Production Troubleshooting
Finding out what is actually wrong when a production failure does not stay inside one layer.
The failures that take longest are rarely the ones with a clear stack trace. They are the ones where the application looks fine, the infrastructure looks fine, and the problem only appears for certain clients, certain regions, or certain request paths — so each team can reasonably conclude it is not theirs.
What that needs is not a guess at the fix but a method: reproduce the failure precisely, isolate which layer it originates in by testing each one directly, and keep narrowing until the actual cause is identified rather than a plausible-sounding one. The fix is usually the short part.
Every engagement ends with something that prevents a silent repeat — a monitor, a smoke test, or a log that would have caught it.
Typical engagements
- Investigating an incident that crosses application, infrastructure and CDN boundaries
- Failures that only affect some clients — crawlers, specific regions, specific routes
- Deciding whether a problem belongs to the application or the platform it runs on
- Adding the monitoring that would have caught the failure earlier
Related work
- TaxPal
Sales analytics for an accounting-services brokerage in Japan: cases, KPI targets against actuals, rankings and pipeline conversion by staff member, team and company.
- How I Traced a Googlebot-only HTTP 500 Across Next.js, Cloud Run and the Hosting Edge
Users and every other crawler got 200 while Googlebot got 500 site-wide. The cause: a 404-path regression amplified by crawler verification at the hosting edge.
Technologies used in this work
- Apollo Client
- AWS AppSync
- AWS Cognito
- AWS Lambda
- Docker
- Elasticsearch
- GraphQL
- Next.js
- PostgreSQL
- Prisma
- React
- Terraform
- TypeScript
Is this a fit?
- A good fit: business systems, backends and APIs, GCP and AWS infrastructure, production incidents.
- Not the right fit: work that is mainly pixel-perfect UI or heavy animation.
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