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Category Archives: Automation

Virtualizing Big Data at VMware IT – Starting Out at Small Scale

The Hadoop-based system running on vSphere that is described here was architected by Rajit Saha, (who provided the material for this blog) and a team from VMware’s IT department.

This article describes the technical infrastructure for a VMware internal IT project that was built and deployed in 2015 for analyzing VMware’s own business data.. Details of the business applications used in the system are not within the scope of this article. The virtualized Hadoop environment and modern analytics project was implemented entirely on the vSphere 6 platform.

The key lesson that we learned from this implementation is that you can start at a small scale with virtualizing big data/Hadoop and then scale the system up over time. You don’t need to wait for a large amount of hardware to become available to get started.

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Updating to VMware Tools 10 – Must Read

In September we announced that VMware Tools 10.0.0 Released and that VMware is now shipping VMware tools outside of the vSphere releases. Since then, we have received a lot of feedback from the community, customers, and internal folks alike. I would like to let everyone know that we have listened and we continue on our path to make VMware Tools lifecycle (and ESXi lifecycle for that matter) easier and less painful than how it may appear today.


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Architecting Virtual SAP HANA Using VMware Virtual Volumes And Hitachi Storage

VMWorld Recap: SAP HANA and VMware Virtual Volumes

This is a follow up to my earlier VMWorld blog; “Virtualizing SAP HANA Databases Greater Than-1TB On vSphere-5-5”, where I discussed SAP Multi-Temperature Data Management strategies and techniques which can significantly reduce the size and cost associated with SAP HANA’s in-memory footprint. This blog will focus on Software-Defined Storage and the need for VMware Virtual volumes when deploying Mission Critical Applications/Databases like SAP HANA as discussed in my VMWorld session.

Multi-Temperature Data Management Is By Definition Software-Defined Storage

SAP and VMware customers who plan on leveraging multi-temperature strategies, where data is classified by frequency of access as either hot, warm or cold depending on data usage is the essence of Software-Defined Storage. This can also be equated to EMC’s Information Lifecycle Management which examines the value of data to the business over time. To bring the concept of the Software-Defined Data Center and more precisely Software-Defined Storage to reality, see Table 1. This table depicts the various storage options for SAP HANA so customers can create an architecture that aligns with the business and its applications demands.

Table 1: Multi-Temperature Storage Options with SAP HANA


Planning Your Journey To Software-Defined Storage

As we get into the various storage options for SAP HANA, VMware has made it very easy to create and deploy software defined storage in the form of Virtual Volumes. However I want to stress the actual definitions of how the storage should be abstracted is a collaborative task, at a minimum you must involve the storage team, VI-Admins, application owners, and dba’s in order to create an optimized virtual architecture; this should not be a siloed task.

In my previous post I discussed the storage requirements for SAP HANA In-Memory, Dynamic Tiering, Near-Line Storage, and the Archiving Components; one last option I did not cover in Table 1 is Data Aging which is specific to SAP Business Suite. Under normal operations SAP HANA does not preload data into memory, data is loaded upon first access, so the first time you access data its always off disk.

With Data Aging you can essentially mark data so its never loaded into memory and will always reside on disk. This is not available on all modules for Business Suite, so please check with SAP for availability and roadmap with respect to Data Aging.

Essentially this is another SAP HANA feature which enables customers to reduce and manage their memory footprint more efficiently and effectively. The use of Data Aging can change the design requirements of your Software-Defined Storage, if Data Aging becomes more prevalent in your SAP Landscape, VMware Virtual Volumes can be used to address the changing storage requirements of the application by seamlessly migrating data between different classes of software-defined storage or VMDKs.

VMware Virtual Volumes Transform Storage By Aligning With SAP HANA’s Requirements

Now lets get into Virtual Volumes and the problems they solve, with Virtual Volumes the fundamental model is centered around provisioning storage based on the application needs rather than the underlying infrastructure. When deploying SAP HANA using the Tailored Data Center Integration model, the storage KPIs can be quite complex, so how do customers translate latency, throughput for reads – writes – and updates, at various block sizes to the storage layer?

Plus how does a customer address the storage requirements for SAP HANA’s entire data life cycle, whether you are planning on using Dynamic Tiering, with or without Near-Line-Storage and what is the archiving strategy storage requirements as well. Also some of the storage requirements do tie back to the compute layer, as an example with Dynamic Tiering if you plan on using Row Level Versioning there is a compute to memory relationship for storage that comes into play when sizing

Addressing and achieving these design goals using an infrastructure centric model can be quite difficult because you are tied to physical LUNs and trust me, with mission critical databases, you will always have database administrators fighting over LUNs with the lowest numbers because of the concerns around radial density. This leads to tremendous waste when provisioning storage using an infrastructure centric model.

VMware Virtual Volumes significantly reduces the storage design complexity by using an Application Centric model because you are not dealing with storage at the LUN level, instead vSphere admins use policies to express the application requirements to the storage array, then the storage array maps storage containers to the application requirements.

What are VMware Virtual Volumes?

