10 Advanced PostgreSQL Tuning Strategies to Handle High Concurrency (Don't just increase max_connections!)

Stop Guessing: 10 Advanced PostgreSQL Tuning Strategies for High Concurrency

AWS/GCP/Azure RDS is fantastic, but running a high-concurrency application requires deep knowledge of PostgreSQL's internals to avoid bottlenecks and crashes.

I just published a detailed guide breaking down the 10 most critical, yet often overlooked, strategies for achieving maximum performance and stability under heavy load.

Here are three instant takeaways from the full article:

1. The Right Way to Handle Caching (shared_buffers & work_mem)
   Don't just assign 25% of your RAM to shared_buffers blindly. We break down the relationship between shared_buffers, work_mem, and the operating system's cache to ensure your memory is optimized for your specific workload (OLTP vs. OLAP).

   1. Autovacuum Tuning is Mandatory Default autovacuum settings can often be too slow for high-write systems, leading to transaction ID wrap-around failures or massive table bloat. Learn how to fine-tune autovacuum_vacuum_cost_limit and autovacuum_naptime based on your write volume.

2. Connection Pooling is Non-Negotiable
   
   Using max_connections correctly means understanding connection pooling tools like PgBouncer or Pgpool-II. Directly increasing max_connections is an anti-pattern that eats up RAM and degrades performance. We explain why and how to set up pooling effectively.

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This is just the tip of the iceberg! The full guide covers advanced topics like:

Partitioning strategies for massive tables.
Indexing analysis (partial indexes, covering indexes).
Choosing the right WAL settings for durability vs. speed.

Ready to crush your database bottlenecks?

Read the full 10-point strategy guide on my blog:
https://www.sparkgoldentech.com/en/blog/2025/12/03/postgresql-performance-tuning-10-advanced-strategies-for-high-concurrency-applications