## Objective Perform a TPC-B-like benchmarking with pgbench with different concurrency levels to evaluate how scalable each hardware is, and how saturation will impact `response time/latency` and `RPS` over the hardware to be evaluated. ## Workload: Benchmarking hardware nodes: - `n2d-standard-224` - patroni-main-machine-test-01-db-db-benchmarking.c.gitlab-db-benchmarking.internal - `n1-highmem-96` - patroni-main-machine-test-a-01-db-db-benchmarking.c.gitlab-db-benchmarking.internal - `n2-highmem-128` - patroni-main-machine-test-b-01-db-db-benchmarking.c.gitlab-db-benchmarking.internal - `n2d-highmem-96` - patroni-main-machine-test-c-01-db-db-benchmarking.c.gitlab-db-benchmarking.internal --- The `-s` should be a scale factor sufficient for the dataset not fit completely in memory, hence we should observe some degree of I/O reads. Suggestion is: 1.3 TB which is 1.5 times RAM size of `n2d-standard-224`. --- To simulate concurrency, we can start with 50 clients and increment by 50 on each cycle until we reach (CPU or I/O) saturation on all 3 nodes for us to find what is the limit of concurrency for each hardware. Concurrent client connections cycles should be: - 50 - 100 - 150 - 200 - 250 - 300 (optional until saturation is reached) - 350 (optional until saturation is reached) - 400 (optional until saturation is reached) ## Parameters: PG Parameter settings should be customised for each hardware: - max_connections: TBD - shared_buffers: TBD - effective_cache_size: TBD