Category Archives: Fundamentals

The Fundamentals of Storage Systems – Shared Consolidated Storage Systems

Shared Consolidated Storage Systems – A Brief History

Hey, “Shared Consolidated Storage Systems” did you just make that up? Why yes, yes I did.

For as long as we have had computers there has been a need to store and retrieve data. We have covered the basics of hard disks, RAID and solid state storage. We have looked at all of this through the aspect of being directly attached to a single server. It’s time we expand to attaching storage pools to servers via some kind of network. The reason I chose to say shared and consolidated storage instead of just SAN or Storage Area Network was to help define, broaden and give focus to what we really mean when we say SAN, NAS, Fibre Channel or even iSCSI. To understand where we are today we need to take a look back at how we got here.

Once, There Were Mainframes…

Yep, I know you have heard of these behemoths. They still roam the IT Earth today. Most of us live in an x86 world though. We owe much to Mainframes. One of these debts is networked storage. Way back when, I’m talking like the 1980’s now, Mainframes would attach to their storage via a system bus. This storage wasn’t internal the way we think of direct attached storage though. They had massive cables running from the Mainframe to the storage pods. The good folks at IBM and other big iron builders wanted to simplify the standard for connecting storage and other peripherals.


Who doesn’t love working with these cables?

You could never lose this terminator!

Out With The 1960’s And In with the 1990’s!

Initially IBM introduced it’s own standard in the late 80’s to replace the well aged bus & tag and other similar topologies with something that was more robust and could communicate over optical fiber. ESCON was born. The the rest of the industry backed Fibre Channel which is a protocol that works over optical fiber or copper based networks, more importantly it would be driven by a standards body and not a single vendor. Eventually, Fibre Channel won out. In 1994 Fibre Channel was ratified and became the defacto standard even IBM got on board. Again, we are still talking about connecting storage to a single Mainframe, longer connections were possible and the cabling got a lot cleaner though. To put this in perspective, SQL Server 4.2 was shipping at that point with 6.0 right around the corner.

High Performance Computing  and Editing Video.

One of the other drivers for Fibre Channel was the emerging field of High Performance Computing (HPC) and the need to connect multiple mainframes or other compute nodes to backend storage. Now we are really starting to see storage attached via a dedicated network that is shared among many computers. High end video editing and rendering farms also drove Fibre Channel adoption. Suddenly, those low end pc-based servers had the ability to connect to large amounts of storage just like the mainframers’.

Commodity Servers, Enterprise Storage.

Things got interesting when Moore’s Law kicked into high gear. Suddenly you could buy a server from HP, Dell or even Gateway. With the flood of cheaper yet powerful servers containing either an Intel, MIPS, PPC or Alpha chip you didn’t need to rely on the mainframe so heavily. Coupled with Fibre Channel and suddenly you had the makings for a modern system. One of the biggest challenges in this emerging commodity server space was storage management. Can you deal with having hundreds of servers and thousands of disks without any real management tools? What if you needed to move some unused storage from server A to Server B? People realized quickly that maintaining all these islands of storage was costly and also dangerous. Even if they had RAID systems if someone didn’t notice the warnings you could lose whole systems and the only people who knew something was up was the end user.

Simplify, Consolidate, Virtualize and Highly Available

Sound familiar? With the new age of networked storage we needed new tools and methodologies. We also gained some nifty new features. Network attached storage became much more than a huge hard drive. To me, if you are calling your storage solution a SAN it must have a few specific features.


Your SAN solution must use standard interconnects. That means if it takes a special cable that only your vendor sells it doesn’t qualify. In this day and age, if a vendor is trying to lock you into specific interface cards and cables they are going to go the way of the dodo very quickly. Right now the two main flavors are Fiber Optics and copper twisted pair a.k.a Ethernet. It must also reduce your management overhead this usually means a robust software suite above and beyond your normal RAID card interface.


It must be able to bring all your storage needs together under one management system. I’m not just talking disks. Tape drives and other storage technologies like deduplication appliances are in that category. The other benefit to consolidation is generally much better utilization of these resources. Again, this falls back to how robust the software stack that your SAN or NAS comes with.


It must be able to abstract low level storage objects away from the attached servers allowing things like storage pools. This plays heavily into the ability to manage the storage that is available to a server and maintain consistency and up time. How easily can I add a new volume? Is it possible to expand a volume at the SAN level without having to take the volume off-line? Can other resources share the same volumes enabling fun things like clustering?

Highly Available

If you are moving all your eggs into one HUGE basket it better be one heck of a basket. Things like redundant controllers where one controller head can fail but the SAN stays on line without any interruption to the attached servers. Multiple paths into and out of the SAN so you can build out redundant network paths to the storage. Other aspects like SAN to SAN replication to move your data to a completely different storage network in the same room or across the country may be available for a small phenomenal add on fee.

If your SAN or NAS hardware doesn’t support these pillars then you may be dealing with something as simple as a box of disks in a server with a network card. Realize that most SANs and NAS’es are just that. Specialized computers with lots of ways to connect with them and some really kick-ass software to manage it all.

