Should I vibe code
Receive bounded error events, group them, link releases, and notify one team
Your error logs are the least-secured copy of your most-sensitive data.
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Their verdict, the Team price and the build-time estimate come from their entry, MIT-licensed. Checked 2026-08-03.
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Our verdict, the regret score and everything below it. Editorial and unsponsored — nobody can pay to be moved.
The honest answer
why the verdict is what it is
Receiving and grouping events is very doable. What people miss is that stack traces and request payloads routinely contain tokens, emails and whatever the user just typed.
What actually breaks
not "if". the specific failures.
- Stack traces containing tokens, passwords or personal data
- Request bodies logged verbatim, including whatever the user just typed
- Unbounded ingestion filling the disk during an error storm
- An error reporting endpoint that anyone can post to
An error spike floods the box. Somewhere in those two hundred thousand events are the request bodies from the checkout flow, and one of the fields was a card number that should never have reached your server in the first place. Your error log is now the most sensitive database you own, and it has the weakest access controls of anything you run.
Is that you?
the verdict is a default, not a law
- You scrub sensitive fields before storage, not after
- It is internal-only and authenticated
- There is a retention policy that actually deletes things
- The ingest endpoint is unauthenticated and public
- You have not looked at what is actually in your payloads
If you build it anyway
the checklist, then the prompt that enforces it
- Scrub on ingest with a denylist of key names — password, token, authorization, card, secret — and prefer an allowlist if you can.
- Never store raw request bodies. Store shapes and types.
- Set a retention window and enforce it. Errors from last year help nobody.
- Authenticate ingestion and rate-limit hard, or an error storm becomes an outage.
- Treat the error store as production-sensitive: it holds the worst of everything.
I want self-hosted error tracking. The data it collects is more sensitive than people expect: 1. Scrub before storage, never after. Redact any field whose key matches password, passwd, token, secret, authorization, cookie, session, card, cvv, ssn, or api_key — case-insensitive, recursively through nested objects. Make the list extensible and log when redaction fires. 2. Do not store raw request bodies by default. Store the key names and value types. Full capture is opt-in per endpoint and warned about in the README. 3. Cap the ingest rate per project and per client. During an error storm, sample rather than ingest everything, and never let ingestion fill the disk — reserve headroom and shed load first. 4. The ingest endpoint requires a per-project key. Rate-limit by key and by IP. 5. Group events by a fingerprint of the stack frames rather than the message, so parameterised messages collapse correctly. 6. Retention deletes events older than N days (default 90) on a schedule that actually runs. Verify it with a test. 7. The dashboard requires authentication. There is no public read mode. 8. In the README, state plainly that this store contains the least-sanitised copy of production data and should be treated with the same care as the primary database.
That one keeps you out of trouble. For the prompt that actually builds it, canivibecodeit.com has one.
their build prompt ↗Or don’t build it
the boring option, and the way back out
Once a team relies on it. Alerting, release tracking, source maps and issue assignment are the actual product, and they are what turn error data into fixes.
Because retention is enforced, walking away leaves a shrinking rather than a growing liability. Keep the SDK integration thin — a standard error interface — so swapping to a hosted service later touches one file.
Popular open-source uptime monitoring dashboard with many check types.
Questions
Is receiving JSON and grouping it not straightforward?
The ingestion is straightforward. What is not is that you have accidentally built a database of everything that has ever gone wrong, including the values that caused it, and those values are frequently the most sensitive ones in the system.
Every week, someone ships something they shouldn’t have.
New verdicts, the worst thing that landed in the trap, and the occasional incident report. No other email, ever.
last reviewed 2026-08-03 · verdict is editorial and unsponsored · shared entry data from canivibecodeit under MIT · not legal advice