Condusiv Technologies Blog

Condusiv Technologies Blog

Blogging @Condusiv

The Condusiv blog shares insight into the issues surrounding system and application performance—and how I/O optimization software is breaking new ground in solving those issues.

Webinar: Physical vs. Virtual Bottlenecks: What You Really Need To Know

by Damian 20. February 2012 07:05

Diskeeper Corporation recently delivered a live webinar hosted by Ziff Davis Enterprise. The principle topics covered were:

  • Measuring performance loss in Windows over SAN
  • Identifying client-side performance bottlenecks in private clouds
  • Expanding performance awareness to the client level
  • The greatest and often-overlooked performance issue in a virtual ecosystem

The webinar was co-hosted by:

  • Stephen Deming, Microsoft Partner Solution Advisor
  • Damian Giannunzio, Diskeeper Corporation Field Sales & Application Engineer

Don't miss out on this critical data! If you missed the webinar, you can view the recorded version online here.

Here are some additional, relevant resources:

White Paper: Diskeeper 2011: Improving the Performance of SAN Storage

White Paper: Increasing Efficiency in the IT Environment

White Paper: Inside Diskeeper 2011 with IntelliWrite

White Paper: Running Diskeeper and V-locity on SAN Devices 

Setting the Record Straight - Windows 7 Fragmentation, SSDs, and You

by Howard Butler 21. January 2012 14:50

In today’s well connected world of electronics and instant communications I received a text from a friend asking if I had seen the recent PC World magazine (February, 2012).  He said it had some tidbit of information concerning one of my favorite subjects; system performance, defragmentation, and SSDs.  I located a copy here at the office and found the article. As I read the first line I realized the debate on the virtues of defragmentation especially on SSDs will be one that goes on indefinitely as no one really talks about the issue with supporting hard facts and numbers.  Most articles are rehashing ideas and opinions long since debunked.  They continue to surface because very few truly understand the intricacies of the Windows NTFS file system and that of the storage media, whether it is rotating magnetic hard disks or electronic solid state disks.

So let’s set the record straight… Fragmentation is exponentially more of a problem with today’s data explosion. Defragmenting once a week will still cause the user to experience slowdowns from the degradation effects and doesn’t address the issue when files are initially being written.  And yes, never do a traditional defrag on SSDs.

NTFS file and free space fragmentation happens far more frequently than you might guess.  It has the potential to happen as soon as you install the operating system.  It can happen when you install applications or system updates, access the internet, download and save photos, create e-mail, office documents, etc…  It is a normal occurrence and behavior of the computer system, but does have a negative effect on over all application and system performance.  As fragmentation happens the computer system and underlying storage is performing more work than necessary.  Each I/O request takes a measurable amount of time.  Even in SSD environments there is no such thing as an “instant” I/O request.  Any time an application requests to read or write data and that request is split into additional I/O requests it causes more work to be done.   This extra work causes a delay right at that very moment in time.  Whoever thought that defragmenting once a month or weekly was good enough, simply didn’t understand fragmentation.

Disk drives have gotten faster over the years, but so have CPUs.  In fact, the gap between the difference in speed between hard disks and CPU has actually widened.  This means that applications can get plenty of CPU cycles, but they are still starving to get the data from the storage.  What’s more, the amount of data that is being stored has increased dramatically.  Just think of all those digital photos taken and shared over the holidays.  Each photo use to be approximately 1MB in size, now they are exceeding 15MB per photo and some go way beyond that.  Video editing and rendering and storage of digital movies have also become quite popular and as a result applications are manipulating hundreds of Gigabytes of data.  With typical disk cluster sizes of 4k, a 15MB size file could potentially be fragmented into nearly 4,000 extents.  This means an extra 4,000 disk I/O requests are required to read or write the file.  No matter what type of storage, it will simply take longer to complete the operation.

