hyper-v

You are currently browsing articles tagged hyper-v.

Does your Building Block need a Fabric? <- Part 6

Okay, so this is all well and good, but you have been reading these posts and thinking that your environment is nowhere near the size of my example so Building Blocks are not for you. The fact is you can make individual Building Blocks quite a bit smaller or larger than the example I used in these posts and I’ll use a couple more quick examples to illustrate.

Small Environment: In this example, we’ll break down a 150 VM environment into three Building Blocks to provide the availability benefit of multiple isolated blocks. Additional Building Blocks can be deployed as the environment grows.

150 Total VMs deployed over 12 months
(2 vCPUs/32GB Disk/1GB RAM/25 IOPS per VM)

    • 300 vCPUs
    • 150GB RAM
    • 4800 GB Disk Space
    • 3750 Host IOPS

Assuming 3 Building Blocks, each Building Block would look something like this:

    • 50 VMs per Building Block
    • 2 x Dual CPU – 6 Core Servers (Maintains the 4:1 vCPU to Physical thread ratio)
    • 24-32GB RAM per server
    • 19 x 300GB 10K disks in RAID10 (including spares) — any VNXe or VNX model will be fine for this
      • >1600GB Usable disk space (this disk config provides more disk space and performance than required)
      • >1250 Host IOPS

Very Large Environment: In this example, we’ll scale up to 45,000 VMs using sixteen Building Blocks to provide the availability benefit of multiple isolated blocks. Additional Building Blocks can be deployed as the environment grows.

45000 Total VMs deployed over 48 months
(2 vCPUs/32GB Disk/4GB RAM/50 IOPS per VM)

    • 90000 vCPUs
    • 180,000 GB RAM
    • 1,440,000 GB Disk Space
    • 2,250,000 Host IOPS

Assuming 4 Building blocks per year, each Building Block would look something like this:

    • 2812 VMs per Building Block
    • 18 x Quad CPU – 10 Core Servera plus Hyperthreading (Maintains the 4:1 vCPU to Physical thread ratio)
    • 640GB Ram per server
    • 1216 x 300GB 15K disks in RAID10 (including spares) — one EMC Symmetrix VMAX for each Building Block
      • >90000GB Usable disk space (the 300GB disks are the smallest available but still too big and will provide quite a bit more space than the 90TB required. This would be a good candidate for EMC FASTVP sub-LUN tiering along with a few SSD disks, which would likely reduce the overall cost)
      • >140,000 Host IOPS

Hopefully this series of posts have shown that the Building Block approach is very flexible and can be adapted to fit a variety of different environments. Customers with environments ranging from very small to very large can tune individual Building Block designs for their needs to gain the advantages of isolated, repeatable deployments, and better long term use of capital.

Finally, if you find the benefits of the Building Block approach appealing, but would rather not deal with the integration of each Building Block, talk with a VCE representative about VBlock which provides all of the benefits I’ve discussed but in a pre-integrated, plug-and-play product with a single support organization supporting the entire solution.

Does your Building Block need a Fabric? <- Part 6

Tags: , , , , , , , , , , , , , , , , , , , , , ,

Sizing your Building Block <- Part 5 -> I’m too small for Building Blocks

You may have noticed in the last installment that I did not include any FibreChannel switches in the example BOM. There are essentially three ways to deal with the SAN connectivity in a Building Block and there are advantages as well as disadvantages to each. (Note: this applies to iSCSI as well)

1.) Use switches that already exist in your datacenter: You can attach each storage array and each server back to a common fabric that you already have (or that you build as part of the project) and zone each of the Building Block’s servers to their respective storage array.

  • Advantages:
    • Leverage any existing fabric equipment to reduce costs and centralize management
    • Allow for additional servers to be added to each Building Block in the future
    • Allow for presenting storage from one Building Block to servers in a different Building Block (useful for migrations)
  • Disadvantages:
    • Increases complexity – Requires you to configure zoning within each Building Block during deployment
    • Increases chances for human error that could cause an outage – Accidentally deleting entire Zonesets or VSANs is not as uncommon as you might think
    • Reduces the availability isolation between Building Blocks – The fabric itself becomes a point-of-failure common to all Building Blocks.

2.) Deploy a dedicated fabric within each Building Block: Since each Building Block has a known quantity of storage and server ports, you can easily add a dual-switch/fabric into the design. In our example of 9 hosts you’d need a total of 18 ports for hosts and maybe 8 ports for the storage array for a combined total of 26 switch ports. Two 16-port switches can easily accommodate that requirement.

