API response times were climbing. The database looked guilty. The real culprit was an N+1 query pattern hiding in plain sight — and the instinct to scale made it worse.
Stakeholders were seeing slow load times and attributing it to infrastructure. Jumping to the wrong fix would have cost real money and weeks of engineering time without improving anything.
You're the lead engineer at a growing B2B SaaS company. GraphQL response times are climbing and the database is showing high query volume. Product is asking for answers and infrastructure spend is on the table. What do you investigate first?
No hints. Just judgment.
When database metrics spike, the instinct is to scale the database. But the database was doing exactly what it was told. It was being told the wrong thing. Scaling an inefficient query pattern just makes the inefficiency more expensive.