Paste the evidence from an incident — the stack trace, service logs, the request that failed, the response, and any deployment context — and this workspace correlates it into a prioritized debugging report with a reproduction command.
DataFormatter Production Error Workspace correlates a stack trace, service logs, the failing request and its response into one prioritized debugging report — with a reproduction command, trace-ID correlation and export to Markdown or JSON, all fully local and free.
Incident debugging means pulling together a stack trace from your APM, logs from the service, the request that failed and the response it got. The Production Error Workspace normalizes those slices into one session: a parsed exception with its call chain, structured log lines with level and trace IDs, a request/response pair, deploy metadata, and a prioritized list of observations ranked critical first.
Findings are labeled observations with their evidence and a location rather than absolute claims. A critical severity means "this slice of evidence shows a server-side failure"; the description explains why. Use the ordering to decide what to look at first, then pair it with your own system state before acting.
Paste the captured trace, logs and request from an on-call window, export the Markdown report and attach it to the incident ticket.
Take the request evidence from a failed payload and generate a cURL or code snippet to replay it against staging.
Expressions that fail only in a specific deploy? Add version and environment metadata to correlate the finding set against changelogs.
A stack trace, service logs (timestamped lines, JSON logs or access logs), the failing request and response, and deploy context like version or environment. Every slice is optional and is correlated with the others when the evidence supports it.
Heuristically, in the browser: a 5xx response becomes critical, a message repeated across log lines is flagged as a repeat, trace IDs are correlated between the logs and request headers. Every finding is labeled as an observation — there are no guaranteed verdicts.
Yes. When request evidence is present, the Reproduction tab builds the same cURL and code snippets (fetch, axios, Python, Java, Go) as DataFormatter's cURL converter, so you can replay the failing call locally.
No. Stack traces, logs, request and response bodies never leave your browser. Export (Markdown or JSON) writes a file to your own machine only.
Last reviewed September 2026 · DataFormatter team — this tool processes data locally in your browser.