How can database density be measured?
- How does database performance behave as more DBs are consolidated?
- What impact does running the CVM have on available host resources?
- The cluster was able to achieve ~90% of the theoretical maximum.
- CVM overhead was 5% for this workload.
The goal was to establish how database performance is affected as additional database workloads are added into the cluster. As a secondary metric, measure the overhead from running the virtual storage controller on the same host as the database servers themselves. We use the Postgres database with pgbench workload and measure the total transactions per second.
- 4 Node Nutanix cluster, with 2x Xeon CPU’s per host with 20 cores per socket.
Each database is identically configured with
- Postgres 9.3
- Ubuntu Linux
- 4 vCPU
- 8GB of memory
- pgbench benchmark, running the “simple” query set.
The database is sized so that it fits entirely in memory. This is a test of CPU/Memory not IO.
The experiment starts with a single Database on a single host. We add more databases into the cluster until we reach 40 databases in total. At 40 databases with 4 vCPU each and a CPU bound workload we use all 160 CPU cores on the cluster.
The database is configured to fit into the host DRAM memory, and the benchmark runs as fast as it can – the benchmark is CPU bound.
Below are the measured results from running 1-40 databases on the 4 node cluster.
Performance scales almost linearly from 4 to 160 CPU with no obvious bottlenecks before all of the CPU cores are saturated in the host at 40 databases.Continue reading