Until Next Time…

Now that we have a bit of history and a framework we will start digging deep into specific SAN and NAS implementations. Where they are strong and where they fall flat.

Fundamentals of Storage Systems, IO Latency and SQL Server

A Thousand Men Marching Still Only March As Fast As One Man.

la·ten·cy – Computers . the time required to locate the first bit or character in a storage location, expressed as access timeminus word time.

Often when talking to people about performance they get rapped around the MB/Sec number and ignore a critical factor, latency. SQL Server is one of those few applications that is very sensitive to disk and network latency. Latency is what the end user sees. If your SQL Server is waiting around for disk or network they will start to complain. In an OLTP environment SQL Server accesses data on disk in a nonlinear fashion, aka random IO’s. The size of these IO request can be pretty small. In a good application you really try and limit the amount of data returned to keep things speedy. The down side of small Random IO’s is the system will never be faster than a single seek operation on your disk. So, if you have a 15k SAS drive that is around 2.5ms. Caching and buffering schemes aside for now, 2.5ms is your floor. You will never be faster than that. Depending on the size of the IO request you spend more time waiting for the seek operation than you do actually transferring the data from the disk. We group disks together in larger arrays to give us more aggregate throughout and higher operations per second, but you are ever only as fast as your slowest disk. You can always get more aggregate throughput up to several gigabytes a second but you still have to wait on that first bit to travel to you.

To get around these short comings, SQL Server buffers as much data as it can in memory. We also add large amounts of cache to our SAN’s and disk controllers. This can mask some of the problem, but at some point it still needs to come from your disk drives.

On the network side things are actually better. With latency under a millisecond on a LAN you usually waiting on disk to deliver the data. There are other factors like the speed of the network equipment and number of hops across interfaces you have to make can be more significant than the actual transmittion rate. TCP/IP can be a factor as well. Out of the box SQL Server is configured at 4KB(4096 byte) packet. This is a good general setting for most workloads. If you are working on a highly tuned OLTP system you may want to set that to something smaller or align it with the TCP packet size for your network, usually 1500 bytes. If it is a OLAP system with lots of streaming throughput latency will make up a very small part of the overall transmission time and going with a larger packet size possibly aligned to the 8KB page size with increase throughput and decrease the time to transmit overall. If you do set a large packet size you should consider enabling jumbo frames on your network card. Make sure that your network equipment can support the jumbo frame from end to end.

Another place where we are starting to see more latency issues is with database mirroring. In synchronous mode, the default setting, you are now adding network latency plus the disk latency of the other server to the overall transaction time.

Mirroring isn’t the only game in town. We have had SAN level replication for quite a while as well. In most of the scenarios where we were using SAN level replication it was site to site across several miles. To give you an idea of how much latency can be added in this situation go ping or, I’ll wait….. Ok, from my location ether of them is 45ms~75ms, or 18 times slower than your spinning disks. All the sudden, your network is the major player in delaying transactions. I’ve used fibre optics to connect to sites and the latency can still be a killer for OLTP systems. The general rule of thumb is 7.5 microseconds for every  1 1/2 miles. If our target SAN is 125 miles away we just added 2ms of latency to the 4ms of latency the two sets of disks are providing. In reality, it is worse than that when you again figure in network equipment. I personally haven’t seen synchronous setups more than 50 miles apart.

Just something to keep in mind as you plan your SQL Server infrastructure. Latency in its myriad forms is king.

Series To Date:
  1. Introduction
  2. The Basics of Spinning Disks
  3. The System Bus
  4. Disk Controllers, Host Bus Adapters and Interfaces
  5. RAID, An Introduction
  6. RAID and Hard Disk Reliability, Under The Covers
  7. Stripe Size, Block Size, and IO Patterns
  8. Capturing IO Patterns
  9. Testing IO Systems
  10. Latency – You are here!

SQLDIY: Gather Virtual File Statistics Using T-SQL #TSQL2sDay 15

It’s that time again, T-SQL Tuesday is here! This time Pat Wright (blog|twitter) is hosting and has put forth automating tasks using ether T-SQL or Powershell. I LOVE automating stuff. As a production DBA in some very large shops you can’t do your job unless you make your servers work for you. I’ve been using T-SQL and *GASP* xp_cmdshell, OSQL and file shares to gather stats and push configurations to servers for decades. Log before fancy things like C# and Powershell existed. These days I use a variety of home grown tools but doing things with just T-SQL can be just as powerful. I’m going to leverage this post to start a series on a pure T-SQL implementation of configuration management, data gathering and utility procedure deployment.

Where Is Your Management Database?

Every DBA should have two things, a utility, or management database on every server and a central repository where all the locally collected data in the management database is pulled back to. What surprises people when I talk about this methodology is I don’t always advocate using a licensed copy of SQL Server. By that I mean that SQL Express works just great as a central repository server. I usually put this on a virtual machine, Hyper-V or what ever flavor of virtual environment your company supports. This allows you to do things like enable CLR and xp_cmdshell on a server that technically is non-production and keep your security risk much lower. Every server that is deployed in my shop gets a local management database. From the central repository I can push out everything I need to manage a server and keep all my servers up to date as I make improvements or bug fixes to the management code. That’s all I’m really going to say about that in this post though I just wanted to give you an idea of just how deep the rabbit hole can go.

