Agent Skills: Database Connection Pooler

Database Connection Pooler

Overview

Configure and optimize database connection pooling using external poolers (PgBouncer, ProxySQL, Odyssey) and application-level pool settings to prevent connection exhaustion, reduce connection overhead, and improve database throughput.

Prerequisites

• psql or mysql CLI for querying connection metrics
• Access to database configuration files (postgresql.conf, my.cnf) for max_connections settings
• PgBouncer, ProxySQL, or Odyssey installed if using external pooling
• Application connection pool settings accessible (database URL, pool size parameters)
• Server CPU core count and available memory for pool sizing calculations

Instructions

1. Audit current connection usage by querying active connections:

   • PostgreSQL: SELECT count(*) AS total, state, usename FROM pg_stat_activity GROUP BY state, usename ORDER BY total DESC
   • MySQL: SHOW STATUS LIKE 'Threads_connected' and SHOW PROCESSLIST
   • Compare against max_connections setting to determine headroom

2. Calculate the optimal pool size using the formula: pool_size = (core_count * 2) + effective_spindle_count. For SSD-backed databases, use core_count * 2 + 1. A 4-core server with SSD storage should have a pool size of approximately 9. This formula applies per application instance.

3. Configure application-level connection pool parameters:

   • minimumIdle: Set to 2-5 for low-traffic periods (avoids cold-start latency)
   • maximumPoolSize: Set using the formula from step 2
   • connectionTimeout: 5-10 seconds (fail fast rather than queue indefinitely)
   • idleTimeout: 10-30 minutes (release idle connections back to pool)
   • maxLifetime: 30 minutes (prevent stale connections from accumulating)
   • leakDetectionThreshold: 60 seconds (log warning for connections held too long)

4. For PostgreSQL with many application instances, deploy PgBouncer in transaction pooling mode:

   • Set pool_mode = transaction to multiplex connections (one backend connection serves many clients between transactions)
   • Set default_pool_size = 20 and max_client_conn = 1000
   • Configure server_idle_timeout = 600 to close unused backend connections
   • Set server_lifetime = 3600 to periodically refresh connections

5. For MySQL with many application instances, deploy ProxySQL:

   • Configure connection multiplexing in mysql_servers table
   • Set max_connections per backend server
   • Configure query rules for read/write splitting to replicas
   • Enable connection pooling with free_connections_pct = 10

6. Set max_connections in the database server based on available memory. Each PostgreSQL connection uses approximately 5-10MB of memory. For a server with 8GB RAM: max_connections = (8192MB - 2048MB_for_OS - 2048MB_shared_buffers) / 10MB = ~400. For MySQL, each thread uses approximately 1-4MB.

7. Implement connection health checks. Configure the pool to validate connections before lending (testOnBorrow or validation-query). Use a lightweight query: SELECT 1 for MySQL or a simple query for PostgreSQL. Set validation interval to avoid excessive overhead.

8. Monitor connection pool metrics continuously:

   • Active connections vs. pool size (saturation indicator)
   • Wait time for connection acquisition (queuing indicator)
   • Connection creation rate (churn indicator)
   • Idle connection count (waste indicator)
   • Connection leak warnings (application bug indicator)

9. Handle connection storms (sudden spike in connection requests) by configuring a connection request queue with a bounded wait time, implementing retry with exponential backoff in the application, and pre-warming the pool during application startup.

10. Document the connection architecture: application pool size per instance, number of application instances, PgBouncer/ProxySQL settings, database max_connections, and the maximum theoretical connections formula (instances * pool_size_per_instance).

Output

• PgBouncer/ProxySQL configuration files with optimized pool settings
• Application pool configuration with connection string and pool parameters
• Connection sizing worksheet documenting the calculation from cores to pool size
• Monitoring queries for connection metrics and health checks
• Connection architecture diagram showing application -> pooler -> database flow

Error Handling

| Error | Cause | Solution | |-------|-------|---------| | FATAL: too many connections for role | Application pool size exceeds max_connections or connection leak | Reduce pool size; fix connection leaks (enable leak detection); add PgBouncer for connection multiplexing | | Connection timeout after 5 seconds | Pool exhausted, all connections in use | Increase pool size cautiously; check for long-running transactions holding connections; add connection queue with backpressure | | connection reset by peer errors | Server-side idle timeout killed the connection | Set pool maxLifetime shorter than server idle_in_transaction_session_timeout; enable connection validation | | PgBouncer no more connections allowed | max_client_conn exceeded | Increase max_client_conn; or reduce client connection demand; check for connection leaks in application | | High connection churn (create/destroy rate) | Pool too small for workload or maxLifetime too short | Increase pool size; extend maxLifetime to 30 minutes; ensure minimumIdle is set to avoid constant pool resizing |

Examples

Right-sizing a pool for a Spring Boot microservice: 4-core server, SSD storage, 3 microservice instances. Optimal pool per instance: (4 * 2) + 1 = 9. Total connections: 9 * 3 = 27. Database max_connections = 100 with comfortable headroom. Application startup pre-warms 5 connections per instance. Connection leak detection set to 60 seconds catches a missing connection.close() in an error handler.

PgBouncer deployment for a serverless application: Lambda functions create a new database connection per invocation, overwhelming PostgreSQL with 500+ connections. PgBouncer deployed between Lambda and PostgreSQL with pool_mode = transaction, default_pool_size = 25, max_client_conn = 5000. Lambda connects to PgBouncer; PgBouncer multiplexes to 25 backend connections. Connection errors eliminated; database CPU reduced from 95% to 30%.

ProxySQL read/write splitting: A MySQL application sends 80% reads and 20% writes. ProxySQL routes writes to the primary and distributes reads across 2 replicas. Connection pooling reduces backend connections from 300 (direct) to 60 (pooled). Average query latency drops from 8ms to 3ms due to reduced connection overhead.

Resources

• PgBouncer documentation: https://www.pgbouncer.org/config.html
• ProxySQL documentation: https://proxysql.com/documentation/
• HikariCP pool sizing: https://github.com/brettwooldridge/HikariCP/wiki/About-Pool-Sizing
• PostgreSQL connection management: https://www.postgresql.org/docs/current/runtime-config-connection.html
• Odyssey connection pooler: https://github.com/yandex/odyssey