  • Advantages:
    • Depending on the switches used, it could allow for additional servers in each Building Block in the future
    • Allow for presenting storage from one Building Block to servers in a different building block (useful for migrations) by connecting ISLs between Building Blocks
    • Maintains the Building Block isolation by not sharing the fabric switches across Building Blocks.
  • Disadvantages:
    • Increases complexity – Requires you to configure zoning within each Building Block during deployment
    • Increases chances for human error that could cause an outage – Again, accidentally deleting entire Zonesets or VSANs is not as uncommon as you might think

3.) Dispense with the fabric entirely: Since Building Blocks are relatively small, resulting in fewer total initiator/target pairs, it’s possible in some cases to directly attach all of the hosts to the storage array. In our example, the nine hosts need eighteen ports and the VNX5700 supports up to twenty four FC ports. This means you can directly attach all of the hosts to the array and still have six remaining ports on the array for replication, etc. Different arrays from EMC as well as other vendors will have various limits on the number of FC ports supported. Also, not all vendors support direct attached hosts so you’ll need to check that with your storage vendor of choice to be sure.

  • Advantages:
    • Maintains the Building Block isolation by not sharing the fabric switches across Building Blocks.
    • Simplifies deployment by eliminating the need to do any zoning at all and effectively eliminates any port queue limits (HBA elevator depth settings)
    • Simplifies troubleshooting by eliminating the fabric (buffer to buffer credits, bandwidth, port errors, etc) from the IO path.
  • Disadvantages:
    • Limits the number of hosts per Building Block by the maximum number of ports supported by the storage array.
    • More difficult to non-disruptively migrate VMs between Building Blocks since storage cannot be shared across. (If all Building Blocks are in the same Virtual Data Center in VMWare vSphere, you can still live-migrate VMs via the IP network between Building Blocks using Storage vMotion)

If you decide that the host count limit is okay, and either non-disruptive migration between Building Blocks is unnecessary or Storage vMotion will work for you, then eliminating the fabric can reduce cost and complexity, while improving overall availability and time to deploy. If you need the flexibility of a fabric, I personally like using dedicated switches in each building block. Cisco and Brocade both offer 1U switches with up to 48 ports per switch that will work quite well. Always deploy two switches (as two fabrics) in each Building Block for redundancy.

Okay, so you’ve managed to calculate the size of your environment, how much time it will take you to virtualize it, the number of Building Blocks you need, and the specifications for each Building Block, including whether you need a fabric. Now you can submit your budget, get your final quotes, and place orders. Once the equipment arrives it’s time to implement the solution.

When your first Building Block arrives, it would be a valuable use of time to learn how to script the configuration for each component in the Building Block. An EMC VNX array can be completely configured using Naviseccli or PowerShell, from the Storage Pool and LUN provisioning to initiator registration and Host/LUN masking. VMWare vSphere can similarly be configured using scripts or PowerShell. If you take the time to develop and test your scripts against your first Building Block, then you can use those scripts to quickly stand up each additional Building Block you deploy. Since future Building Blocks will be nearly identical, if not entirely identical, the scripts can speed your deployment time immensely.

EMC Navisphere/Unisphere CLI (for VNX) is documented fully in the VNX Command Line Interface (CLI) Reference for Block 1.0 A02. This document is available on EMC PowerLink at the following location:

Home > Support > Technical Documentation and Advisories > Software ~ J-O ~ Documentation > Navisphere Management Suite > Maintenance/Administration

Be sure to leverage any storage vendor plug-ins available to you for your chosen hypervisor (VMWare, Hyper-V, etc) to improve visibility up and down the layers and reduce the number of management tools you need to use on a daily basis.

For example, EMC Unisphere Manager, the array management UI running on the VNX storage array, includes built-in integration with VMWare and other host operating systems. Unisphere Manager displays the VMFS datastores, RDMs, and VMs that are running on each LUN and a storage administrator can quickly search for VM names to help with management and/or troubleshooting tasks.

EMC also provides free downloadable plug-ins for VMWare vSphere and Hyper-V so server administrators can see what storage arrays and LUNs are behind their VMs and datastores. The plug-ins also allow administrators to provision new LUNs from the storage array through the plug-ins without needing access to the array management tools.