Suppose I chose to do some editing of my family videos on Tuesday evening.  Even the built-in defragmentation tool in Windows 7 doesn’t do me much good because it isn’t schedule to run until Wednesday morning at 1:00am.  This also means that quite a bit of fragmentation has built up since the previous week when it last ran.  Maybe I’ll manually run it, but that can take quite a while and I’ve wasted time that I would have rather spent on my project.  Unfortunately, the Windows built-in defragmentation utility doesn’t prevent fragmentation so even after running it manually; I still will wind up with fragmentation and slow access speed of my newly created files. 

I’ve often thought about why Wednesday at 1:00am was chosen as the time to schedule defragmentation.  Why isn’t it scheduled all the time?   It is because there could be system resource conflicts that either interfere with getting the task done or the defragmentation process has difficulty throttling back under a variety of conditions.  Regardless, this wait a week to clean up fragmentation doesn’t really help me when I need it most.

As pointed out in the article, the built-in defragmenter does not have the technology advancement to properly deal with fragmentation and SSDs. The physical placement of data on an SSD doesn’t really matter like it does on regular magnetic HDDs.  With an SSD there is no rotational latency or seek time to contend with.  Many experts assume that fragmentation is no longer a problem, but the application data access speed isn’t just defined in those terms.  Each and every I/O request performed takes a measurable amount of time.  SSD’s are fast, but they are not instantaneous.  Windows NTFS file system does not behave any differently because the underlying storage is an SSD vs. HDD and therefore fragmentation still occurs.  Reducing the unnecessary I/O’s by preventing and eradicating the fragmentation reduces the number of I/O requests and as a result speeds up application data response time and improve the overall lifespan of the SSD.  In essence, this makes for more sequential I/O operations which is generally faster and outperforms random writes.

In addition, SSD’s require that old data be erased before new data is written over it, rather than just writing over the old information as with HDDs.  This doubles the wear and tear and can cause major issues with the speed performance and lifespan of the SSD.  Most SSD manufactures have very sophisticated wear-leveling technologies to help with this. The principle issue is write speed degradation due to free space fragmentation.  Small free spaces scattered across the SSD causes the NTFS file system to write a file in fragmented pieces to those small available free spaces.  This has the effect of causing more random I/O traffic that is slower than sequential operations.

I think I have clearly made my point….  The built-in defragmenter in Windows 7 is not a solution for neither the consumer/home user, nor the enterprise business user.  Data access speeds are far more critical in the business world where time is money.  In the enterprise environment there are generally many more files that are used by higher number of users that are accessing data across shared type of storage such as SAN.  Even virtual platforms benefit from the same points covered.  This opens the door and is the reason why robust solutions such as Diskeeper exist.  More data about Diskeeper and the superior technology it offers can be found at http://www.diskeeper.com.

Optimizing Virtual Platform Disk Performance (ESX)

by Michael 28. June 2011 07:38

Overview 

The intensified demand for IT network efficiency and lower operating costs has been driving the phenomenal growth of virtualization in the past decade, with no signs of slowing. At present, many corporations run more virtualized servers than physical servers.

 

While virtualization provides opportunity for consolidation and better hardware utilization, it’s critically important to recognize and never exceed hardware capacities.  

The importance of ensuring sufficient CPU and memory are well understood, with many processes and management tools available to help plan and properly provision VMs for these critical resources. I/O traffic, network and disk, are more complicated to account for in virtual environments as they tend to be more unpredictable.

In order to better accommodate disk I/O, most virtualization platforms will implement a Storage Area Network (SAN) which can offer greater data throughput, and a dynamic environment to address fluctuations in I/O demands.

While a storage infrastructure can be built out to meet expected demands, there are uncontrollable behaviors that will still impede performance. 

File Fragmentation

As files are written to a general purpose local disk file systems, such as Windows NTFS, a natural byproduct is file fragmentation. File fragmentation is a state in which the data stream of a file is stored in non-contiguous clusters in the file system. Fragmentation occurs on logical volume, and by device drivers is translated to logical blocks, and eventually to physical sectors residing on a storage device. It can be demonstrated as pieces of a file located in a non-contiguous manner. The effect of this file fragmentation is increased I/O overhead, leading to slower system performance for the operating system.

