Stack Dyno
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Data

Dec 26, 2024

Connect Stack Dyno to BigQuery

Sync contextual tables (labels, business units, owners) so FinOps narratives stay human-readable.

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Connect Stack Dyno to BigQuery

Beyond raw billing export data, Stack Dyno benefits from lightweight lookup tables that translate project IDs into ownership, lifecycle stage, and margins.

TableColumnsPurpose
teamsteam_id, name, leader_emailDrive alert routing + savings owners
projectsproject_id, business_unit, env, productFriendly labels for Sankey + filters
commitmentssku, term_months, coverage_targetAutomate CUD guidance

ETL flow

  1. Source metadata from your CMDB or spreadsheets.
  2. Load into a staging table (CSV imports work fine).
  3. Merge into the canonical dataset with simple SQL.
MERGE `my-project.stackdyno_metadata.projects` AS target
USING `my-project.tmp.projects_staging` AS src
ON target.project_id = src.project_id
WHEN MATCHED THEN UPDATE SET
  business_unit = src.business_unit,
  env = src.env,
  product = src.product
WHEN NOT MATCHED THEN
  INSERT(project_id, business_unit, env, product)
  VALUES(project_id, business_unit, env, product);

Consuming inside Stack Dyno

  • Update frontend-user/src/state/FrontendUserDataContext.tsx to enrich the dataset before rendering.
  • Mirror the logic in frontend-reseller so both apps stay in sync.
  • Surface missing metadata (e.g., unlabeled projects) as checklist items in the docs so teams know how to help.

Once the lookup tables land, screenshots, alerts, and dashboards all reference the same friendly naming conventions.


Need more depth? Check the related guides or ping us for a live walk-through.

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