DMV’s give you the information, you have to use it.

Since SQL Sever 2005 Microsoft let of of the black box mentality and started providing crazy useful information via Dynamic Management Views. Virtual file statistics though have been around for quite a while. They got a touch up in the DMV but the basic information was available in SQL Server 2000 via function call.  The DMV I’m after is sys.dm_io_virtual_file_stats. It has a ton of information in it. It’s main problem though is it is an aggregation over time and doesn’t really tell you what is different from yesterday to today. To get around that we have to build our own sampling routine.

The VirtualFileStats Table

We create a table in our local management database to collect the daily numbers. I try to keep things simple.

CREATE TABLE dbo.VirtualFileStats
     RecordID                             INT IDENTITY(1,1) NOT NULL,
     ServerName                           VARCHAR(255) NOT NULL,
     DBID                                 INT NOT NULL,
     FileID                               INT NOT NULL,
     Reads                                BIGINT NULL,
     ReadsFromStart                       BIGINT NULL,
     Writes                               BIGINT NULL,
     WritesFromStart                      BIGINT NULL,
     BytesRead                            BIGINT NULL,
     BytesReadFromStart                   BIGINT NULL,
     BytesWritten                         BIGINT NULL,
     BytesWrittenFromStart                BIGINT NULL,
     IostallInMilliseconds                BIGINT NULL,
     IostallInMillisecondsFromStart       BIGINT NULL,
     IostallReadsInMilliseconds           BIGINT NULL,
     IostallReadsInMillisecondsFromStart  BIGINT NULL,
     IostallWritesInMilliseconds          BIGINT NULL,
     IostallWritesInMillisecondsFromStart BIGINT NULL,
     RecordedDateTime                     DATETIME NULL,
     IntervalInMilliseconds               BIGINT NULL,
     FirstMeasureFromStart                BIT NULL
CREATE TABLE dbo.VirtualFileStatsHistory
     RecordID                             INT NOT NULL,
     ServerName                           VARCHAR(255) NOT NULL,
     DBID                                 INT NOT NULL,
     FileID                               INT NOT NULL,
     Reads                                BIGINT NULL,
     ReadsFromStart                       BIGINT NULL,
     Writes                               BIGINT NULL,
     WritesFromStart                      BIGINT NULL,
     BytesRead                            BIGINT NULL,
     BytesReadFromStart                   BIGINT NULL,
     BytesWritten                         BIGINT NULL,
     BytesWrittenFromStart                BIGINT NULL,
     IostallInMilliseconds                BIGINT NULL,
     IostallInMillisecondsFromStart       BIGINT NULL,
     IostallReadsInMilliseconds           BIGINT NULL,
     IostallReadsInMillisecondsFromStart  BIGINT NULL,
     IostallWritesInMilliseconds          BIGINT NULL,
     IostallWritesInMillisecondsFromStart BIGINT NULL,
     RecordedDateTime                     DATETIME NULL,
     IntervalInMilliseconds               BIGINT NULL,
     FirstMeasureFromStart                BIT NULL

This is what we need to gather, and later analyze the data. Since we are managing our samples we have to know when the sampling started and what the first sample is. FirstMeasureFromStart lets us know that it is the first base measurements the rest of the samples will delta off of.

GatherVirtualFileStats Stored Procedure

Next we need a stored procedure to do the sampling. One thing you will notice is the procedure executes continuously with a WAIT FOR DELAY built into it so you can get finer grained than the 1 minute limitation of the SQL Agent. Sometimes, I will do one off sampling for a short period, say 30 minutes at a 30 second interval but most often I just let it run and set the sample rate at 1 minute or larger depending on how busy the system is.

            id = Object_id(N'[dbo].[GatherVirtualFileStats]')
            AND Objectproperty(id, N'IsProcedure') = 1)
  DROP PROCEDURE [dbo].[GatherVirtualFileStats]


--  GatherVirtualFileStats
--  by: Wesley D. Brown
--  date: 02/08/2011
--  mod:  04/14/2011
--  mod:  04/17/2013

--  description:
--	This stored procedure is used to sample sys.dm_io_virtual_file_stats to track
--	performance at a database file level. This is useful for finding
--	hotspots on SAN's or under performing IO systems.

--  parameters:
--    @Duration	 = '01:00:00' How long to run before exiting
--   @IntervalInSeconds = 120 Number of seconds between samples
--@DB			 = -1 DB_ID to monitor, -1 for all
--@DBFile		 = -1 File_ID of file to monitor, -1 for all
--  usage:
--  	DECLARE @RC         INT,
--			@StartTime  DATETIME,
--			@databaseID INT

--	SELECT @StartTime = Getdate(),
--		   @databaseID = Db_id()

