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Tag Archives: virtualization

New White Paper: Fast Virtualized Hadoop and Spark on All-Flash Disks – Best Practices for Optimizing Virtualized Big Data Applications on VMware vSphere 6.5

A new white paper is available showing how to best deploy and configure vSphere 6.5 for Big Data applications such as Hadoop and Spark running on a cluster with fast processors, large memory, and all-flash storage (Non-Volatile Memory Express storage and solid state disks). Hardware, software, and vSphere configuration parameters are documented, as well as tuning parameters for the operating system, Hadoop, and Spark.

The best practices were tested on a 13-server cluster, with Hadoop installed on vSphere as well as on bare metal. Workloads for both Hadoop (TeraSort and TestDFSIO) and Spark Machine Learning Library routines (K-means clustering, Logistic Regression classification, and Random Forest decision trees) were run on the cluster. Configurations with 1, 2, and 4 VMs per host were tested as well as bare metal. Among the 4 virtualized configurations, 4 VMs per host ran fastest due to the best utilization of storage as well as the highest percentage of data transfer within a server. The 4 VMs per host configuration also ran faster than bare metal on all Hadoop and Spark tests but one.

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Introducing VMmark3: A highly flexible and easily deployed benchmark for vSphere environments

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.

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Oracle Database Performance on vSphere 6.5 Monster Virtual Machines

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 across 4 generations of Intel based servers on vSphere 6.5

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.

Please read the full paper, Oracle Monster Virtual Machine Performance on VMware vSphere 6.5, for details on hardware, software, test setup, results, and more cool graphs.  The paper also covers performance gain from Hyper-Threading, performance effect of NUMA, and best practices for Oracle monster virtual machines. These best practices are focused on monster virtual machines, and it is recommended to also check out the full Oracle Databases on VMware Best Practices Guide.

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.

This work on Oracle is in some ways a follow up to Project Capstone from 2015 and the resulting whitepaper Peeking at the Future with Giant Monster Virtual Machines . That project dealt with monster VM performance from a slightly different angle and might be interesting to those who are also interested in this paper and its results.

 

Weathervane, a benchmarking tool for virtualized infrastructure and the cloud, is now open source.

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.

Weathervane has been used extensively within VMware, and is now open source and available on GitHub at https://github.com/vmware/weathervane.

The rest of this blog gives an overview of the primary features of Weathervane.

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Machine Learning on vSphere 6 with Nvidia GPUs – Episode 2

by Hari Sivaraman, Uday Kurkure, and Lan Vu

In a previous blog [1], 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.

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Virtual SAN 6.2 Performance with OLTP and VDI Workloads

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.

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Peeking At The Future with Giant Monster Virtual Machines

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?

That was Project Capstone, and it was presented at VMworld San Francisco and VMworld Barcelona last fall as a spotlight session.  The follow-up whitepaper is now completed and published,  which means that there are lots of great technical details available with testing results and analysis.

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.

Tutorial Session on Performance Debugging on VMware vSphere

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.

Fault Tolerance Performance in vSphere 6

VMware has published a technical white paper about vSphere 6 Fault Tolerance architecture and performance. The paper describes which types of applications work best in virtual machines with vSphere FT enabled.

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.

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Virtualizing Performance-Critical Database Applications in VMware vSphere 6.0

by Priti Mishra

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

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