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DRS Enhancements in vSphere 6.7

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A new paper describes the DRS enhancements in vSphere 6.7, which include new initial placement, host maintenance mode enhancements, DRS support for non-volatile memory (NVM), and enhanced resource pool reservations.

Resource pool and VM entitlements—old and new models

A summary of the improvements follows:

  • DRS in vSphere 6.7 can now take advantage of the much faster placement and more accurate recommendations for all DRS configurations. vSphere 6.5 did not include support for some configurations like VMs that had fault tolerance (FT) enabled, among others.
  • Starting with vSphere 6.7, DRS uses the new initial placement algorithm to come up with the recommended list of hosts to be placed in maintenance mode. Further, when evacuating the hosts, DRS uses the new initial placement algorithm to find new destination hosts for outgoing VMs.
  • DRS in vSphere 6.7 can handle VMs running on next generation persistent memory devices, also known as Non-Volatile Memory (NVM) devices.
  • There is a new two-pass algorithm that allocates a resource pool’s resource reservation
    to its children (also known as divvying).

For more information about all of these updates, see DRS Enhancements in vSphere 6.7.

VMware’s AI-based Performance Tool Can Improve Itself Automatically

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PerfPsychic  our AI-based performance analyzing tool, enhances its accuracy rate from 21% to 91% with more data and training when debugging vSAN performance issues. What is better, PerfPsychic can continuously improve itself and the tuning procedure is automated. Let’s examine how we achieve this in the following sections.

How to Improve AI Model Accuracy

Three elements have huge impacts on the training results for deep learning models: amount of high-quality training data, reasonably configured hyperparameters that are used to control the training process, and sufficient but acceptable training time. In the following examples, we use the same training and testing dataset as we presented in our previous blog.

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VMware Speedily Resolves Customer Issues in vSAN Performance Using AI

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We in VMware’s Performance team create and maintain various tools to help troubleshoot customer issues—of these, there is a new one that allows us to more quickly determine storage problems from vast log data using artificial intelligence. What used to take us days, now takes seconds. PerfPsychic analyzes storage system performance and finds performance bottlenecks using deep learning algorithms.

Let’s examine the benefit artificial intelligence (AI) models in PerfPsychic bring when we troubleshoot vSAN performance issues. It takes our trained AI module less than 1 second to analyze a vSAN log and to pinpoint performance bottlenecks at an accuracy rate of more than 91%. In contrast, when analyzed manually, an SR ticket on vSAN takes a seasoned performance engineer about one week to deescalate, while the durations range from 3 days to 14 days. Moreover, AI also wins over traditional analyzing algorithms by enhancing the accuracy rate from around 80% to more than 90%.

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vSphere with iSER – How to release the full potential of your iSCSI storage!

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By Mark Ma

With the release of vSphere 6.7, VMware added iSER (iSCSI Extensions for RDMA) as a native supported storage protocol to ESXi. With iSER run over iSCSI, users can boost their vSphere performance just by replacing the regular NICs with RDMA-capable NICs. RDMA (Remote Direct Memory Access) allows the transfer of memory from one computer to another. This is a direct transfer and minimizes CPU/kernel involvement. By bypassing the kernel, we get extremely high I/O bandwidth and low latency. (To use RDMA, you must have an HCA/Host Channel Adapter device on both the source and destination.) In this blog, we compare standard iSCSI performance vs. iSER performance to see how iSER can release the full potential of your iSCSI storage.

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New white paper: Big Data performance on VMware Cloud on AWS: Spark machine learning and IoT analytics performance on-premises and in the cloud

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By Dave Jaffe

A new white paper is available comparing Spark machine learning performance on an 8-server on-premises cluster vs. a similarly configured VMware Cloud on AWS cluster.

Here is what the VMware Cloud on AWS cluster looked like:

Screenshot of cluster configuration

VMware Cloud on AWS configuration for performance tests

Three standard analytic programs from the Spark machine learning library (MLlib), K-means clustering, Logistic Regression classification, and Random Forest decision trees, were driven using spark-perf. In addition, a new, VMware-developed benchmark, IoT Analytics Benchmark, which models real-time machine learning on Internet-of-Things data streams, was used in the comparison. The benchmark is available from GitHub.

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Persistent Memory Performance in vSphere 6.7

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We published a paper that shows how VMware is helping advance PMEM technology by driving the virtualization enhancements in vSphere 6.7. The paper gives a detailed performance analysis of using PMEM technology on vSphere using various workloads and scenarios.

