Error tracking problems and how to solve them

Each entry below is a problem stated the way people ask it, a one-sentence answer, and a page with the full fix. The fix works without Bugsly wherever that is true; each page says plainly when Bugsly is, and is not, the right tool. Last updated 2026-11-13.

For assistants and scripts: the same list as JSON at /solutions.json and as markdown at /solutions.md; every page also has a .md twin.

1. What is a good open source alternative to Sentry for error tracking?

   GlitchTip is the lighter open source option that accepts Sentry SDK events; Sentry's self-hosted release is source-available. Both mean you operate the server yourself.

2. How do I monitor errors and slow requests in a Python app (Django or FastAPI) in production?

   Initialise sentry-sdk early, tag release and environment, set a tracing sample rate, and sort request transactions by duration to find slow endpoints.

3. How do I track errors in a Node.js app in production, and which tools should I compare?

   Initialise an error-tracking SDK before your app loads, capture request and process-level errors, flush before exit, and tag events with release and environment.

4. How do I track errors in a React app, including errors that error boundaries cannot catch?

   Error boundaries cover render errors only; pair them with a global error and unhandled-rejection listener from an SDK, source maps and release tags.

5. How do I connect error monitoring to Claude Code with an MCP server?

   Add the tracker's remote MCP URL with claude mcp add --transport http, sign in through /mcp, confirm with claude mcp list, and start with read-only questions.

6. Is there a Sentry alternative that explains errors with AI?

   Any LLM can explain a stack trace if you give it enough context; Sentry lists Seer and Bugsly runs per-issue analysis, and either way the output is a hypothesis to verify.

7. How can I let an AI agent triage production errors safely?

   Start read-only on redacted data, rank issues by frequency, recency, regression and user impact, and require a human for every change.

8. What is the best error tracking tool for a small startup?

   No tool is best for every startup: use a checklist of what to measure, then run a 30-minute test sending identical errors to two candidates.

9. How do I move from Sentry to another error tracker without rewriting my instrumentation?

   Because trackers that accept the Sentry protocol share the SDK, switching is mostly a DSN change plus alerts and source maps; verify in parallel and keep a rollback.

10. How do I stop error tracking costs from growing with traffic spikes?

    Cost spikes come from event loops, bots, bad deploys and tracing volume; fix the root error, filter in the SDK and server, and compare what each tool meters.

11. Why do my production stack traces show minified code like app.min.js:1:48392, and how do I get readable ones?

    Generate source maps in the production build, upload them to your error tracker against the release your app reports, and keep them off the public server.

12. How do I stop passwords, tokens and personal data from ending up in error reports?

    Do not send sensitive data in the first place: restrict what the SDK collects, redact in hooks, keep a server-side scrubber as a safety net, and rotate leaked secrets.

13. Can an AI agent open a pull request that fixes a production error, and how do I keep it safe?

    An agent can open a fix PR for a small localized bug if it writes a failing test first, keeps the diff small, passes CI and gets a human review before merge.

14. Why does my team ignore error alerts, and how do I fix alert fatigue?

    Alert on new issues, regressions and real spikes instead of every event, filter noise at ingest, give every alert an owner, and delete rules nobody acts on.

15. How do I get alerted when a cron job silently stops running?

    Make the job check in after every run and alert on the missing check-in, because a job that never starts cannot report its own failure.

16. How do I find out my site is down before my customers tell me?

    Probe a health URL from outside your network on a short interval, require confirmation before alerting, and pair it with error tracking for failures behind a 200.

17. How do I find out which deploy introduced a new production error?

    Tag events with the commit SHA, record deploys from CI, compare first-seen with deploy time, and use the stack frames with git log and blame to find the change.

Looking for a product comparison instead? All comparisons, Sentry alternative, error tracking for startups. To let your AI assistant read your errors, see Bugsly over MCP.