DEVOPS

Reconcile live Vercel Edge Config flags against GitLab source of truth

On a schedule, diffs the live Vercel Edge Config feature flags against the canonical flags.json committed in GitLab and posts any drift to Slack with a per-flag breakdown.

CategoryDevOps
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerHourly schedule fires
  • ActionRead live Edge Config key/value mapVercelVercel
  • ActionFetch flags.json from GitLab default branchGitLabGitLab
  • LogicDiff live vs. source, classify each flag
  • LogicBranch: drift found vs. clean
  • OutputPost drift report to Slack channelSlack

What it does

Keeps your runtime feature flags honest. Every run it pulls the active Vercel Edge Config store, pulls the canonical `flags.json` from the main branch of your GitLab config repo, computes a three-way diff (added live, missing live, value mismatch), and reports drift to your platform channel. If everything matches it stays silent or posts a quiet all-clear.

When to use it

Run it when manual dashboard edits or rushed hotfixes have a habit of leaving the live Edge Config out of sync with what's in version control. It turns "who flipped that flag in prod?" into a daily, auditable answer instead of a postmortem.

How it works

  1. 1A schedule fires the reconciler (default hourly).
  2. 2Fetch the current key/value map from the Vercel Edge Config store via the Vercel API.
  3. 3Fetch `flags.json` from GitLab at the default branch ref.
  4. 4A logic step computes the diff and classifies each flag as in-sync, drifted value, live-only, or repo-only.
  5. 5If any drift exists, post a formatted Slack message listing each offending flag, its live value, and its expected value; otherwise mark the run clean.

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 SlackChannels, DMs, threads, mentions.
  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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