DEVOPS

Snapshot Vercel flag drift to BigQuery for compliance history

On schedule, records the full live-vs-source flag comparison as timestamped rows in BigQuery, building a queryable history of every flag's state and any drift events.

CategoryDevOps
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • Trigger15-minute schedule fires
  • ActionFetch live Edge Config from VercelVercelVercel
  • ActionFetch flags.json source from GitLabGitLabGitLab
  • LogicJoin by key, stamp drift status + timestamp
  • OutputAppend rows to BigQuery flag-history tableGoogle BigQueryBigQuery

What it does

Builds an immutable audit log of feature-flag state over time. Each run captures the live Vercel Edge Config values alongside the GitLab `flags.json` source values, computes per-flag drift status, and appends one timestamped row per flag to a BigQuery table. Over weeks this becomes a full history you can query for when a flag changed, how long it was drifted, and who diverged from source.

When to use it

Use it for compliance, incident forensics, or change-management reporting where you must prove the state of production flags at any past moment. Pairs well with a separate remediation workflow that fixes drift in real time.

How it works

  1. 1A schedule fires the snapshot job (default every 15 minutes).
  2. 2Fetch live Edge Config values from Vercel.
  3. 3Fetch the canonical `flags.json` from GitLab at the default branch.
  4. 4A logic step joins the two by key and stamps each flag with in-sync or drifted status plus the run timestamp.
  5. 5Append the rows to the BigQuery flag-history table for later querying.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect VercelDeploys, runtime logs, analytics.
  2. 2
    Connect GitLabRepos, MRs, pipelines, registry.
  3. 3
    Connect BigQueryDatasets, queries, schemas.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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