DEVOPS

Vercel Build-Time Regression Detector to Datadog and Slack

Tracks Vercel build durations over time, flags when a deploy's build time regresses beyond a rolling-average threshold, emits a Datadog metric.

CategoryDevOps
Enginesim
Difficultyintermediate
Triggerwebhook
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerVercel deployment-succeeded webhookVercelVercel
  • ActionAppend duration and compute rolling averagePostgreSQLPostgres
  • ActionSubmit build duration metric to DatadogDatadogDatadog
  • LogicDetect regression vs rolling-average threshold
  • OutputAlert platform channel in SlackSlack

What it does

Watches how long each Vercel build takes and catches slow-build regressions before they erode developer velocity. After every successful deploy it records the build duration, compares it to the recent rolling average, sends the value to Datadog as a custom metric, and pings Slack when a build is meaningfully slower than normal.

When to use it

Use it when build times are creeping up and you want a quantified, charted signal instead of anecdotes. Good for teams that already run Datadog dashboards and want build performance treated as a first-class operational metric.

How it works

  1. 1A Vercel deployment-succeeded webhook delivers the build duration and metadata.
  2. 2The flow appends the duration to a Postgres history table and computes the trailing rolling average.
  3. 3It submits the build duration as a custom metric to Datadog for dashboarding and long-term trends.
  4. 4A regression check fires when the new build exceeds the rolling average by the configured percentage.
  5. 5On regression it posts a Slack message naming the project, branch, duration, and percent over baseline so the team can investigate.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect VercelDeploys, runtime logs, analytics.
  2. 2
    Connect DatadogMetrics, traces, log search.
  3. 3
    Connect PostgresAny Postgres URL — query, write, migrate.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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