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Performance/vConsolidate-SMP

999 bytes added, 09:13, 22 April 2011
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=== Benchmark Description ===
This The goal of Intel vConsolidate benchmark is designed to measure aggregated server performance in consolidation scenario: where when different apps (and non-related unlike to LAMP benchmark) applications are running at on the same time box each in separate its own virtual environment (virtual machines machine or operating system containerscontainer).
vConsolidate benchmark was developed by Intel in cooperation with other vendors. It runs separate workloads with Java (SPECjbb test), Mail, Web and Database VMs running concurrently. Each set of such VMs is called CSU - Consolidation Stack Unit. Performance metric is a geomean from throughput of each workload type: transactions/sec for Db, requests/sec for Web and java operations/sec for Java. The same type of metric is commonly used in other benchmarks like those from SPEC.
 
vConsolidate benchmark is very similar to other virtualization specific benchmarks like VMMark from VMWare and SPECvirt, but the latter are more enterprise oriented and generate the load requiring a fast SAN storage and high end hardware. Since we believe containers benefits are even more prominent on commodity hardware we use vConsolidate benchmark to demonstrate that.
=== Implementation ===
We use standard industrial benchmark: Intel vConsolidatev1. It was developed by Intel in cooperation with other vendors1. vConsolidate measures performance from Java, Web and Db VMs running concurrently (we excluded We do not run Mail VM as it was MS Intel benchmark has Microsoft Windows version only). Each set of such three VMs is called CSU - Consolidation Stack Unit.Performance metric is geomean from throughput of each for mail workload type: transactions/sec for Db, requests/sec for Web and java operations/sec for Java.
=== Testbed Configuration ===
Hardware:* Server: 4xHexCore Intel Xeon (2.66 GHz), 64 GB RAM, HP MSA1500 SAN Storage, 8 SATA (7200 RPM) Disks in RAID0* Client: 4xHexCore Intel Xeon (2.136 GHz), 32 GB RAM* Network: 1Gbit direct server <-> client connection
ClientPlatform: 4xHexCore Intel Xeon (2.136 GHz), 32 GB RAM Network: Gbit direct server<>client connection * Virtualization Software: XenServer5.6fp1, OpenVZ (RH5) 2.6.18-028stab085.3, OpenVZ (RH6) 2.6.32-042test006.1.x86_64 * Guest OS: Centos 5.5 x86_64
Software and Tunings:
* Custom vConsolidate profile was used: 4 load threads for Java workload, 4 load threads for Db workload and 8 threads for Web workload (standard setting)
* Firewall was turned off
* All other tunings settings were left at default valuesas defaults
=== Benchmark Results ===
=== Summary ===
OpenVZ demonstrates outstanding performance benefits over hypervisors in case of multi-processor environments and multi-threaded workloads:*Almost 3x times better overall performance in case of single set of workloads (1 CSU).* 2.1-2.2x times better overall performance on 5 and 10 CSU. === TODO: write summary===* add ESX* add a link to paper where explaining why containers are great for SMP workloads and CPU overcommit.