--	EXEC @RC = Gathervirtualfilestats
--	  '00:45:30',
--	  30,
--	  10,
--	  -1

--	FROM   dbo.VirtualFileStats
--	WHERE  DBID = 10
--	ORDER  BY RecordID

--  platforms:
--  SQL Server 2005
--  SQL Server 2008
--  SQL Server 2008 R2
--  SQL Server 2012
--  tested:
--  SQL Server 2005 SP2
--  SQL Server 2012
--  *** change log		***
--	Added history table and perge on start up if there is data in the main table
--  *** end change log	***
CREATE PROC dbo.Gathervirtualfilestats
  @Duration          DATETIME = '01:00:00',
  @IntervalInSeconds INT = 120,
  @DB                INT = -1,
  @DBFile            INT = -1
  SET nocount ON

    @StopTime                 DATETIME,
    @LastRecordedDateTime     DATETIME,
    @CurrentDateTime          DATETIME,
    @ErrorNumber              INT,
    @NumberOfRows             INT,
    @ErrorMessageText         NVARCHAR(4000),
    @CurrentServerName        VARCHAR(255),
    @DifferenceInMilliSeconds BIGINT,
	@SQLVersion				  VARCHAR(50)

	select @SQLVersion =
		substring(version_number,1,charindex(' ',version_number))
			substring(version,charindex('-',version)+2, charindex('(',version)-patindex('%.[0-9]',version)) as version_number from
				select @@version as version
			) as t
	) as t

	if (charindex('11.',@SQLVersion,0) > 0)
		IF (@DB = -1)
			set @DB = NULL
		IF (@DBFile = -1)
			set @DBFile = NULL

                    id = Object_id(N'[dbo].[VirtualFileStats]')
                    AND Objectproperty(id, N'IsTable') = 1)
              INSERT INTO dbo.VirtualFileStatsHistory

              TRUNCATE TABLE dbo.VirtualFileStats;

    @CurrentServerName = Cast(Serverproperty('servername') AS VARCHAR(255))

  SET @DifferenceInMilliSeconds = Datediff(ms, CONVERT(DATETIME, '00:00:00', 8), @Duration)

    @StopTime = Dateadd(ms, @DifferenceInMilliSeconds, Getdate())

  WHILE Getdate() <= @StopTime
          @LastRecordedDateTime = @CurrentDateTime

          @CurrentDateTime = Getdate()

        INSERT INTO dbo.VirtualFileStats
          vfs.num_of_reads - dbaf.ReadsFromStart                            AS Reads,
          vfs.num_of_reads                                                  AS ReadsFromStart,
          vfs.num_of_writes - dbaf.WritesFromStart                          AS Writes,
          vfs.num_of_writes                                                 AS WritesFromStart,
          vfs.num_of_bytes_read - dbaf.BytesReadFromStart                   AS BytesRead,
          vfs.num_of_bytes_read                                             AS BytesReadFromStart,
          vfs.num_of_bytes_written - dbaf.BytesWrittenFromStart             AS BytesWritten,
          vfs.num_of_bytes_written                                          AS BytesWrittenFromStart,
          vfs.io_stall - dbaf.IostallInMillisecondsFromStart                AS IostallInMilliseconds,
          vfs.io_stall                                                      AS IostallInMillisecondsFromStart,
          vfs.io_stall_read_ms - dbaf.IostallReadsInMillisecondsFromStart   AS IostallReadsInMilliseconds,
          vfs.io_stall_read_ms                                              AS IostallReadsInMillisecondsFromStart,
          vfs.io_stall_write_ms - dbaf.IostallWritesInMillisecondsFromStart AS IostallWritesInMilliseconds,
          vfs.io_stall_write_ms                                             AS IostallWritesInMillisecondsFromStart,
            WHEN @LastRecordedDateTime IS NULL THEN NULL
            ELSE Datediff(ms, dbaf.RecordedDateTime, @CurrentDateTime)
          END                                                               AS IntervalInMilliseconds,
            WHEN @LastRecordedDateTime IS NULL THEN 1
            ELSE 0
          END                                                               AS FirstMeasureFromStart
          sys.Dm_io_virtual_file_stats(@DB, @DBFile) vfs
        LEFT OUTER JOIN VirtualFileStats dbaf
          ON vfs.database_id = dbaf.dbid
             AND vfs.[file_id] = dbaf.fileid
          ( @LastRecordedDateTime IS NULL
             OR dbaf.RecordedDateTime = @LastRecordedDateTime )

          @ErrorNumber = @@ERROR,
          @NumberOfRows = @@ROWCOUNT

        IF @ErrorNumber != 0
              SET @ErrorMessageText = 'Error ' + CONVERT(VARCHAR(10), @ErrorNumber) + ' failed to insert file stats data!'

              RAISERROR (@ErrorMessageText,
                         1) WITH LOG

              RETURN @ErrorNumber

        WAITFOR DELAY @IntervalInSeconds

I Have Data, Now What?

This is where the fun begins! If you just query the table the data doesn’t make much sense.


We need to do some simple math and get the data into a metric that is meaningful.

