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Card class: Non-HeroCategory: Capacity

At a glance

Connections In Use is the live count of client connections currently established to the MySQL instance, read from the Threads_connected status variable. It is the raw numerator behind pool saturation: how many seats at the table are taken right now, before you compare against the max_connections ceiling. A steady reading that tracks your traffic shape is healthy; a flat-line at the ceiling, or a slow upward creep that never falls back, is the early signal of a connection leak or an undersized pool.

What it tracks

The card reports Threads_connected from SHOW GLOBAL STATUS, sampled in real time. That value is every connection currently open, whether actively running a query or sitting idle in a pool. It is distinct from Threads_running (connections actively executing at this instant) and from max_connections (the configured ceiling). Reading it alongside those two tells the whole capacity story: in-use against the ceiling gives headroom, in-use against running tells you how much of the pool is idle. A high in-use count with a low running count is the classic fingerprint of an oversized or leaky application pool holding sessions open without doing work. On managed services the same value appears as the RDS/Aurora DatabaseConnections CloudWatch metric and the Cloud SQL mysql.connections metric.

Reconciling against the source

Run SHOW STATUS LIKE 'Threads_connected'; on the instance for the live figure, or SELECT COUNT(*) FROM information_schema.PROCESSLIST; to see the same connections enumerated; on Amazon RDS / Aurora cross-check the DatabaseConnections CloudWatch metric, and on Cloud SQL the mysql.connections metric.

Tracked live in Vortex IQ Nerve Centre

Connections In Use is one of hundreds of KPI pulses Vortex IQ tracks across MySQL and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. Start for free or book a demo to see this metric running on your own data.