An ASP.NET Core API starts failing with database connection pool exhaustion. How would you investigate it?

Debug connection pool exhaustion in a .NET API

Explains database connection pool exhaustion with practical .NET data-access examples and production trade-offs.

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I confirm pool exhaustion from connection-open latency, timeout errors, active connection metrics, and the database view of sessions. Then I look for leaked connections, long transactions, slow queries, and sudden concurrency growth. EF Core normally opens and closes connections around operations, so manually held connections, streaming readers, and uncompleted transactions deserve close inspection.

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Understanding of database connection pool exhaustion, EF Core/SQL behavior, API boundaries, production risks, and practical debugging or design judgment.

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Explain database connection pool exhaustion with practical .NET data-access examples and production trade-offs. It matters in real backend work because query shape, indexes, transactions, locking, and data volume can turn harmless-looking code into a production bottleneck. The practical angle is database connection pool exhaustion, EF Core/SQL behavior, API boundaries, production risks, and practical debugging or design judgment, tied to a concrete production decision.
I confirm pool exhaustion from connection-open latency, timeout errors, active connection metrics, and the database view of sessions. Then I look for leaked connections, long transactions, slow queries, and sudden concurrency growth. EF Core normally opens and closes connections around operations, so manually held connections, streaming readers, and uncompleted transactions deserve close inspection.
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I correlate the incident with endpoint traffic and query duration because the pool may be healthy in size but every connection is occupied too long. Traces and database activity reveal whether one query, lock wait, or downstream workflow is holding connections. I reduce the hold time, fix disposal and transaction scopes, and bound request or worker concurrency. Increasing the pool can buy time only after the database can handle the extra sessions; it does not repair a leak or overloaded query.

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Treating database connection pool exhaustion as a syntax detail instead of a production behavior.
Not checking generated SQL, query plans, or actual data volume.
Testing only with tiny local data and assuming production will behave the same.
Fixing symptoms with caching, timeouts, or retries before understanding the data-access cause.

An ASP.NET Core API starts failing with database connection pool exhaustion. How would you investigate it?

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