At a high level I’ll go over the architecture and components of Virtual Volumes, this blog is not intended to be a deep dive into Virtual Volumes, instead my goal is to convey that mission critical uses cases for VVOLS and software-defined storage are real. For an excellent white paper on Virtual Volumes see; “VMware vSphere Virtual Volumes Getting Started Guide”.

As shown in Figure 1., Virtual Volumes are a new type of virtual machine object which are created and stored natively on the storage array. The Vendor Provider also known as the VASA Provider, which are the vSphere Storage APIs for Storage Awareness (VASA) that provide the storage awareness services and mediates out of the box communications between vCenterServer and EXi Hosts on one side and the storage system on the other side.

The storage containers are pools of raw storage that a storage system can provide to virtual volumes and unlike LUNS and NFS, they do not require pre-configured volumes on the storage side. Also with virtual volumes you still have the functionality you would expect when using native VMDKs

Virtual Datastores represents a storage container in a vCenter Server instance, so it’s a 1:1 mapping to the storage systems storage container. The ESXi Hosts have no direct access to the virtual volumes on the storage side, so they use a logical I/O proxy called a protocol endpoint and as you would expect VVOLs are compatible with industry standard protocols, iSCSI, NFS, FC, and FCoE

The Published Storage Capabilities will vary by storage vendor depending on which capabilities have been exposed and implemented. In this blog we will be looking at the exposed capabilities of Hitachi Data Systems like latency, throughput, Raid Level, Drive Type/Speed, IOPS, and Snapshot frequency to mention a few.

Figure 1: vSphere Virtual Volumes Architecture and Components


VMware HDS: Creating Storage Containers, Virtual Volumes, and Profiles for Virtual SAP HANA

Now Virtual Volumes are an Industry-wide Initiative, essentially a who’s who of the storage industry are participating in this initiative, however this next section will be representative of the work done with Hitachi Data Systems

And again the guidance here is collaboration when architecting software-defined storage for SAP HANA landscapes and for that matter any mission critical application or database. Because the beauty of software defined storage is once created and architecture correctly you can then provision your virtual machines in an automated and consistent manner.

So in the spirit of collaboration, I got together with Hitachi’s SAP alliance team, their storage team, and database architects and we came up with these profiles, policies, and containers to use when deploying SAP HANA landscapes.

We had several goals when designing this architecture; one was to use virtual volumes to address the entire data life cycle of SAP HANA, the in-memory component, Dynamic Tiering, Near-Line storage, and archiving or any supported combination of the above when creating a SAP HANA landscape. And secondly we wanted to enable rapidly provisioning of SAP HANA landscapes, so we created profiles, policies, and containers which could be used to deploy SAP HANA databases whose in-memory component could range from 512GB to 1TB in size.

I’ll review some of the capabilities HDS exposed which were used for this architecture:

  • Interestingly enough we were able to meet the SAP HANA in-memory KPIs using Hitachi Tier 2 storage which consisted of 10K SAS drives for both log and data files, as well as for the Operating System and the SAP HANA shared file system. This also simplified the design. We then used high density SAS drives for the backup areas
  • We enabled automatic storage managed snapshots for HANA data, log and the OS; and set the Snapshot frequency based on the classifications of Critical, Important, or Best Effort.
  • So snapshots for the data and log were classified as Critical while the OS was classified as Important and the backup area we didn’t snapshot at all
  • We also tagged this storage as certified, capturing the model and serial number, since the SAP HANA in-memory component requires certified storage. We wanted to make sure that when creating HANA VM’s you’re always pulling from certified storage containers.
  • The Dynamic Tiering and NLS storage had similar requirements so could be provisioned from the same containers and since these are disk based columnar databases we selected Tier 1 storage SSDs for the data files based on the random read/write patterns
  • And stuck with SAS drives for the log files since sequential workload don’t benefit much from SSDs. Again because of the disk based access we selected Tier 2 to satisfy the IOPS and Latency requirements.
  • Then finally for the archiving containers we used the lowest cost & highest density storage, pretty much just a file system.

Now there’s just too much information to cover in this effort with HDS but for those of you interested, VMware and Hitachi we will be publishing a Co-Logo White Paper which will be a much deeper dive into how we architected these landscapes so customers can do this almost out of the box.

Deploying VMware Software-Defined Storage With vSphere and Hitachi Command Suite

Example: SAP HANA Dynamic Tiering and Near-Line Storage Tiers. These next couple of screen captures will show how simple virtual volumes are to deploy once architected correctly

Figure 2: Storage Container Creation: SAP HANA DT and NLS Tier


Figure 3: Create Virtual Machine Storage Policies SAP HANA DT/NLS Data/Log File


Figure 4: Create New SAP HANA DT VM Using VVOLS Policies With Hitachi Storage


Addressing Mission Critical Use Cases with VMware Software-Defined Storage

SAP HANA and Multi-Temperature Data Management is the poster child for mission critical software-defined storage use cases. VMware Virtual Volumes solves the complexities and simplifies storage provisioning by using an application centric model rather than an infrastructure centric model.