Depending on which storage vendor you choose, if you build a fabric-less Building Block, you may be able to do all of your server and storage administration from vCenter if you leverage the free plug-ins.

Sizing your Building Block <- Part 5 -> I’m too small for Building Blocks

Tags: , , , , , , , , , , , , , , , , , , , , , ,

How many Building Blocks? <- Part 4 -> Does your Building Block need a Fabric?

Now that we know we’ll be deploying about 562 VM’s per Building Block we can use the other metrics to determine the requirements for a single block.

  • Since 562 VMs is about 12.5% of the 4500 total VMs, we then calculate 12.5% of the other metrics determined in the last post.
    • 12.5% of 9000 vCPUs = 1125 vCPUs
    • 12.5% of 4500GB RAM = 562GB RAM
    • 12.5% of 225,000 IOPS = 28125 Host IOPS
    • 12.5% of 562TB = 70TB Usable Disk capacity

First we’ll size the compute layer of the Building Block

  • At 4:1 vCPUs per Physical CPU thread you’d want somewhere around 281 hardware threads per Building Block. Using 4-socket, 8-core servers (32 cores per server) you’d need about 9 physical servers per building block. The number of vCPUs per physical CPU thread affects the % CPU Ready time in VMWare vSphere/ESX environments.
  • For 562GB of total RAM per Building Block, each server needs about 64GB of RAM
  • Per standard best practices, a highly available server needs two HBAs, more than two can be advantageous with high IOPS loads.

Next, we’ll calculate the storage layer of the Building Block

  • Assuming no cache hits, the backend disk load for 28,125 Host IOPS @ 50:50 read/write looks like the following:
    • RAID10 : 28125/2 + 28125/2*2 = 42187 Disk IOPS
    • RAID5 : 28125/2 + 28125/2*4 = 70312 Disk IOPS
    • RAID6 : 28125/2 + 28125/2*6 = 98437 Disk IOPS
  • If you calculate the number of disks required to meet the 70TB Usable in each RAID level, and the # of disks needed for both 10K RPM and 15K RPM disks to meet the IOPS for each RAID level, you’ll eventually find that for this specific example, using EMC Best Practices, 600GB 10K RPM SAS disks in RAID10 provides the least cost option (317 disks including hot spares). Since 10K RPM disks are also available in 2.5” sizes for some storage systems, this also provides the most compact solution in many cases (29 Rack Units for an EMC VNX storage array that has this configuration). In reality this is a very conservative configuration that ignores the benefits of storage array caching technologies and any other optimizations available, it’s essentially a worst case scenario and it would be beneficial to work with your storage vendor’s performance group to perform a more intelligent modeling of your workload.
  • Finally, you’ll need to select a storage array model that meets the requirements. Within EMC’s portfolio, 317 disks necessitate an EMC VNX5700 which will also have more than enough CPU horsepower to handle the 28125 host IOPS requirement.

At this point you’ve determined the basic requirements for a single Building Block which you can use as a starting point to work with your vendors for further tuning and pricing. Your vendors may also propose various optimizations that can help save you money and/or improve performance such as block-level tiering or extended SSD/Flash based caching.

Example bill-of-materials (BOM):

  • 9 x Quad-CPU/8-Core servers w/64GB RAM each
  • 2 x Single port FibreChannel HBAs
  • 1 x EMC VNX5700 Storage Array with 317 x 300GB 2.5” 10K SAS disks

Wait, where’s the fabric?

How many Building Blocks? <- Part 4 -> Does your Building Block need a Fabric?

Tags: , , , , , , , , , , , , , , , , , , , , , ,

The Building Block Approach <- Part 3 -> Sizing your Building Block

The key to sizing Building Blocks is to calculate the ratio between the compute and storage metrics. First you need to take a look at the total performance and disk space requirements for the whole environment, similar to the below example:

  • Total # of Virtual Machines you expect to be hosting (example: 4500 VMs)
  • Total Virtual CPUs assigned to all Guest VMs (average of 2 vCPUs per VM = 9000 vCPUs)
  • Total Memory required across all Guest VMs (average of 1GB per VM = 4.5TB)
  • Total Host IOPS needed at the array for all Guest VMs (average of 50 IOPS per VM = 225,000 Host IOPS)
    • You will need to have a read/write ratio with this as well (we will use 50:50 for these examples)
  • Total Disk Storage required for all Guest VMs. (average of 125GB per VM = 562TB)

Once you have the above data, you need to decide how many Building Blocks you want to have once the entire environment is built out. There are several things to consider in determining this number:

  • How often you want to be deploying additional Building Blocks (more on this below)
  • Your annual budget (I’m ignoring budget for this example, but your budget may limit the size of your deployment each year)
  • How many VMs you think you can deploy in a year (we’ll use 2250 per year for a two year deployment)

Some of these are pretty subjective so your actual results will vary quite a bit, but based what I’ve seen I do have some recommendations.

