VMmark 3.0, VMware’s multi-host virtualization benchmark is generally available here. VMmark3 is a free cluster-level benchmark that measures the performance, scalability, and power of virtualization platforms.
VMmark3 leverages much of previous VMmark generations’ technologies and design. It continues to utilize a unique tile-based heterogeneous workload application design. It also deploys the platform-level workloads found in VMmark2 such as vMotion, Storage vMotion, and Clone & Deploy. In addition to incorporating new and updated application workloads and infrastructure operations, VMmark3 also introduces a new fully automated provisioning service that greatly reduces deployment complexity and time.
Figure 1: VMmark3
The VMmark3 Benchmark:
Allows accurate and reliable benchmarking of virtual data center performance and power consumption of host and storage components.
Allows heterogeneous workload comparisons between different virtualization platforms.
Allows the analysis of changes in hardware, software, and configuration within virtualization environments.
VMmark3 Application Workloads:
DVDstore3: The third generation DVDstore benchmark is a complete online e-commerce test application with a back-end database component, a web application tier, and driver programs. The application simulates users logging into a web server and browsing a catalog of products using basic queries. VMmark3 utilizes DVDstore3 with 4 virtual machines, 3 Apache web-tier VMs and 1 MySQL database VM. One of the web servers delivers a constant load to the database, while the other two deliver a cyclical load to generate a bursty profile.
Weathervane: This is a highly scalable web application that contains a variety of support services working with a core application that simulates an online auction. Each VMmark3 tile contains two independent instances of the Weathervane Auction application, one static and one elastic, for a sum of 14 VMs (8 static and 6 elastic). The elastic workload mimics self-scaling applications by periodically adding and removing an application server and web server throughout the benchmark run.
Standby: The standby server mimics a heartbeat server.
VMmark3 Infrastructure Operations:
vMotion: This infrastructure operation live migrates one of the Weathervane Auction RabbitMQ VMs in a round-robin fashion to simulate modern sysadmin operations.
Storage vMotion: For this operation, one of the Standby VMs is migrated to a user-specified maintenance partition and then, after a period of rest, returns to the original location.
XvMotion: This operation simultaneously moves one of the DS3WebA VMs to an alternate host and maintenance partition. Similar to Storage vMotion, after a period of rest, the VM will return to its original location.
Automated Load Balancing (DRS): VMmark requires that DRS be enabled and running to ensure typical rebalancing operations occur within the environment under test.
VMmark3 Provisioning Service:
VMmark3 features a highly-automated setup and tile-creation process that makes benchmark deployment fast and easy, with little to no manual intervention. The entire process is seeded from a single OVA and can be utilized in an unattended mode for tile0 to N. VMmark3 uses CentOS-based free or open-source software throughout, eliminating the need for purchasing additional software licenses.
We have just published a new whitepaper on the performance of Oracle databases on vSphere 6.5 monster virtual machines. We took a look at the performance of the largest virtual machines possible on the previous four generations of four-socket Intel-based servers. The results show how performance of these large virtual machines continues to scale with the increases and improvements in server hardware.
Oracle Database Monster VM Performance on vSphere 6.5 across 4 generations of Intel-based four-socket servers
In addition to vSphere 6.5 and the four-socket Intel-based servers used in the testing, an IBM FlashSystem A9000 high performance all flash array was used. This array provided extreme low latency performance that enabled the database virtual machines to perform at the achieved high levels of performance.
Some similar tests with Microsoft SQL Server monster virtual machines were also recently completed on vSphere 6.5 by my colleague David Morse. Please see his blog post and whitepaper for the full details.
Weathervane is a performance benchmarking tool developed at VMware. It lets you assess the performance of your virtualized or cloud environment by driving a load against a realistic application and capturing relevant performance metrics. You might use it to compare the performance characteristics of two different environments, or to understand the performance impact of some change in an existing environment.
Weathervane is very flexible, allowing you to configure almost every aspect of a test, and yet is easy to use thanks to tools that help prepare your test environment and a powerful run harness that automates almost every aspect of your performance tests. You can typically go from a fresh start to running performance tests with a large multi-tier application in a single day.
