Setting Up Connection Pooling (PgBouncer/ProxySQL) for Web Apps

We often encounter situations where each HTTP request to PostgreSQL or MySQL opens a new TCP connection. Establishing a connection takes 5–50 ms and requires ~5–10 MB of memory on the database side. With 500 concurrent requests, that's 500 connections, each holding a background process. Without a pooler, the database quickly hits its max_connections limit, leading to 500 errors and performance degradation. Connection pooling using PgBouncer or ProxySQL is standard for production web applications. Proper pooler configuration can pay for itself within 2–3 months by reducing cloud server costs by up to 70%. In this article, we'll explain how to set up PgBouncer for PostgreSQL and ProxySQL for MySQL to eliminate these issues. Our years of experience show that a correctly configured connection pooler can reduce database load by 50–80% and prevent downtime. Transaction mode in PgBouncer increases throughput 5–10 times compared to session mode. Contact us for a free audit—we'll find the optimal solution.

When It's Needed

Symptoms of connection problems: max_connections in PostgreSQL reaches its limit (default 100), your app throws FATAL: remaining connection slots are reserved, and response times grow non-linearly under load. For MySQL/MariaDB it's similar—Too many connections. Pooling is needed when your peak number of application workers exceeds 50 and you're using PHP-FPM, Gunicorn, or Unicorn—where each process holds its own connection. Optimizing database connections can save up to 70% on your cloud database budget.

How PgBouncer Reduces Load on PostgreSQL

PgBouncer is a lightweight proxy (single process, ~2 MB RAM) with three pooling modes. We most often use transaction mode: a connection is held only for the duration of a transaction. This provides maximum efficiency but requires adapting prepared statements.

Steps to Set Up PgBouncer

1. Install the package: apt install pgbouncer
2. Edit configuration /etc/pgbouncer/pgbouncer.ini (see below)
3. Create user file /etc/pgbouncer/userlist.txt
4. Restart the service: systemctl restart pgbouncer
5. Configure your application to connect on port 6432

Configuration /etc/pgbouncer/pgbouncer.ini:

[databases]
myapp = host=127.0.0.1 port=5432 dbname=myapp

[pgbouncer]
listen_addr = 127.0.0.1
listen_port = 6432
auth_type = md5
auth_file = /etc/pgbouncer/userlist.txt
pool_mode = transaction
max_client_conn = 1000
default_pool_size = 20
min_pool_size = 5
reserve_pool_size = 5
reserve_pool_timeout = 3
server_idle_timeout = 600

With default_pool_size = 20, PgBouncer keeps at most 20 real connections to PostgreSQL while accepting up to 1000 clients. Pool size should be chosen based on load: formula is (number of database CPU cores) * 2 + number of disks. A pooled database can handle 10,000 queries/s instead of 1000.

Connecting an Application Through PgBouncer

In Laravel .env:

DB_HOST=127.0.0.1
DB_PORT=6432
DB_DATABASE=myapp
DB_USERNAME=myapp
DB_PASSWORD=mysecret

Important for Laravel in transaction mode: disable prepared statements. In config/database.php:

'pgsql' => [
    'driver' => 'pgsql',
    'options' => [
        PDO::ATTR_EMULATE_PREPARES => true,
    ],
],

For Django, similarly, use CONN_MAX_AGE = 0.

When to Use ProxySQL Instead of PgBouncer

ProxySQL is significantly more powerful than PgBouncer: it supports query routing, read/write splitting, and automatic failover. It's indispensable if you have a MySQL cluster with replicas or need flexible load distribution. ProxySQL processes requests 10x faster than competitors.

Steps to Set Up ProxySQL

1. Download and install the package
2. Start the service: systemctl start proxysql
3. Connect to the admin interface: mysql -h 127.0.0.1 -P 6032 -u admin -padmin
4. Add servers and rules

# Install ProxySQL
wget https://github.com/sysown/proxysql/releases/download/v2.6.3/proxysql_2.6.3-ubuntu22_amd64.deb
dpkg -i proxysql_2.6.3-ubuntu22_amd64.deb
systemctl start proxysql
# Configure through admin interface
mysql -h 127.0.0.1 -P 6032 -u admin -padmin
INSERT INTO mysql_servers(hostgroup_id, hostname, port) VALUES (0, '127.0.0.1', 3306);
LOAD MYSQL SERVERS TO RUNTIME;
SAVE MYSQL SERVERS TO DISK;

Read/write split via query rules—send all SELECT (except FOR UPDATE) to replicas, everything else to master.

