Benchmarking: How to identify bottleneck (limiting factor) and achieve "linear scalability"?

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Hi,

Please pardon me if this question is already answered in the documentation, Wiki, or the mailing list archive. The problem is, that I don't know the exact term to search for - I've tried searching for "linear scalability" and "concurrency vs performance" but didn't find what I was looking for.

## MAIN QUESTION

pgbench -c 1 achieves approx 80 TPS
pgbench -c 6 should achieve approx 480 TPS, but only achieves 360 TPS
pgbench -c 12, should achieve approx 960 TPS, but only achieves 610 TPS

If pgbench is being run on a 4c/8t machine and pg-server is being run on a 6c/12t machine with 32GB RAM [1], and the two servers are connected with 1 Gbit/s connection, I don't think either pgbench or pg-server is being constrained by hardware, right?

In that case why is it not possible to achieve linear scalability, at least till 12 concurrent connections (i.e. the thread-count of pg-server)? What is an easy way to identify the limiting factor? Is it network connectivity? Disk IOPS? CPU load? Some config parameter?

## SECONDARY QUESTION

At what level of concurrent connections should settings like shared_buffers, effective_cache_size, max_wal_size start making a difference? With my hardware [1], I'm seeing a difference only after 48 concurrent connections. And that too it's just a 15-30% improvement over the default settings that ship with the Ubuntu 18.04 package. Is this expected? Isn't this allocating too many resources for too little gain?

## CONTEXT

I am currently trying to benchmark PG 11 (via pgbench) to figure out the configuration parameters that deliver optimum performance for my hardware [1] and workload [2]

Based on https://wiki.postgresql.org/wiki/Tuning_Your_PostgreSQL_Server I've made the following relevant changes to the default PG config on Ubuntu 18.04:

    max_connection=400
    work_mem=4MB
    maintenance_work_mem=64MB
    shared_buffers=12288MB
    temp_buffers=8MB
    effective_cache_size=16GB
    wal_buffers=-1
    wal_sync_method=fsync
    max_wal_size=5GB
    autovacuum=off  # NOTE: Only for benchmarking

[1] 32 GB RAM - 6 core/12 thread - 2x SSD in RAID1
[2] SaaS webapp -- it's a mixed workload which looks a lot like TPC-B

Thanks,
Saurabh.

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