Weathervane supports a number of advanced capabilities, such as deploying multiple independent application instances, deploying application services in containers, driving variable loads, and allowing run-time configuration changes for measuring elasticity-related performance metrics.
In a previous blog , we looked at how machine learning workloads (MNIST and CIFAR-10) using TensorFlow running in vSphere 6 VMs in an NVIDIA GRID configuration reduced the training time from hours to minutes when compared to the same system running no virtual GPUs.
Here, we extend our study to multiple workloads—3D CAD and machine learning—run at the same time vs. run independently on a same vSphere server.
Virtual SAN is a VMware storage solution that is tightly integrated with vSphere—making storage setup and maintenance in a vSphere virtualized environment fast and flexible. Virtual SAN 6.2 adds several features and improvements, including additional data integrity with software checksum, space efficiency features of RAID-5 and RAID-6, deduplication and compression, and an in-memory client read cache.
We ran several tests to compare the performance of Virtual SAN 6.1 and 6.2 to make sure they were on par with each other.
Remember that cool project with VMware, HP Enterprise, and IBM where four super huge monster virtual machines (VMs) of 120 vCPUs each were all running at the same time on a single server with great performance?
In addition to the four 120 vCPU VMs test, additional configurations were also run with eight 60 vCPU VMs and sixteen 30 vCPU VMs. This shows that plenty of large VMs can be run on a single host with excellent performance when using a solution that supports tons of CPU capacity and cutting edge flash storage.
The whitepaper not only contains all of the test results from the original presentation, but also includes additional details around the performance of CPU Affinity vs PreferHT and under-provisioning. There is also a best practices section that if focused on running monster VMs.
Ever wondered what it takes to debug performance issues on a VMware stack? How do you figure out if the performance issue is in your virtual machine, or the network layer, or the storage layer, or the hypervisor layer?
Here’s a handy tutorial that showcases a systematic approach for troubleshooting performance using tools like Esxtop, vSCSI stats and Net stats on a VMware stack. The tutorial also talks about some very useful optimizations and performance best practices.
Thanks to Ramprasad K. S. for putting together the slides based on his vast experience dealing with customer issues. Thanks also to Ramprasad and Sai Inabattini for presenting this at the CMG India 2nd Annual conference in Bangalore in November 2015, which was received very well.
VMware vSphere Fault Tolerance (FT) provides continuous availability to virtual machines that require a high amount of uptime. If the virtual machine fails, another virtual machine is ready to take over the job. vSphere achieves FT by maintaining primary and secondary virtual machines using a new technology named Fast Checkpointing. This technology is similar to Storage vMotion, which copies the virtual machine state (storage, memory, and networking) to the secondary ESXi host. Fast Checkpointing keeps the primary and secondary virtual machines in sync.
Performance studies have previously shown that there is no doubt virtualized servers can run a variety of applications near, or in some cases even above, that of software running natively (on bare metal). In a new white paper, we raise the bar higher and test “monster” vSphere virtual machines loaded with CPU and running the most taxing databases and transaction processing applications.
The benchmark workload, which we call Order-Entry, is based on an industry-standard online transaction processing (OLTP) benchmark called TPC-C. Both rigorous and demanding, the Order-Entry workload pushes virtual machine performance.
Note: The Order Entry benchmark is derived from the TPC-C workload, but is not compliant with the TPC-C specification, and its results are not comparable to TPC-C results.
The white paper quantifies the:
Performance differential between ESXi 6.0 and native
Performance differential between ESXi 6.0 and ESXi 5.1
Performance gains due to enhancements built into ESXi 6.0
The networking stack of vSphere is, by default, tuned to balance the tradeoffs between CPU cost and latency to provide good performance across a wide variety of applications. However, there are some cases where using a tunable provides better performance. An example is Web-farm workloads, or any circumstance where a high consolidation ratio (lots of VMs on a single ESXi host) is preferred over extremely low end-to-end latency. VMware vSphere 6.0 introduces the Dynamic Host-Wide Performance Tuning feature (also known as dense mode), which provides a single configuration option to dynamically optimize individual ESXi hosts for high consolidation scenarios under certain use cases. Later in this blog, we define those use cases. Right now, we take a look at how dense mode works from an internal viewpoint.