Monitoring PostgreSQL Performance: Tools and Techniques

PostgreSQL is a beast of a database. It’s open-source, powerful, and used by some of the biggest tech companies out there. But let’s be real—just because it’s great doesn’t mean it’s always smooth sailing. Performance issues can creep in, and if you don’t keep an eye on things, they can turn into major headaches.

Now, when I sat down to write this article, I was honestly confused about what to include. Should I go all in on query performance? Talk about storage? Or focus on monitoring tools? So, after doing some deep research (yes, I spent hours reading documentation, blog posts, and case studies), I also roped in a few tech friends who manage large-scale PostgreSQL databases. They helped me optimize this list so that it includes only the most practical, real-world techniques. This is not just a random collection of tips—it’s a well-researched guide that will actually help you.

If you’re a developer, DBA, or just someone managing PostgreSQL in production, this is for you. We’ll cover key metrics, built-in monitoring tools, third-party solutions, and some real-world scenarios. And don’t worry, I’ll keep it simple, engaging, and, most importantly, useful. Let’s dive in!

Why Should You Monitor PostgreSQL Performance?

Imagine running an e-commerce site, and suddenly, your checkout process slows down. Orders aren’t being processed quickly, customers are frustrated, and your sales are taking a hit. This is what happens when you don’t monitor database performance.

Here’s why keeping an eye on PostgreSQL is crucial:

1. You can catch slow queries before they bring your app to a crawl.
2. You’ll know if your database is running out of memory or disk space.
3. You can prevent deadlocks and connection issues before they impact users.
4. You can optimize indexes and query plans, making everything run faster.

Alright, now that we know why monitoring is important, let’s break down what exactly we need to track.

Key PostgreSQL Performance Metrics

1. Query Performance

• Execution Time: Slow queries = slow app. Keep an eye on how long each query takes.
• Query Plan Analysis: Use EXPLAIN ANALYZE to understand how PostgreSQL is executing queries.

EXPLAIN ANALYZE SELECT * FROM orders WHERE customer_id = 123;        

2. Database Connections

• Too many open connections? Check pg_stat_activity to see what’s happening.

SELECT * FROM pg_stat_activity;        

• Use a connection pooler like PgBouncer to avoid overloading your database.

3. Index & Table Statistics

• Not all indexes help—some slow things down! Use pg_stat_user_indexes to see which ones are actually used.

SELECT relname, indexrelname, idx_scan FROM pg_stat_user_indexes;        

• Monitor table bloat and dead tuples with pg_stat_all_tables.

SELECT relname, n_dead_tup FROM pg_stat_all_tables WHERE n_dead_tup > 1000;        

4. Disk I/O & Storage

• If your database is hitting disk too often, performance will suffer. Check pg_stat_bgwriter.

SELECT * FROM pg_stat_bgwriter;        

• Watch out for WAL (Write-Ahead Logging) growth—it can quickly fill up storage.

5. Memory Usage

• Use pg_buffercache to track shared buffer efficiency.
• Monitor work_mem usage to prevent excessive disk writes.

6. Replication & High Availability

• If you’re using replication, track lag with pg_stat_replication.

SELECT * FROM pg_stat_replication;        

• Ensure failover mechanisms are tested regularly.

7. Locking & Deadlocks

• Blocking queries can cripple performance. Use pg_locks to spot issues early.

SELECT * FROM pg_locks;        

Best PostgreSQL Monitoring Tools

1. Built-in PostgreSQL Monitoring Tools

pg_stat_statements

• Tracks execution statistics for queries.
• Helps find slow queries quickly.

SELECT * FROM pg_stat_statements ORDER BY total_time DESC LIMIT 10;        

EXPLAIN & EXPLAIN ANALYZE

• Shows query execution plans.
• Helps in debugging and optimizing queries.

pg_stat_activity

• Lists currently running queries.
• Helps detect long-running or stuck queries.

pg_locks

• Displays active locks in the database.
• Useful for troubleshooting concurrency issues.

2. Third-party Monitoring Tools

pgAdmin

• Web-based GUI for PostgreSQL monitoring and management.

Prometheus + Grafana

• Best for real-time monitoring with visual dashboards.

Datadog

• Cloud-based PostgreSQL performance monitoring.

pganalyze

• Helps optimize query performance with deep insights.

New Relic

• Enterprise-grade tool for monitoring PostgreSQL in cloud environments.

Final Thoughts

If you’re running PostgreSQL in production, don’t wait until things break to start monitoring. Set up automated alerts with tools like Prometheus or Datadog so you can catch issues early. Slow queries, high replication lag, or memory spikes can all be disastrous if ignored.

The key to keeping your PostgreSQL database running smoothly is proactive monitoring and regular tuning. Whether you’re a DBA or a developer, understanding these tools and techniques will save you from many sleepless nights.

At Learnomate Technologies, we provide the best hands-on training for PostgreSQL, covering everything from basic queries to advanced performance monitoring and tuning. If you want to dive deeper and master PostgreSQL, check out our training programs here: Learnomate PostgreSQL Training.

For more insights, visit our YouTube channel where we regularly post tutorials and technical deep-dives: www.youtube.com/@learnomate.

Let’s connect on LinkedIn! Follow me for more tech content and career tips: Ankush Thavali.

If you want to read more about different technologies, check out our blog posts here: Learnomate Blog. Happy learning!