Why this problem matters
A poorly sized connection pool can create excessive concurrency or client queues instead of protecting the database. Applications dependent on session state may also behave incorrectly with an incompatible pool mode.
How to diagnose it
Compare pool-side queue metrics with PostgreSQL distributions by application_name, user, and state. Database connection counts alone do not reveal clients waiting in the pool.
The query groups client backends by application, user, and state. Pool-native metrics are still required for queue depth and client wait time.
SELECT application_name, usename, state, count(*) AS connections
FROM pg_stat_activity
WHERE backend_type = 'client backend'
GROUP BY application_name, usename, state
ORDER BY connections DESC;A safe solution approach
Size the pool around the database's safe active-query capacity. Test the pool mode against transaction, prepared-statement, and session-state requirements.
Why continuous monitoring matters
moon helps monitor how PostgreSQL backends respond to pool changes with low overhead. Persistent saturation can be routed through Slack, PagerDuty, or webhooks.
Frequently asked questions
Does the number of pooled clients equal the PostgreSQL connection count?
No, a pool can multiplex many clients over fewer database connections. Both the pool and PostgreSQL sides therefore need monitoring.
How does moon help with this problem?
moon continuously observes SQL Server, PostgreSQL, and MongoDB signals, helping teams evaluate the problem as a trend instead of relying on a one-time check.