How would you diagnose a slow Spring Boot endpoint in production?

Moves from user-visible latency to route, dependency, database, executor, JVM, and change evidence before selecting a fix.

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TL;DR

I define the scope first: affected route, percentiles, time window, tenants or inputs, error rate, and whether the regression matches a deployment or traffic change. A representative distributed trace shows time in controller, database, downstream calls, and queueing. I correlate it with structured logs and metrics rather than reading one slow request in isolation.

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Latency distributions, traces, structured logs, query and pool metrics, thread dumps, JVM signals, deployment correlation, and mitigation.

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Core answer
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Overview
A slow endpoint is a symptom; diagnosis identifies where the request spends time and what changed before tuning anything.
I define the scope first: affected route, percentiles, time window, tenants or inputs, error rate, and whether the regression matches a deployment or traffic change. A representative distributed trace shows time in controller, database, downstream calls, and queueing. I correlate it with structured logs and metrics rather than reading one slow request in isolation.
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Stronger answer
Optional upgrade with examples, trade-offs, and sharper phrasing.
If database spans dominate, I inspect generated SQL, query plans, lock waits, row counts, and Hikari acquisition time. If time is outside spans or tasks wait, I check server threads, executor queues, downstream client pools, and a thread dump. JVM CPU, allocation, garbage collection, and memory pressure can explain broad pauses. I compare fast and slow examples and keep route labels normalized so the telemetry itself is trustworthy.

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Details

Looking only at average latency.
Adding a cache before locating the slow boundary.
Restarting before collecting representative evidence.

How would you diagnose a slow Spring Boot endpoint in production?

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