  • In order to take advantage of the availability isolation inherent in the Building Block approach, you’ll want to start with at least two Building Blocks and then add them one or two at a time depending on how you want to spread your server farms across the infrastructure.
  • Depending on the size of each Building Block you may want to keep Building Block deployments down to one every 3-6 months. That gives you ample time to build each block correctly and hopefully leaves time between deployments to monitor and adjust the Building Blocks.

That said I’d lean toward 4 to 6 Building Blocks per year. Of course this is just my opinion and your mileage may vary. For our example of 4500 VMs over 2 years @ 4 Building Blocks per year. we’ll end up with 8 Building Blocks with about 562 VMs each.

The Building Block Approach <- Part 3 -> Sizing your Building Block

Tags: , , , , , , , , , , , , , , , , , , , , , ,

Build your own Private Cloud <- Part 2 -> How many Building Blocks

Since server virtualization abstracts the physical hardware from the operating systems and applications, essential for Cloud Infrastructures (also known as Infrastructure-as-a-Service), it’s ideally suited for breaking down the physical infrastructure into Building Blocks. Put simply, Building Blocks are repeatable, pre-designed mixes of storage, CPU, and memory.

There are several advantages to the Building Block approach that I’ll point out here:

  1. Rather than dropping a huge amount of capital up front on the entire infrastructure you need over the long haul, some of which will not be used at first, you can start with a smaller capital outlay today, then make multiple similarly small capital purchases only as needed. Further, when the hardware in a single Building Block reaches the end of its life (for any number of reasons), only that one Building Block will need to be refreshed at that time rather than a wholesale replacement of the entire environment.
  2. In an environment where virtualization is a new endeavor, sizing the compute, memory, and storage required is really an educated guess. As each Building Block is consumed, the real-world performance can be analyzed and adjusted for future Building Blocks to more closely match your specific workload.
  3. Building Blocks are inherently isolated which creates natural performance and availability boundaries. This can be leveraged for web and application server farms by spreading nodes of each farm across multiple Building Blocks. In the event of a catastrophic failure of one Building Block, due to major software bug affecting the cluster or the failure of an entire storage array for some reason, nodes of the server farm not hosted on the failed Building Block will be unaffected.
  4. The list price for storage arrays and servers goes down over time. If your growth is similar to many of my customers, where full build out of the physical infrastructure will not be required until 2-3 years after the start of the project, the acquisition cost of each individual Building Block will decrease over time, saving you money overall.
  5. In many cases, and due to a variety of factors, the cost to upgrade a storage array is higher than the cost to purchase the capacity with a new array. Upgrades also add complexity, complicate asset depreciation, and warranty renewals. The Building Block approach eliminates the majority of upgrades and the associated complexity.

Each Building Block can be maintained in its original build state or upgraded independent of the other building blocks so, for example, you don’t have to worry about upgrading every server in your datacenter with new HBA drivers if you decide to upgrade the storage array firmware on one array. You would only need to upgrade the servers in that arrays’ Building Block.

You may be thinking that your environment is not large enough to use a Building Block approach, but the more I worked on this project, the more I realized that Building Blocks can be adjusted to fit even very small environments. I’ll go into that a bit more later.

Build your own Private Cloud <- Part 2 -> How many Building Blocks

Tags: , , , , , , , , , , , , , , , , , , , , , ,

Part 1 -> The Building Block Approach

As 2011 wraps up and I have a little time at home over the holidays, I’ve been reflecting on some of the customer projects I’ve worked on over the past year. Cloud computing and EMC’s vision for the “Journey to the Private Cloud” have been hot topics this year and of the various projects I’ve worked on this past year, one stands out to me as something that could be used as a blueprint for others who want to deploy their own Private Cloud but may not know how to start.

