Case study · Credit Karma

Automated frontend risk mitigation

Standardized error reporting and post-publish validation so bad releases revert themselves instead of waiting on a manual catch.

Year
2024
observabilityqualityautomation

A shared error-reporting layer plus post-publish smoke tests that auto-revert a release when checks fail.

Before this, every app reported errors its own way, and a bad release was caught by whoever happened to be watching. I standardized how critical frontend errors get reported and added post-publish checks that revert a release on their own when it regresses.

The pieces are small and shared: a required error boundary, a network helper, and one way to report a critical error — all feeding the same telemetry the post-publish checks read. So a regression shows up in the signal a release is judged on, not in a bug report three days later. This lives in the Frontend Platform stack the whole frontend org builds on.

Highlights

  • Required error boundary that captures unhandled exceptions as critical signals
  • Network helper that reports failed requests automatically
  • One shared helper for reporting critical errors across apps
  • Post-publish workflow that runs smoke tests and reverts on failure
Rendering diagram…
Errors and failed requests feed the telemetry the post-publish checks gate on

Result

Promotions gate on smoke-test results instead of a manual sign-off, and a release that fails them reverts automatically — so the window where a bad build is live shrinks to the length of the check, not the length of someone noticing.

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