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virtualization

Available Now: Linux VDA 7.15 LTSR!

Since Citrix released the first version of Linux Virtual App and Desktop support in 2015, our Linux VDA has evolved dramatically to enable more and more use cases and support various Linux platforms and versions. Therefore, the number of new …


  

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The Only Virtualization Solution for Skype Meetings Just Got Even Better!

Over a year and a half after Citrix and Microsoft introduced our jointly developed solution for delivering Skype for Business in virtualized environments — whether on-premises or in the cloud — the HDX RealTime Optimization Pack remains the only virtualization …


  

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Citrix SCOM Management Packs — Ready, Steady, GO!

XenApp and XenDesktop 7.15 Long Term Service Release (LTSR) is the second XenApp and XenDesktop LTSR and the first LTSR that is bundled with SCOM Management Packs.

SCOM Management Packs have been a part of the Citrix product family since …


  

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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.

Here are the results for the TeraSort suite:

And for Spark Random Forest decision trees:

Here are the best practices cited in this paper:

  • Reserve about 5-6% of total server memory for ESXi; use the remainder for the virtual machines.
  • Do not overcommit physical memory on any host server that is hosting Big Data workloads.
  • Create one or more virtual machines per NUMA node.
  • Limit the number of disks per DataNode to maximize the utilization of each disk: 4 to 6 is a good starting point.
  • Use eager-zeroed thick VMDKs along with the ext4 or xfs filesystem inside the guest.
  • Use the VMware Paravirtual SCSI (pvscsi) adapter for disk controllers; use all 4 virtual SCSI controllers available in vSphere 6.5.
  • Use the vmxnet3 network driver; configure virtual switches with MTU=9000 for jumbo frames.
  • Configure the guest operating system for Hadoop performance including enabling jumbo IP frames, reducing swappiness, and disabling transparent hugepage compaction.
  • Place Hadoop master roles, ZooKeeper, and journal nodes on three virtual machines for optimum performance and to enable high availability.
  • Dedicate the worker nodes to run only the HDFS DataNode, YARN NodeManager, and Spark Executor roles.
  • Run the Hive Metastore in a separate MySQL database.
  • Set the YARN cluster container memory and vcores to slightly overcommit both resources
  • Adjust the task memory and vcore requirement to optimize the number of maps and reduces for each application.

All details are in the paper.

The post 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 appeared first on VMware VROOM! Blog.

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XenApp & XenDesktop 7.15 LTSR – The Blockbuster Release of the Summer

Virtualization-goers everywhere will be talking about it. Over two decades in the making. More than twelve million lines of field-proven source code. Featuring the latest star capabilities around security, flexibility and user experience. This is the one you’ve been waiting


  

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Two “Layers” To App Layering

Is that too much? Two much?

via GIPHY

Let’s look at the word “demo” for a moment, shall we? Now, I don’t think its origins are from the Latin phrase “Demon,” but given some of my experiences on stage, you …


  

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Time for Another XenApp & XenDesktop Update Webinar

It’s hard to believe that we are already in mid-August! It feels like we were celebrating New Year’s just a few minutes ago (though the calendar proves me wrong). That said, I guess you’d expect things to seem like they’re …


  

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Citrix Linux VDA Can Now Be Provisioned at Scale on Microsoft Azure

Today, I am pleased to announce the availability of Linux VDA Image Service, a new Citrix Cloud Labs service that allows administrators to jump-start their Linux VDA deployment on Microsoft Azure.

This new service comes armed with the peace …


  

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The New Scout 3.0

If you installed XenApp and XenDesktop 7.14.1, you might have noticed a new version of Citrix Scout. Scout makes it easy for Citrix administrators to collect diagnostics and traces. This tool helps administrators obtain common health check recommendations for their …


  

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Estimate the Size of XenApp & XenDesktop Monitoring Database

With each successive release of Citrix XenApp and XenDesktop, monitoring and Analytics gets stronger and adds more information.

Citrix Director — the monitoring and troubleshooting solution for XenApp and XenDesktop — has introduced new monitoring capabilities, like CPU usage, memory


  

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