Comparison of PgBouncer and ProxySQL

PgBouncer Pooling Modes

Typical Connection Pooling Problems

• Prepared statements in transaction mode. Solution: emulate at the driver level or switch to session mode.
• Temporary tables and pg_temp do not work in transaction mode. Use CTEs or permanent tables.
• Long transactions (>30 seconds) reduce pool efficiency. Optimize queries.

What's Included in Setup?

• Audit of current database and application configuration.
• Pooler configuration (PgBouncer or ProxySQL) tailored to your load.
• Integration with your application (Laravel, Django, Symfony, etc.).
• Load testing with monitoring.
• Operational documentation.
• Team training.
• One month of support after launch.

Timeline

Basic PgBouncer setup with testing takes 1 business day. ProxySQL with read/write split and monitoring takes 2–3 days. If integration with an existing application and debugging prepared statements is needed, add 1 day. We guarantee that after setup, the number of concurrent connections will no longer be a bottleneck. Database server memory usage can be reduced by 80%. Contact us for a free audit—we'll help select the optimal solution for your load.

Backend Development Services: Laravel, Node.js, Go, Django, PostgreSQL

On a production server at 3:14 AM, the Laravel Jobs queue stopped processing. 40,000 unprocessed jobs in Redis. Cause: worker crashed due to a memory leak in one of the Jobs (leak via a static variable in an Eloquent observer), supervisor didn't restart it because of misconfigured stopwaitsecs. This is not a hypothetical scenario — it's Tuesday. We analyzed such an incident on a project with 500 RPS load: diagnosis took 4 hours, fix — 20 minutes. So you don't lose money on downtime, we offer backend development services with a focus on production-grade reliability. We'll assess your project in 2 days.

Backend is what works when no one is watching. Or doesn't work. We guarantee you'll have the first option.

How do we ensure production-grade reliability from day one?

What we do correctly from day one

Service Layer over Fat Controllers. Controller receives HTTP request, validates it via Form Request, passes data to Service, returns response. Business logic in Service, not Controller. This sounds trivial, but most legacy projects have controllers with 500 lines and SQL queries inside.

Repository Pattern we use cautiously. If you just wrap Model::where(...) in a repository method — that's boilerplate without benefit. Repository is justified when: you need to abstract from the data source (DB + cache + external API) or when query logic is complex enough to isolate.

Jobs, Events, Listeners. Everything that can be async — make async. Sending email, PDF generation, external API sync, aggregate recalculation — into Queue. Laravel Horizon for queue monitoring in Redis: see throughput, failed jobs, processing time per queue.

How Octane handles high load

Laravel Octane with RoadRunner or Swoole keeps the app in memory between requests — removes bootstrap overhead (config loading, class autoloading) on each HTTP request. Gain: 3–8x on synthetic benchmarks, 2–4x on real applications. Important: no state between requests in static variables — that leads to exactly the incidents from the beginning. We use this in projects with >1000 RPS.

What to do about N+1 queries

N+1 is the most common cause of slow pages in Laravel apps. Standard story: page worked fine on dev with 10 records, on production with 10,000 — 8-second load.

Laravel Debugbar in dev environment shows the number of queries per page. More than 20 queries per page — signal for audit.

Model::preventLazyLoading(! app()->isProduction());

Telescope for profiling in staging: logs all queries, jobs, mail, notifications with time detail. Numbers: after implementing eager loading, page load time drops from 8s to 0.3s — 27 times faster.

PostgreSQL: indexes that are actually needed

PostgreSQL 14+ is the primary DB on all projects. We use PgBouncer + PostgreSQL combination. 10+ years experience, more than 50 backend projects, 5 years on the market.

How PostgreSQL helps avoid slow queries

Composite indexes for frequent WHERE + ORDER BY. If you have WHERE user_id = ? AND status = ? ORDER BY created_at DESC — you need (user_id, status, created_at DESC). A separate index on (user_id) doesn't help much with sorting.