I have been working with a customer with approximately 10,000 servers that support their business and for all intents had zero virtualization as recent as 2010.  As most customers already know, they thought it would be good to begin virtualizing their environment to drive up asset utilization and flexibility while bringing down costs.  In the past, they’ve experimented with multiple server virtualization solutions (such as VMWare ESX and Microsoft Hyper-V) with limited success and had all but abandoned the idea.  A change in leadership in late 2010 brought a top-down initiative to virtualize wherever possible, but in order to instill confidence in virtualized environments within the various business units, the virtual infrastructure needed to be reliable and performant.

The customer spent the latter half of 2010 looking at their existing physical environment, finding that about 80% of the 10,000 servers were various application, file, and web servers; the remaining 20% being various database servers (mostly MS SQL).  Moving an infrastructure this large into a Private Cloud model would take several years and, further adding to the challenge, the DBA teams were particularly wary about virtualizing their database servers.  That said, the newly formed Virtualization and Cloud team set a goal of virtualizing the approximately 8,000 non-database servers over 36 months, starting out with dev/test and gradually adding production and tier-1 applications until only the database servers remained on physical infrastructure.  They believe that if they prove success with virtualization during this first 3 years, the DBAs will be more willing to begin virtualizing their systems, plus there should be more knowledge and tools in the public domain for managing virtual database instances by then.

To accomplish all of their goals, the customer leveraged some experience that individual team members had gained from prior environments to come up with a Building Block based deployment.  I worked with them to finalize the design and sizing for the each Building Block and throughout the year have helped analyze the performance of the deployed infrastructure to help determine how the Building Blocks can be optimized further.  Through the next several posts, I will explain the Building Block approach, detailing the benefits, some of the considerations, and some thoughts around sizing.  I hope that this information will be useful to others.  The content is mostly vendor agnostic except for some example data that uses EMC specific storage best practices.

Part 1 -> The Building Block Approach

Tags: , , , , , , , , , , , , , , , , , , , , , ,

I started this post before I started working for EMC and got sidetracked with other topics.  Recent discussions I’ve had with people have got me thinking more about orchestration of data protection, replication, and disaster recovery, so it was time to finish this one up…

———————————–

Prior to me coming to work for EMC, I was working on a project to leverage NetApp and EMC storage simultaneously for redundancy.  I had a chance to put various tools from EMC and NetApp into production and have been able to make some observations with respect to some of the differences.  This is a follow up my previous NetApp and EMC posts…

NetApp and EMC: Real world comparisons
NetApp and EMC: Startup and First Impressions
NetApp and EMC: ESX and Exchange 2007 CCR
NetApp and EMC: Exchange 2007 Replication

Specifically this post is a comparison between NetApp SnapManager 5.x and EMC Replication Manager 5.x.  First, here’s a quick background on both tools based on my personal experience using them.

Description

EMC Replication Manager (RM) is a single application that runs on a dedicated “Replication Manager Server.”  RM agents are deployed to the hosts of applications that will be replicated.  RM supports local and remote replication features in EMC’s Clariion storage array, Celerra Unified NAS, Symmetrix DMX/V-Max, Invista, and RecoverPoint products.  With a single interface, Replication Manager lets you schedule, modify, and monitor snapshot, clone, and replication jobs for Exchange, SQL, Oracle, Sharepoint, VMWare, Hyper-V, etc.  RM supports Role-Based authentication so application owners can have access to jobs for their own applications for monitoring and managing replication.  RM can manage jobs across all of the supported applications, array types, and replication technologies simultaneously.  RM is licensed by storage array type and host count. No specific license is required to support the various applications.

NetApp SnapManager is actually a series of applications designed for each application that NetApp supports.  There are versions of SnapManager for Exchange, SQL, Sharepoint, SAP, Oracle, VMWare, and Hyper-V.  The SnapManager application is installed on each host of an application that will be replicated, and jobs are scheduled on each specific host using Windows Task Scheduler.  Each version of SnapManager is licensed by application and host count.  I believe you can also license SnapManager per-array instead of per-host which could make financial sense if you have lots of hosts.

Commonality

EMC Replication Manager and NetApp SnapManager products tackle the same customer problem–provide guaranteed recoverability of an application, in the primary or a secondary datacenter, using array-based replication technologies.  Both products leverage array-based snapshot and replication technology while layering application-consistency intelligence to perform their duties.  In general, they automate local and remote protection of data.  Both applications have extensive CLI support for those that want that.

