CURRENT

Demos run on sanitized datasets with known edge cases handled. Your production data has nulls in unexpected places, encodings that break parsers, and user behavior no QA team anticipated. Ask for deployment timelines on real customer data, not feature completeness on their test set.

Monitoring shows you that something failed. Observability lets you figure out why without redeploying instrumentation. When production breaks at 3am, you need to interrogate the system with questions you didn't think to ask yesterday. Predefined dashboards won't cut it.

Your best deployment platform is the one your ops team already knows. If this requires new infrastructure or doesn't integrate with existing monitoring, you're not evaluating a tool. You're committing to a migration project that'll consume six months nobody planned for.

Requirements shift constantly. New data sources, modified workflows, unexpected use cases. Can your team adapt the system themselves, or does every adjustment require vendor involvement? This determines whether your investment compounds or becomes technical debt you're stuck maintaining.

Test conditions reveal nothing about production behavior. What happens at 10x your demo load during a traffic spike? Does latency climb linearly or does something cliff-dive? The architectural choices that seem theoretical now determine whether you're rebuilding when actual users arrive.

Some infrastructure fades into the background. Other systems demand constant attention. Before committing, understand monitoring requirements, rollback procedures, incident patterns. Production readiness reviews take months at scale because this question has expensive answers vendors won't surface in sales calls.