SELECT TOP 10 Db_name(dbid)                                          AS 'databasename',
              File_name(fileid)                                      AS 'filename',
              Reads / ( IntervalInMilliSeconds / 1000 )              AS 'readspersecond',
              Writes / ( IntervalInMilliSeconds / 1000 )             AS 'writespersecond',
              ( Reads + Writes ) / ( IntervalInMilliSeconds / 1000 ) AS 'iopersecond',
                WHEN ( Reads / ( IntervalInMilliSeconds / 1000 ) ) > 0
                     AND IostallReadsInMilliseconds > 0 THEN IostallReadsInMilliseconds / Reads
                ELSE 0
              END                                                    AS 'iolatencyreads',
                WHEN ( Reads / ( IntervalInMilliSeconds / 1000 ) ) > 0
                     AND IostallWritesInMilliseconds > 0 THEN IostallWritesInMilliseconds / Writes
                ELSE 0
              END                                                    AS 'iolatencywrites',
                WHEN ( ( Reads + Writes ) / ( IntervalInMilliSeconds / 1000 ) > 0
                       AND IostallInMilliseconds &gt; 0 ) THEN IostallInMilliseconds / ( Reads + Writes )
                ELSE 0
              END                                                    AS 'iolatency',
FROM   management.dbo.VirtualFileStats
       AND FirstMeasureFromStart = 0

This gives us reads, writes and io latency per second results.


Now we are cooking! We can now see that on this database we are seeing some spikes in latency, the number of milliseconds it takes to complete a single IO request, and may warrant investigation. As a general rule of thumb if I see IO latency above 20 milliseconds consistently I start looking deeper into the IO system to see what is wrong. A single modern hard disk is capable of 130 random IO’s a second. Another thing to consider is how many databases are on the same disk. I will pull the database files together with the volume they are on to get a true aggregate number of IO’s and latencies. You may find that a single database is dominating the disks and causing other databases to slow down even when the number of IO’s for those databases is small. On a SAN being able to get to the file level can help you locate the physical disks for that LUN and help your SAN administrators look at a very specific spot instead of the overall health of the SAN and actually fix your performance issues.

Lastly, I run a nightly job that performs these aggregations for me and moves them into a table that I keep long term so I can see performance over time. This is a great way to see if you are getting near your IO capacity and if the steps you have done correct the issues.

So, That’s it?

Not by a long shot. Measuring IO latencies is just one piece of a much larger puzzle for troubleshooting performance problems. It is a valuable one though, and keeping this information over time is just priceless. Now that you have the tools to gather virtual file statistics on your SQL Server instance I’d love to hear how you are using the data.

Update 4/14/2011

I added a history table an a check at the beginning to move all data to history before starting up. Mike Kaplan reported below that multiple runs caused issues if there was data in the table from a previous run.

Update 4/17/2013

Added a check for the version of SQL Server. In 2012 they changed the syntax so calling the dmv with a -1,-1 simply gives you no data. Previously, it returned all database files.

Fundamentals of Storage Systems, Understanding Reliability and Performance of Solid State Storage

Solid state storage has come on strong in the last year. With that explosion of new products it can be hard to look at all the vendor information and decide which device is best for you. Between the different manufacturers using different methods to benchmark their products showing two different numbers for reads and writes using different methodologies it can be extremely confusing. If you haven’t read Solid State Storage Basics you may not understand all the terms used in this article.

SLC and MLC Characteristics and Differences

Right now there are two main flavors of NAND Flash that are in use. Single Level Cell(SLC) and Multi Level Cell(MLC). SLC stores a single bit cell while MLC can store two bits. There are flavors of MLC that can store three and four bits but are unsuitable at this time for mass storage like hard drives. They have very low endurance and wear out quickly.

SLC has several desirable characteristics that have made it the choice for enterprise applications for quite a while. It is more durable in every way over MLC. Where it loses out is on capacity and price.

Measure SLC MLC
Read Speed 25~ nanoseconds 50~ nanoseconds
Write Speed 220~ nanoseconds 900~ nanoseconds
P/E Cycles 100k to 300k 3k to 30k
Minimum ECC Bits required 1 bit per 512 bytes 12 bits per 512 bytes
Block Size 64KB 128KB


SLC can cost as much as five times as MLC. This alone is enough for many manufacturers to look at MLC over SLC. Couple that with the increased capacity makes MLC a compelling alternative for mass storage. The problem has been how to make MLC reliable in the enterprise.