Differences

  • Deployment
    • EMC RM – Replication Manager is a client-server application installed on a control server.  Agents are deployed to the protected servers.
    • NetApp SM – SnapManager is several applications that are installed directly on the servers that host applications being protected.
  • Job Management
    • EMC RM – All job creation, management, and monitoring is done from the central GUI. Replication Manager has a Java based GUI.
    • NetApp SM – Job creation and monitoring is done via the SnapManager GUI on the server being protected.  SnapManager utilizes an MMC based GUI.
  • Job Scheduling
    • EMC RM – Replication Manager has a central scheduler built-in to the product that runs on the RM Server.  Jobs are initiated and controlled by the RM Server, the agent on the protected server performs necessary tasks as required.
    • NetApp SM – SnapManager jobs are scheduled with Windows Task Scheduler after creation.  The SnapManager GUI creates the initial scheduled task when a job is created through the wizard.  Modifications are made by editing the scheduled task in Windows task scheduler.

So while the tools essentially perform the same function, you can see that there are clear architectural differences, and that’s where the rubber meets the road.  Being a centrally managed client-server application, EMC Replication Manager has advantages for many customers.

Simple Comparison Example: Exchange 2007 CCR cluster
(snapshot and replicate one of the two copies of Exchange data)

With NetApp SnapManager, the application is installed on both cluster nodes, then an administrator must log on to the console on the node that hosts the copy you want to replicate, and create two jobs which run on the same schedule.  Job A is configured to run when the node is the active node, Job B is configured to run when the node is passive.  Due to some of the differences in the settings, I was unable to configure a single job that ran successfully regardless of whether the node was active or passive.  If you want to modify the settings, you either have to edit the command line options in the Scheduled Task, or create a new job from scratch and delete the old one.

With EMC Replication Manager, you deploy the agent to both cluster nodes, then in the RM GUI, create a job against the cluster virtual name, not the individual node.  You define which server you want the job to run on in the cluster, and whether the job should run when the node is passive, active, or both.  All logs, monitoring, and scheduling is done in the same RM GUI, even if you have 50 Exchange clusters, or SQL and Oracle for that matter.  Modifying the job is done by right-clicking on the job and editing the properties.  Modifying the schedule is done in the same way.

So as the number of servers and clusters increases in your environment, having a central UI to manage and monitor all jobs across the enterprise really helps.  But here’s where having a centrally managed application really shines…

But what if it gets complicated?

Let’s say you have a multi-tier application like IBM FileNet, EMC Documentum, or OpenText and you need to replicate multiple servers, multiple databases, and multiple file systems that are all related to that single application.  Not only does EMC Replication Manager support SQL and Filesystems in the same GUI, you can tie the jobs together and make them dependent on each other for both failure reporting and scheduling.  For example, you can snapshot a database and a filesystem, then replicate both of them without worrying about how long the first job takes to complete.  Jobs can start other jobs on completely independent systems as necessary.

Without this job dependence functionality, you’d generally have to create scheduled tasks on each server and have dependent jobs start with a delay that is long enough to allow the first job to complete while as short as possible to prevent the two parts of the application from getting too far out of sync.  Some times the first job takes longer than usual causing subsequent jobs to complete incorrectly.  This is where Replication Manager shows it’s muscle with it’s ability to orchestrate complex data protection strategies, across the entire enterprise, with your choice of protection technologies (CDP, Snapshot, Clone, Bulk Copy, Async, Sync) from a single central user interface.

Tags: , , , , , , , , , , , , , , , , , , , , , , , , , , ,

In my previous post, where I discussed the problem of unusable (or slack) disk space on a SAN, I promised a follow-up with techniques on how to increase storage utilization.  I realized that I should discuss some related technologies first and then follow that up with how to put it all together.  So today I start by talking about Thin Provisioning.  I will then follow up with an explanation of De-Duplication and finally talk about how to use multiple technologies together to get the most use out of your storage.

So what is Thin Provisioning?  It is a technology that allows you to create LUNs or Volumes on a storage device such that the LUN/Volume(s) appear to the host or client to be larger than they actually are.   In general, NAS clients and SAN attached hosts see “Thin Provisioned” LUNs just as they see any other LUN but the actual amount of disk space used on the storage device can be significantly smaller than the provisioned size.  How does this help increase storage utilization?  Well, with thin provisioning you provide applications with exactly the storage they want and/or need but you don’t have to purchase all of the disk capacity up front.

