Journey of developing a performance optimization feature in PGSQL | POSETTE 2026

Dive into a systematic approach to diagnosing performance issues and making optimizations for PostgreSQL. Rahila Syed (PostgreSQL developer) shares insights in her talk “Journey of developing a performance optimization feature in PostgreSQL” at POSETTE: An Event for Postgres 2026. Abstract: In this talk, I will share the journey of identifying and optimizing a performance bottleneck in PostgreSQL. The session will walk through a systematic approach to diagnosing performance issues — distinguishing whether the bottleneck lies in the CPU, I/O, or network — and how iterative profiling and analysis can guide effective optimizations. Using perf and other diagnostic tools, we’ll examine how bottlenecks can shift during optimization, sometimes masking real gains. I will demonstrate how to effectively measure improvement in performance through careful tuning of the database, along with use of pgbench and custom benchmarking scripts tailored to the optimization under test. As a practical example, we will explore an optimization in PostgreSQL’s physical replication that enables the WAL sender to transmit WAL records to standbys before they are flushed to disk on the primary. This enhancement aims to reduce replication latency by leveraging WAL buffers to send data more proactively, minimizing disk reads and improving network utilization. For large transactions, this approach allows most WAL data to be sent in parallel with ongoing writes on master, aligning the flush operations on primary and standby more closely and significantly reducing replication lag. Rahila Syed has approximately 13 years of experience working as a PostgreSQL developer. ► Video chapters: ⏩ 00:00 – Music & introduction ⏩ 00:48 – Physical replication basics ⏩ 03:54 – WAL flow from primary to standby ⏩ 05:26 – WAL buffers, fsync, and tuning ⏩ 08:41 – WAL sender loop and behavior ⏩ 15:51 – Perf profiling and flamegraph insights ⏩ 22:01 – Sending unflushed WAL ⏩ 26:03 – Benchmark results & performance gai