Enterprise Reliability

As you can see, SLC is more robust requiring less error correcting code to fix data issues. Just a few years ago, MLC wasn’t considered good enough to be in even consumer grade drives. Over the last three years several manufacturers have focused on building NAND Flash controllers that could compensate for this using large amounts of error correction. In some cases several times the 12 bits per 512 bytes. This combined with better garbage collection and wear-leveling algorithms have finally extended MLC into the enterprise. This comes with a price though. ECC has to be stored somewhere, usually sacrificing storage space, and you need a much more powerful controller to handle the calculations without hurting performance. Another one of the techniques to extend the performance and endurance used is to put as many chips in a parallel arrangement with multiple channels. Think of it as RAID on a chip level instead of a hard disk level. This allows them to spread the IO load as wide as possible. The larger the capacity of the storage device the more area it has to use things like TRIM and it’s own internal garbage collection across multiple NAND chips keeping IO from stalling out due to write amplification. It also increases the life of the device as well since you can spread the wear-leveling out. There are standards bodies like JEDEC that help define endurance and longevity but you must still read the fine print. A good example is the Intel product manual for the X-25M SSD. If you look at page 6 you see the minimum useful life rated at 3 years. But, if you look at the write endurance you see that the 80 gigabyte drive is rated at 7.5 terabytes. That is 7.5 terabytes period, for the life of the drive. That means you shouldn’t write more than 21 gigabytes a day in changed data to the drive. For SQL Server that can be quite a low number. I’ve seen data warehousing processes load multiple terabytes over a 8 hour load window. Again, capacity equals endurance the 160 gigabyte drive can sustain 15 terabytes worth of data change. Intel will tell you that the X25-M is meant for enterprise workloads, they are wrong. In contrast, the X-25E SSD has a much longer life due to the SLC it uses instead of MLC. the 32 gigabyte version supports 1 petabyte of random writes and the 64 gigabyte drive supports 2 petabytes of random writes over the life of the drive. This makes the X-25E a better candidate for server work loads. Fusion-io rates their MLC based ioDrive at 5 terabytes a day. They also claim a life expectancy of 16 years. That is 28 petabytes of P/E cycles. This is to just show you that with enough engineering you can have an MLC based device still be very reliable.

SATA, SAS or Neither?

The interface for your solid state disk is also critical to the performance of the drive. We are quickly hitting a wall with SATA II and solid state where a single SSD can saturate a single SATA channel. SAS and SATA both have released the new third generation standard allowing up to 600 megabytes a second of through put but even that doesn’t offer much head room for growth. Several manufacturers are calling their SSD offerings enterprise even though they are on a SATA interface. If you are building a high performance IO subsystem SATA isn’t the best option. With SATA II and the addition of Native Command Queuing  it did get a lot better but still falls short of SAS in several areas.


Feature SAS SATA
Command Queuing TCQ supports queue depths up to 216 usually capped at 64 NCQ supports queue depths up to 32
Error recovery and detection Uses the SCSI command is more robust SMART Proven to be in adequate. see Google  Paper
Duplex Full Duplex dual port per drive Half Duplex single port
Multi-path IO fully supported at drive level supported in SATA II via expanders

Some of these features were nice but if you were choosing between a 7200 RPM SATA drive and a 7200 RPM SAS drive there wasn’t a huge difference. Add in flash though and SATA very quickly shows its short comings. I cannot stress how important command queuing is to flash storage. If the drive you have picked supports NCQ make sure your HBA supports NCQ and ACHI mode to get the most out of it, PC Perspective has a nice write up on this.  Lastly, most SATA drives don’t honor the OS request to disable write caching on the drive. This is a big deal for SQL Server where protecting the data is very important. That alone usually keeps me from putting critical databases on SATA based storage. Most RAID HBA’s may let you toggle the drives write cache on or off on a per drive basis but there is still no guarantee that the drive will honor that request ether.

PCIe add in cards
If you aren’t limited to the standard 3.5” or 2.5” form factor and can choose a PCIe based flash device I would recommend starting with Fusion-io. I haven’t had any experience with the Texas Memory System PCIe card though. OCZ, Super Talent and others like them use a combination of bridge chips, RAID controller chips and flash controller chips to build up their SATA PCIe offerings. The form factor may be more convenient but they are ultimately the same as multiple SATA drives plugged into a RAID HBA.

The last thing to remember is TRIM doesn’t work through RAID HBAs SAS or SATA doesn’t matter.

Performance Characteristics

By the numbers
I see people quote performance numbers from different manufactures about just how fast their particular solid state storage is. The problem is, there is no real standard for measuring performance and it can be almost impossible to do an apples to apples comparison between two different devices. If you start at the product specification for the X25-M you see the what you expect. 4K read IOPS 35,000 at 100 percent span(using the entire drive). Write IOPS however are a little different. Using 100 percent span the IO/Sec drop to 350. If you only use one tenth of the drive it shoots up to 3300. The difference is startling. Using an old technique called short stroking, they are able to show the drive in a better light. Using this technique on hard disks yields higher IO’s per second at the cost of capacity and throughput. Applying this technique to a solid state disk limits the amount of data space used for writes and gives the maximum amount of free space for wear-leveling and garbage collection greatly reducing the write amplification effect. Rarely do you see the lower number quoted. On the X-25E all numbers are quoted at full span, showing again the higher performance of SLC. Also, if you look at the footnotes all write tests were done with drive caches enabled. For SQL Server this is a bad idea, if you have a power outage any data in the drive cache is lost. They perform these tests at the maximum queue depth for Native Command Queuing (NCQ) can handle. Again, this pushes the device to its peak throughput. This isn’t a bad thing for SSD’s, but most SQL Server setups have been engineered to keep queue depths low to decrease latencies from the IO system which is usually made up of spinning disks. If you don’t have latency issues now, you may not see a huge improvement by replacing your spinning disks with solid state ones. Size of the IO request is also very important Usually for number of IO’s they will use a sector sized request. On SSD’s that is normally 4 kilobytes. For throughput megabytes per second they use a 128 kilobyte request to get higher numbers. So, when you read the specifications you get the impression that a drive will do say 260 MB/sec at 35,000 IOs/Sec which just isn’t true. This isn’t a new game, hard drive benchmarks also do something similar.  As you look at the 4k numbers you can effectively cut them in half since SQL Server works on an 8k page request size. SSDs also perform differently on random and sequential IO loads just like hard disks do. When you look at the specification make sure and note the IO mix, if they don’t give those numbers assume that you will have to do your own testing!