Let’s start with a comparison of using standard LUNs vs thin LUNs with a theoretical application set:

Say we have 3 servers, each running Windows Server.  The operating system partition is on local disk and application data drives are on SAN.  Each server runs an application that collects and stores data over time and the application owner expects that over the next year or so the data will grow to 1TB on each server.  In this particular case we also know that the application’s performance requirements are relatively low.

With traditional provisioning we might create 3 LUNs that are 1TB each and present them to the servers.  This provides the application with room for the expected growth.  Using 300GB FC disks we can carve out three 4+1 RAID5 sets, create one LUN in each and it would work fine.  Alternatively we could use wide striping (ie: a MetaLUN on EMC Clariion) and put all three LUNs on the same 15 disks.  Either way we’ve just burned 15 disks on the storage array based on uncertain future requirements.  If we were stingier with storage we could create smaller LUNs (500GB for example) and use LUN expansion technology to increase the size when the application data fills the disk to that capacity.

In the Thin Provisioning world we still create three 1TB LUNs but they would start out by taking no space.  The pool of disk that the LUNs get provisioned from doesn’t even need to have 3TB of capacity.  As the application data grows over the next 12 months or longer the pool size only needs to grow to accommodate the actual amount of data stored.  Depending on the storage array, we can add disks to the pool one at a time.  So on day one we start with 3 disks in the pool, and then add additional disks one by one throughout the year.  We can then create additional LUNs for other applications without adding disks.  As we add disks to the pool, we expand the capacity available for all of the LUNs to grow (up to each LUN’s maximum size) and we increase performance for ALL of the LUNs in the pool since we are adding spindles.  The real-world benefits come as we consolidate numerous LUNs into a single disk pool.

The nice thing about this approach is that we stop managing the size of individual LUNs and just manage the underlying disk pool as a whole.   And the cost-per-GB for SAN disk constantly goes down so we can spend only what we have to today, and when we add more later it will likely be a little cheaper.  Disk capacity utilization will be much higher in a thin model compared with the traditional/thick model.

The story gets even better in a virtual server environment such as with MS Hyper-V or VMWare ESX.  First, the virtual server OS drives are on the SAN in addition to the application data, and there can be multiple virtual disks on the same LUN.  Whether physical or virtual, we need to maintain some free space in the disks to keep applications running, plus with virtual systems we need some free space on the LUN for features of the virtualization technology like snapshots.  The net effect is that in a virtualized environment, disk utilization never gets much above 50% when slack space at both the virtual layer and inside the virtual servers is considered.  With thin provisioning we could potentially store twice the number of virtual servers on the same physical disks.

There are caveats of course.  Maintaining performance is the primary concern.  Whether used in a thick LUN or thin LUN, each disk has a specific amount of performance.   Thin provisioning has no effect on the amount of IOPS or bandwidth the application requires nor the amount of IOPS the physical disk can handle.  So even if thin provisioning saves 50% disk space in your environment, you may not be able to use all of that reclaimed space before running into performance bottlenecks.  If the storage array has QOS features (ie: EMC Clariion NQM) it is possible to prioritize the more important applications in your disk pool to maintain performance where it matters.

Other problems that you may encounter have to do with interoperability.  For starters, some applications are not “thin-friendly”; ie: they write data in such a way as to negate any benefit that thin provisioning provides.  Also, while many storage arrays support thin provisioning, each has different rules about the use of thin LUNs.  For example, in some scenarios you can’t replicate thin LUNs using native array tools.  It pays to do your homework before choosing a new storage array or implementing thin provisioning.

I didn’t cover thin provisioning in NAS environments directly but the feature works in the same manner.  Thin volumes are provisioned from pools of storage and users/clients see a large amount of available disk space even if the disk pool itself is very small.  Since NAS is traditionally used for user home directories and departmental shares, absolute performance is usually not as much of a concern so thin provisioning is much easier to implement and in many cases is the default behavior or simply a check box on NAS appliances like EMC Celerra or NetApp FAS.

Thin provisioning is a powerful technology when used where it makes sense.  In my next post I’ll explain de-duplication technology and then talk about how these technologies can be used together plus some workarounds for the caveats that I’ve mentioned.

Tags: , , , , , , , , , , , , , ,