In the case of virtual platforms, a guest operating systems is stored as a file (i.e. set of files) on the virtual platforms file system as a “virtual disk”. A virtual disk is essentially a container file, housing all the files that constitute the OS and user data of a VM.  A virtual disk files can fragment just as any other file can resulting in what amounts to a “logically” fragmented virtual hard disk, which still has typical file fragmentation contained within it. The picture represented to the right would appear as “VirtualServer1.vmdk, 30GB in size, in 4 pieces”.  

 

This situation equates to hierarchical fragmentation or more simply fragmentation-within-fragmentation. Given the relatively static nature and large size of virtual disks, and large allocation unit size of VMFS (typically 1MB), fragmentation of these files is unlikely to cause performance issues in most cases. The focus and solution to fragmentation should be directed at the guest operating system.

Fragmentation within a Windows VM will cause Windows to generate additional unnecessary I/O. This added I/O traffic can be discovered using Windows Performance Monitor, where it is one of the principal causes for Split I/O.  

 

Fragmentation prevention and defragmentation technologies exist to eliminate unnecessary I/O overhead, and improve system performance. Fragmentation prevention solves fragmentation at the source, by actively causing files to be written contiguously via advanced files system drivers. Defragmentation is the action in which file fragments are re-aligned within the file system, into a single extent, so that only the minimal amount of disk I/Os are required to access the file, thereby increasing access speed.  

Partition Alignment 

Depending on your storage protocol and virtual disk type, misaligned partitions can cause additional unnecessary I/O[1]. In the example below in which the ESX and SAN volumes are not properly aligned, a Word file spanning four NTFS clusters causes additional unnecessary I/O in both VMFS and the SAN LUN.  

 

Similarities between Partition Alignment and Fragmentation 

Much like misaligned partitions can cause additional I/O at multiple layers, so does fragmentation. While partitions can be properly aligned once and never require further corrective action, fragmentation will continue to occur, and needs to be regularly addressed.

In the example below, which assume proper partition alignment, a file in eight fragments in the guest OS, causes additional I/Os to be generated at the virtualization platform layer[2] and at the LUN.   

 

Defragmentation in the guest operating system (of this file), eliminates excess I/O when accessing the file as Windows only generates one I/O. This reduction in I/O traffic translates to the host file system and SAN LUN, ensuring efficiencies at each layer.   

 

Best Practices 

Defragmentation of Windows file systems is a VMware recommended performance solution. The VMware Knowledge Base article 1004004[3] states “Defragmenting a disk is required to address problems encountered with an operating system as a result of file system fragmentation. Fragmentation problems result in slow operating system performance.” In order to validate the Vmware statement, tests were performed.

 

Test Environment

  
Configuration

Test Environment Configuration Host OS: ESX Server 4.1 with VMFS (1MB blocks)

Guest OS: Windows Server 2008r2 x64 (3GB RAM, 1 vCPU)

Benchmarking Software: Iometer (http://www.iometer.org/)

Fragmentation Program: FragmentFile.exe (used to fragment a specified file)

Defragmentation Software: V-locity® 3.0 (http://www.diskeeper.com/business/v-locity/)

 

Storage: 10GB test volume in a 40GB virtual disk. VMFS Datastore of 410GB. HP Smart Array P400 controller. RAID 5 (4x 136GB SCSI at 10K RPM) Stripe size of 64KB with a 64KB offset (properly aligned).

Load Generation 

The industry standard benchmarking tool Iometer was used to generate I/O load for these experiments.  