Previous Writes Effect Future Writes
Another issue with the performance numbers quoted has to do with the state of the drive. When a solid state disk is new, i.e. never been written to, it is at it’s peak. Performance will be the best it is ever going to be. When you test your solid state devices doing short duration tests can be very misleading. As I have already pointed out, if you only use a small section of the drives for writes you get inflated numbers. If you only do a short test on the entire drive you are effectively doing the same thing. You must test the entire drive. You must also understand your workload. If you don’t know what the workload will be don’t be afraid to test a wide range of IO sizes and types. Sequential writes tend to leave large contiguous blocks of free space making garbage collection faster. In contrast random writes typically leave lots of small blocks of free space forcing garbage collection to work overtime slowing writes down. As you move from one IO type to another you should add in extra time for the drive to settle into a new steady state before resuming valid samples. Your goal is to get the drive to perform in a predictable manor for your IO load. Realize you may need to discard a range of samples that cover the transition from one steady state to the other. It can lower or inflate your averages and cause you to under or over provision your storage to meet your IO requirements.

Performance over Time
Unlike a hard drive, as you use a solid state disks performance degrades over time for several reasons. In the case of the X-25M the first firmware suffered from poor garbage collection and IO pattern recognition on large volumes of small IO’s causing the drive to suffer as much as a five fold decrease in write performance. We aren’t just talking small files but small changes to large files, like SQL Server data files. This particular problem was partially fixed with a firmware update. In general, all solid state devices suffer As you use your drive over a longer period it will lose performance as part of the normal wear on the NAND Flash chips themselves. They develop more errors cause more write retries. These issues are corrected using ECC and bad block management, but it still leads to poorer performance. SLC has an advantage over MLC again due to it’s much higher endurance but isn’t 100 percent immune to this. If you replace your hardware on a three or five year cycle this may not be a huge issue for you, but it still pays to monitor the performance over time.


There is a lot to learn when it comes to solid state storage. Making sure you do your own testing and research can keep you from suffering from premature failure and poor performance down the road. Remember, NAND Flash has been around for a while but this new wave of solid state storage is only a few years old. Not having a large pool of these devices in the field for longer than their rated life span makes it hard to predict if they are truly as reliable as we all hope they are.

Fundamentals of Storage Systems – RAID and Hard Disk Reliability, Under the Covers

In the last RAID article we covered the basics. This is a little deeper dive into the underlying mechanics of RAID. Exactly what it does, how it does it and what it doesn’t do that people assume it does. I sited David Patterson, Garth Gibson, and Randy Kats and their work at UC Berkley on RAID. They show something I’ve talked about before the “Pending I/O Crises”. Of course it isn’t pending anymore, its here. One of the concerns has to do with Amdah’s Law and speeding up execution with parallel operations. As processors and memory speed up hard disks are still an order of magnitude slower. Another aspect is Kryder’s Law, which like Moore’s Law, is a estimation of capacity growth of hard disks over time. Kryder’s Law is starting to slow down just as Moore’s law is. The problem with hard drives has never really been capacity, its speed. As areal density increases you do get an increase in data throughput, there is simply more data per square inch on the disk. You also get an improvement in I/O’s, tracks are closer together.  We haven’t broken past the 15k barrier yet. I’ve still got Seagate Cheetah 15k.3 drive from 2002. It has a max sequential throughput around 80 MB/sec. I doubt we will see spinning disks faster than 15k. This is a real problem for scaling I/O up. Enter RAID. It’s simple get a bunch of disks and then stripe data across them. One little problem creeps up.  Reliability goes down for each drive you add to the array. Using RAID 0 pretty much guarantees you will have an array failure. To overcome this We start adding some way to make the data more redundant.

Hard Disk Reliability

People make a lot of assumptions about hard drives and their reliability. Hard disks break down into two classes consumer grade, the drive you have in your desktop and enterprise, the kind usually in your servers. There are misconceptions around both. Recently, Google and others have written papers based on long term large batch sample failure rates and found the enterprise class drives don’t last any longer than consumer class. This study is perfectly valid from a physical reliability point of view. Most drives are manufactured the same way in the same plants. Not like the poor misunderstood lemming, hard disks do all jump off a cliff together. Studies have shown that there is a strong corollary to disk failure and a shared manufacturing batch. Simply put, if they are made around the same time if one has a failure there is a likelihood, around 30%, other drives in that batch will also suffer failures. So, what are we paying for with an enterprise drive besides speed? Data reliability. Enterprise level drives have more robust error correction than their consumer counterparts. On a normal hard drive the smallest piece of data that can be written is 512 bytes. This is the size of a sector. Enterprise drives usually have 520 byte sector 8 bytes are used to verify the data in that sector, this is the Data Integrity Field. DIF isn’t 100% ether. It is more reliable than a consumer drive without it. You can still have write corruption for several reasons. Misdirected writes occur when data is written to the wrong location on disk and reported as a successful write. When the system goes to access again you get a read fault. Torn pages, which we are familiar with, is when an 8k page write is requested but only part of the 8k is actually reported. Corruption outside the drive where the controller makes a bad request to write but it is a perfectly legitimate I/O request at the hard drive level. With larger drives the odds of hitting one of these errors becomes a real possibility. Enterprise drives add this extra layer of protection. Your RAID HBA may also have additional error correction. The last thing I would like to touch on is write catching. Without a battery backup, or if the cache non-volatile in nature, you will loose data on a power failure if a write is in progress.