The SAP HANA in-memory component is not yet certified for production use on vSphere 6.0, however Virtual Volumes can be used for SAP HANA Dynamic Teiring, Near-Line Storage, and Archiving. So my advice to our customers is to start architecting now, get together with your storage admins, VI Admins, application owners, and database administrators to create containers, policies, and profiles correctly so when vSphere 6.0 is certified you are ready to “Run SAP HANA Simple”.



Big Data on vSphere with HBase

This article describes a set of performance tests that were conducted on HBase, a popular data management tool that is frequently used with Hadoop, running on VMware vSphere 6 and provisioned by the vSphere Big Data Extensions tool. The work described here was done by Xinhui Li, who is a staff engineer in the Big Data team in VMware’s R&D Labs in Beijing. Xinhui’s biography and background details are given at the end of the article.

What is HBase?

HBase is an Apache project that is designed to handle very large amounts of data on the Hadoop platform. HBase is often described as providing the functionality of a NoSQL database running on top of Hadoop. It combines the scalability of Hadoop, through its use of the Hadoop Distributed File System (HDFS) to store the data, with real-time data access to the data. HBase can handle billions of rows of data and very large numbers of columns. Along with Hadoop, HBase runs on clusters of commodity hardware that form a distributed system. The HBase architecture is made up of RegionServers that run on the worker nodes while the HBase Master Server controls them.

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PowerCLI Webcast

Our next webcast in the vSphere 6 webcast series is all about increased efficiency of running your data center via automation.  Brian Graf, VMware’s PowerCLI guru, will discuss what’s new in vSphere 6 for PowerCLI as well as show off some tips and tricks that will wow you.

This webcast takes place July 7 at 9am PST.  Register for the webcast today!

Configure Auto Deploy Rules – PowerCLI

In the previous post Configure DHCP and TFTP for Auto Deploy, we discussed how to setup your DHCP and TFTP servers to allow your ESX hosts to PXE boot. However, once an ESX host boots, it will need directions to know what to boot. This is where Auto Deploy Rules come in. Continue reading

Big Data on vSphere : Two Customer Case Study White Papers Published


Two new white papers are now available on the work done at Adobe on virtualizing Hadoop. The VMware-authored paper,  Adobe Deploys Hadoop as a Service on VMware vSphere, focuses on the business background and justifications for virtualizing the workload. It also talks about implementing Hadoop-as-a-Service by the central Technical Operations function to satisfy the needs of the business units and data analysis groups that require Hadoop as a platform. This paper also gives details about the use of the vSphere Big Data Extensions tool which was used heavily in the project, as well as the connection to vRealize Automation that forms the basis for the cloud offering at Adobe.

The second, complementary white paper, on the same architecture, Virtualizing Hadoop in Large-Scale Infrastructureswas written by the EMC consulting team that supported the project. The EMC paper, with the title “Virtualizing Hadoop in Large-Scale Infrastructures”, focuses on the technical reference architecture for the Proof-of-Concept conducted in late 2014, the results of that POC, the performance tuning work and the physical topology that was deployed using Isilon storage. The two papers were written in concert by the organizations and should be read together for a full picture of the Hadoop virtualization project. This system is now live at Adobe Digital Marketing, hosted on their Virtual Private Cloud and it is being used by different groups within the big data community there. The papers together provide an outline reference architecture for use in other installations also. Watch this space, there are more technical case studies in the works.

Speaking of technical reference material for Hadoop on vSphere, here is the current list of technical papers and websites that are now available for people to learn more about this particular subject – for your reference:

Big Data/Hadoop on VMware vSphere – Reference Materials

Deployment Guides

Reference Architectures

Customer Case Studies

Performance Studies

There are some very useful best practices in the first two technical papers.

vSphere Big Data Extensions (BDE)

Other vSphere Features and Big Data

Configure DHCP and TFTP for Auto Deploy

In the previous post, we covered Enabling Auto Deploy on vCenter Server Appliance 6.

There are several more steps that need to be taken to get Auto Deploy configured correctly.

In this post we discuss the next step in our journey to running Auto Deploy in your environment, which is Continue reading

vSphere Hardening Guide 6.0 Public Beta 1 available

I’m happy to announce that the vSphere 6 Hardening Guide Public Beta 1 is now available.

The guide is being provided as Excel spreadsheet. I’m also making a PDF doc available for easier viewing. In addition,  I’ve also included an Excel spreadsheet of the guidelines that have moved out of the guide and into documentation. THIS IS INCOMPLETE. We are still working on some of that content. (that’s why this is a beta!)

Please read the blog on the changes that have happened to the guide. LOTS of changes and the blog will explain.

vSphere 6.0 Hardening Guide – Overview of coming changes | VMware vSphere Blog – VMware Blogs

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Enable Auto Deploy on vCenter Server Appliance (vCSA) 6

Many customers are now converting over to use the vCenter Server Appliance 6.0 since vSphere 6 has reached feature parity with the Windows vCenter Server.

For those of you who are new to using the appliance, I figured I would walk you through setting up the Auto Deploy portion of the server. Continue reading