your runs for lower compute, fresher data, and faster iteration with dbt State
Jimmy Hooker / FivetranView session - View sessionHands-on lab
Standardizing insights with the dbt Semantic Layer
- Breakout session
Data share as a service — generalizing Snowflake DataShare across Mitratech products
Manju Choudhary / MitratechView session