Iometer configuration options used as variables in these experiments:

• Transfer request sizes: 1KB, 4KB, 8KB, 16KB, 32KB, 64KB, 72KB, and 128KB

• Percent random or sequential distribution: for each transfer request size, 0 percent and 100 percent random accesses were selected

• Percent read or write distribution: for each transfer request size, 0 percent and 100 percent read accesses were selected 

Iometer parameters that were held constant for all tests:

• Size of volume: 10GB

• Size of Iometer test file (iobw.tst): 8,131,204 KB (~7.75GB)

• Number of outstanding I/O operations: 16

• Runtime: 4 minutes

• Ramp-up time: 60 seconds

• Number of workers to spawn automatically: 1 

The following is excerpted from a VMware white paper[4], and helps to explain why the Iometer parameters were used. 

Servers typically run a mix of workloads consisting of different access patterns and I/O data sizes.

Within a workload there may be several data transfer sizes and more than one access pattern.There are a few applications in which access is either purely sequential or purely random. For example, database logs are written sequentially. Reading this data back during database recovery is done by means of a sequential read operation. Typically, online transaction processing (OLTP) database access is predominantly random in nature. 

The size of the data transfer depends on the application and is often a range rather than a single value. For Microsoft Exchange, the I/O size is generally small (from 4KB to 16KB), Microsoft SQL Server database random read and write accesses are 8KB, Oracle accesses are typically 8KB, and Lotus Domino uses 4KB. On the Windows platform, the I/O transfer size of an application can be determined using Perfmon.

In summary, I/O characteristics of a workload are defined in terms of the ratio of read operations to write operations, the ratio of sequential accesses to random accesses, and the data transfer size. Often, a range of data transfer sizes may be specified instead of a single value.  

Create Fragmentation 

The FragmentFile.exe tool was used to fragment the Iometer test file (iobw.tst) into 568,572 fragments, a mid-range amount of fragmentation for a production server. The statistics collected from an analysis of the volume (shown below) were performed with V-locity.

Test Procedure 

The primary objective was to characterize the performance of fragmented versus defragmented virtual machines for a range of data sizes across a variety of access patterns. The data sizes selected were 1KB, 4KB, 8KB, 16KB, 32KB, 64KB, 72KB, and 128KB. The access patterns were restricted to a combination of 100 percent read or write and 100 percent random or sequential. Each of these four workloads was tested for eight data sizes, for a total of 32 data points per workload.

In order to isolate the impact of fragmentation only the test VM was powered on and active for the duration of the tests.

For the initial run, Iometer created a non-fragmented file, and performance data was collected. Then FragmentFile.exe tool was used to fragment the Iometer test file, the VM rebooted, and the test procedure re-run. This resulted in data sets for both non-fragmented and fragmented scenarios. The results are graphed below.  

Performance Results  

As the graphs show, all workloads show an increase in throughput when the volume [file] is defragmented (i.e. not fragmented).  It also becomes clear that as the I/O read/write size increases, the fragmentation-induced I/O latency increases dramatically.  The greatest improvements of a contiguous file are found with file reads; both random and sequential. 

 

Random Reads  
 
Random Writes 

Sequential Reads

Sequential Writes

Conclusion

 

Fragmentation demonstratively impedes performance of Windows guest operating systems.  While the tests depicted were executed on a singular VM, the issue becomes exponentially worse in a multi-VM environment wherein each VM suffers from file fragmentation.  As server virtualization establishes a symbiotic relationship, it is important to remember that generating disk I/O in one virtual machine affects I/O requests from other virtual systems.  Therefore latencies in one VM will artificially inflate latency in co-located virtual machines (VMs that share a common platform).  

Fragmentation artificially inflates the amount of disk I/O requests which, on a virtual machine platform, compounds the disk bottleneck even more so than on conventional systems.

Eliminating fragmentation in VMs, and the corresponding unnecessary disk I/O traffic, is vital to platform-wide performance and enhances the ability to host more VMs on a shared infrastructure.

You can download the PDF white paper here: Optimizing Virtual Platform Disk Performance.pdf (1.04 mb)

[1] VMware guide to proper partition alignment: http://www.vmware.com/pdf/esx3_partition_align.pdf
[2] It should be noted that VMFS, in the example above need only read the actual amount of data requested in multiples of 512 byte sectors, and does not need to read an entire 1MB block.  
              