These are the key points that we cover in this white paper:

  • We explain how PMEM can be configured and used in a vSphere environment.
  • We show how applications with different characteristics can take advantage of PMEM in vSphere. Below are some of the use-cases:
    • How PMEM device limits can be achieved under vSphere with little to no overhead of virtualization. We show virtual-to-native ratio along with raw bandwidth and latency numbers from fio, an I/O microbenchmark.
    • How traditional relational databases like Oracle can benefit from using PMEM in vSphere.
    • How scaling-out VMs in vSphere can benefit from PMEM. We used Sysbench with MySQL to show such benefits.
    • How modifying applications (PMEM-aware) can get the best performance out of PMEM. We show performance data from such applications, e.g., an OLTP database like SQL Server and an in-memory database like Redis.
    • Using vMotion to migrate VMs with PMEM which is a host-local device just like NVMe SSDs. We also characterize in detail, vMotion performance of VMs with PMEM.
  • We outline some best practices on how to get the most out of PMEM in vSphere.

Read the full paper here.

Performance Best Practices Guide for vSphere 6.7

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We are pleased to announce the availability of Performance Best Practices for VMware vSphere 6.7. This is a comprehensive book designed to help system administrators obtain the best performance from their vSphere 6.7 deployments.

The book covers new features as well as updating and expanding on many of the topics covered in previous versions.

These include:

  • Hardware-assisted virtualization
  • Storage hardware considerations
  • Network hardware considerations
  • Memory page sharing
  • Getting the best performance with iSCSI and NFS storage
  • Getting the best performance from NVMe drives
  • vSphere virtual machine encryption recommendations
  • Running storage latency-sensitive workloads
  • Network I/O Control (NetIOC)
  • DirectPath I/O
  • Running network latency-sensitive workloads
  • Microsoft Virtualization-Based Security (VBS)
  • CPU Hot Add
  • 4KB native drives
  • Selecting virtual network adapters
  • The vSphere HTML5 Client
  • vSphere web client configuration
  • Pair-wise balancing in DRS-enabled clusters
  • VMware vSphere update manager
  • VMware vSAN performance

The book can be found here.

Also, for a summary of the new performance-related features in vSphere 6.7, refer to What’s New in Performance.

Extreme Performance Series at VMworld 2018

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I’m excited to announce that the “Extreme Performance Series” is back for its 6th year with 14 sessions created and being presented by VMware’s best and most distinguished performance engineers, principals, architects and gurus. You do not want to miss this years program as it’s chalk full of advanced content, practical advice and exciting technical details!

Sessions

Spread across 5 different VMworld tracks, you’ll find these sessions full of performance details that you won’t get anywhere else at VMworld. They’ll also be recorded so if the sessions you want to see aren’t being hosted in your region, you’ll still get access to it.

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What’s New in Performance – VMware vSphere 6.7

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Underlying each release of VMware vSphere are many performance and scalability improvements. The vSphere 6.7 platform continues to provide industry-leading performance and features to ensure the successful virtualization and management of your entire software-defined datacenter.

The What’s New in Performance for vSphere 6.7 white paper highlights significant scale and performance items such as:

  • 2x increase in VMware vCenter Server Operations Per Second over the 6.5 release
  • Support for 1GB Large Memory Pages
  • vmxnet3 enhancements to RSS and VXLAN/Geneve Offloads
  • Performant support of new Persistent Memory offerings

As with each release I’m excited about these new capabilities and the performance each of them offers.

Document: What’s New in Performance for vSphere 6.7

Got a question? Ask below.

 

 

 

 

Oracle Database Performance with VMware Cloud on AWS

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You’ve probably already heard about VMware Cloud on Amazon Web Services (VMC on AWS). It’s the same vSphere platform that has been running business critical applications for years, but now it’s available on Amazon’s cloud infrastructure. Following up on the many tests that we have done with Oracle databases on vSphere, I was able to get some time on a VMC on AWS setup to see how Oracle databases perform in this new environment.

It is important to note that VMC on AWS is vSphere running on bare metal servers in Amazon’s infrastructure. The expectation is that performance will be very similar to “regular” onsite vSphere, with the added advantage that the hardware provisioning, software installation, and configuration is already done and the environment is ready to go when you login. The vCenter interface is the same, except that it references the Amazon instance type for the server.

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