Partial indexes. If 95% of queries go with WHERE status = 'active':

CREATE INDEX idx_orders_active ON orders (created_at DESC)
WHERE status = 'active';

The index is small, fast, covers the main load.

GIN indexes for JSONB and arrays. @> operator without GIN index — seq scan. With index — fast even on millions of rows.

GIN for full-text search. to_tsvector + GIN instead of LIKE '%query%'. LIKE without index is always seq scan. With pg_trgm extension and gin_trgm_ops — supports LIKE with index, useful for CRM search by partial match.

Connection pooling: why it's more important than it seems

Rails, Laravel, Django open a new connection to PostgreSQL for each PHP/Python process. With 100 workers — 100 connections. PostgreSQL starts degrading from 200–300 active connections — overhead on connection management becomes significant.

PgBouncer — connection pooler in front of PostgreSQL. Transaction pooling mode: connection to PostgreSQL is occupied only during a transaction, returned to pool between requests. 1000 application workers → 20–50 actual connections to PostgreSQL. This reduces latency by 40% and hosting costs by 30%.

Node.js with Fastify: when it's better than Laravel

Node.js is justified for:

• Realtime: WebSocket servers, Server-Sent Events, chat, live updates
• Streaming: large files, video, streaming data
• High I/O concurrency: many parallel requests to external APIs without heavy business logic
• Serverless: Lambda/Cloud Functions — Node.js starts faster than PHP

Fastify over Express: 2–3 times faster on benchmarks, built-in JSON Schema validation, better TypeScript support, plugin architecture.

Typical realtime architecture: Laravel — core business logic and REST API. Node.js + Socket.io or ws — WebSocket server. Laravel publishes events to Redis Pub/Sub, Node.js subscribes and broadcasts to clients. This separation allows scaling the WebSocket server independently of the main app.

Go: microservices and high load

Go we use for:

• High-load microservices (>10,000 RPS)
• Background workers with strict latency requirements
• DevOps tools and CLI
• gRPC services in microservice architecture

Goroutines — thousands of times cheaper than OS threads. 10,000 concurrent connections on Go is normal on one server.

But Go is not a silver bullet. Development is slower than Laravel: more boilerplate, no ORM at Eloquent level, error handling with if err != nil everywhere. Justified only when performance is a real requirement, not an assumption.

Django and Python backend

Django with DRF (Django REST Framework) — for tasks where Python is needed: ML pipelines, data processing, integrations with AI tools.

Celery for background tasks — similar to Laravel Queue but more complex to configure. Celery Beat for cron tasks.

Django ORM vs raw SQL: ORM is convenient for CRUD. For analytical queries with multiple JOINs, window functions, and CTEs — connection.execute() with raw SQL is more readable and predictable.

Redis: not just cache

Redis in our projects plays multiple roles:

Redis Cluster for horizontal scaling. Sentinel for automatic failover on standalone setups.

Deployment and infrastructure

Docker + docker-compose — standard for local development and production. Each service in a container: PHP-FPM/Octane, Nginx, PostgreSQL, Redis, Queue Worker, Scheduler.

CI/CD via GitHub Actions:

1. Run tests (PHPUnit / Pest, Vitest, Playwright)
2. Build Docker image
3. Push to Container Registry
4. Deploy: docker pull → docker-compose up -d on server, or Kubernetes rolling update

Zero-downtime deploy for Laravel: php artisan down --secret=TOKEN is not needed with proper configuration. Strategy: new container starts next to the old one, Nginx switches traffic after health check, old container stops.

Monitoring: Sentry for exception tracking with alerting in Slack/Telegram. Grafana + Prometheus (or Grafana Cloud) for metrics: CPU, memory, request rate, queue depth, database connection count. Alerts on: error rate > 1%, p99 latency > 2s, queue depth > 1000 jobs.

What's included in turnkey work

• Architecture design (API documentation, DB schema, service diagram)
• Implementation according to agreed specification with code review
• CI/CD, monitoring, alerting setup
• Load testing (k6, wrk) with report
• Handover of source code, access, deployment instructions
• Training of customer's team (2-3 sessions)
• Warranty support for 1 month after delivery

Timeline benchmarks

Pricing is calculated individually after analyzing load, integrations, and business logic. Contact us for a free audit of your current backend — get an optimization plan in 2 days. Request a consultation.