Tags:

SAN | Defrag | V-Locity | SAN | VMware | V-Locity | white paper | VMware | white paper

The Summer Blockbuster Sequel: V-locity 3.0

by Michael 24. June 2011 07:00

Coming Soon: V-locity 3.0 (virtual platform optimizer)  has some fantastic new features in it we're sure you’ll like, including:

+Full Support for ESXi Server (in addition to existing support for ESX and Hyper-V)

+Reduced installation effort for ESX Servers (no installation on Host)

+New CogniSAN technology (for storage area networks)

+New V-Aware technology (for any virtualization platform)

+Automatic zeroing of free space (for thin/dynamic virtual disks)

+Added support for virtualization platforms such as XenServer, RHEV, Oracle VM and more

We are just a few short weeks from releasing it, and could use your help. If your interested in catching a “sneak peak” (our final release candidate build), and are interested and able to install, evaluate and then comment (fill out a 10 minute online survey) on this software, simply fill-out a Non-Disclosure Agreement (NDA) located here.

Fax the signed NDA to:
Fax: 818-252-5514

Please add the following to the Fax cover page:
Attn: Field Test Administrator/V-locity Field Test

Alternatively you can email the signed NDA (scan in the pages with your signature) to our Field Test administrator. Please add "V-locity Field Test" in the subject line.

UPDATE July 28, 2011:

Congrats to Benjie Henderson, Virtualization Architect at SS&C, winner of the iPad2 raffle held for release candidate testers! 

Tags: , , , , ,

Hyper-V | SAN | virtualization | V-Locity | VMware

Finding Latencies in your VM/SAN Infrastructure

by Michael 30. March 2011 11:10

Okay, so you've bought, installed, connected, configured, and then tuned/optimized your new storage virtualization solution, but somehow there are still latencies with apps (e.g. SQL).

You've run the Storage Area Network (SAN) vendor utilities that:

  • did not see any contention on the disks in the RAID group(s). 
  • noted that the average I/O to physical disks did not exceed a reasonable number of I/O's per second on each volume in the meta device.
  • checked the utilization of the port that the Host Bus Adaptor (HBA) is zoned to and did not see any performance issues.
  • noted the switch port that the HBA is connected to is not saturated or reporting any errors.

And basically surmised "at this time we do not see any issue on the array or with the SAN in reference to this server."

However....

When running PerfMon within Windows, it continues to uncover latencies in the 100ms+ range. What the hayel!

This is when it's important to consider what those SAN optimization and reporting tools are providing. SANs can optimize storage from HBA-to-spindle. Above the HBA other factors cause latencies outside the scope or control of the SAN, and ultimately it is the App/User Experience that needs to be addressed.

So, it's time to look further up the storage stack.

Here is a great chart (borrowed from VMware here):

The chart helps simplify that SAN and even VM based latency monitoring and storage optimization do not account for latencies that may exist in the Guest Operating System (GOS). They are only aware of, and able to optimize I/O from the point they receive the traffic to the physical storage.

Monitoring performance in Windows does not go away simply because you've left direct attached storage (DAS) and physical servers to go virtual. There are numerous causes for poor performance on the GOS side, from poorly written apps, to incorrect configurations, to bad partitioning strategies, file system fragmentation and more. Pretty much all the issues that could cause poor Windows I/O performance on physical servers with DAS, still exist.

It's important to continue to use GOS based solutions to determine application latency such as PerfMon, which can support counters for popular apps (like SQL).

To evaluate if file fragmentation is a potential cause, track these metrics with Perfmon. Fragmentation will show up in the logical disk statistics referred to in the document. You can also use a freeware solution from Diskeeper Corporation; called Disk Performance Analyzer for Networks (DPAN) to collect file fragmentation statistics from any Windows system (physical or virtual) on your LAN/WAN.  You can download DPAN here.

Sample DPAN Report:

Tags:

Defrag | SAN

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