RAID Host Bus Adapter Reliability

The adapter is as reliable as any other component in your system. Normally, the cache on the controller is ECC based. Also, you usually have the option of a battery module to supply the cache with power incase of an outage so the data in cache can be written to the array when everything comes back up. Most of the issues I have seen with RAID HBAs is almost always driver or firmware related. You may also see inconsistent performance due to write catching and the battery backup unit. The unit has to be taken off line and conditioned to keep it in top condition. The side effect is a temporary disabling of the write cache on the controller. You can override this setting on some controllers but it is dangerous proposition. I personal anecdote from my days at a large computer manufacturer, we started getting a larger volume of failed drive calls into support. We started doing failure analysis. It all pointed back to a particular batch of hard drives. That was when the drive manufacturer made a change in its drives removing very small component. It shaved a few cents off the cost but had a dramatic effect. All the drives were technically good and would pass validation. Under a enough load and attached to a particular RAID HBA they would randomly fall off line. It came down to the little component. It provided a little bit of electrical noise suppression on the SCSI bus. Some cards were effected and others chugged along just fine. This is also confirmed by the Google paper, they observed the same behavior. They also point out that 20% to 30% of all returned drives have no detectible problems. The point is validate your entire I/O stack. Any single component may be within specification but may not play well with others.

RAID Parity, Mirroring, and Recoverability

Not to belabor the point, RAID isn’t bullet proof. People rap RAID round themselves like Superman’s cape. There are several issues that all the RAID schemes in the world don’t protect against. With current hard disks in the two terabyte range it is possible to build even a small RAID 5 array and have potential for complete failure. The problem is the amount of data that has to be read for the rebuild process. Having a hot spare available reduces the time to replace a failed drive to zero but that is only part of the equation. The much larger part is rebuild time. Lets say you have a 14 drive RAID 5 array with the new two terabyte drives installed and suffer a failure. If you have no activity on the array and all the IO is detected to the rebuilt it could still take two or three days to rebuild the array. During that time you are effectively running on a RAID 0 array that is now under load. Your chance of total array failure is near 100%. RAID by its very nature assumes a failure is a hard failure. A drive goes off line and the redundant part of the system takes over. It also makes the assumption that if a write succeeds then, barring a hardware failure, the read will also be valid. Data is only validated on writes not on reads. If it was RAID 5 would be twice as slow on reads and four times as slow on writes as a single drive or RAID 0. With all the potential hidden write failures it is completely possible to have hidden corruption and not know it until it is way to late. RAID levels with striped parity are most susceptible to this kind of silent creeping corruption. It is possible that the corrupted data is in the parity stripe making it completely unusable for data reconstruction. If that particular piece of data doesn’t change you can go a very long time with a RAID 5 array with polluted parity. You know how to recover from a polluted parity stripe? Simple, copy all the data off the array, figure out which files are now corrupt and restore them. RAID 6 with its dual stripes makes it more likely to recover your data from a single parity stripe becoming corrupt. You do pay a price in write speed for that extra level of protection. RAID 1 and RAID 10 aren’t perfect ether. On a mirrored pair if the write is assumed good there is no way to validate that on read. Without a third piece of information, like a checksum, it would be a coin toss. If the read is successful there is no way to tell which drive has the bad data. It is possible to have a mirrored pair run just fine with one giving you corrupted data on reads all day long. It would manifest itself as file corruption or some other anomaly that could be difficult to track down. We are back to relying on the disk to tell us all is well. We often recommend RAID 10 over everything else for speed and reliability, and I still hold to that. RAID 10 can still suffer from a catastrophic failure due to a single mirrored pair failing at the same time. With the probability of correlated disk failures it can’t be ignored.

What Can We Do?

There are a few tools available to us that can help predict the failure of a drive or that something is wrong with the array. All modern drives support the SMART protocol. Even though Google found it wasn’t as useful and wasn’t 100% reliable, closer to 30%, some warning is better than none in my opinion. All modern RAID HBA’s also come with tools to detect parity errors. You do take a hit when you run these internal consistency checks. Just like you run maintenance on your databases via DBCC your RAID arrays need checkups too. They are a necessary evil if you don’t want any surprises one day when you have a failed drive in your RAID 5 array and can’t rebuild it. If you have intermittent problems with a drive, don’t mess around, replace it. The HBA almost always has the ability to send SNMP messages to something like nagios or HP Openview, Use it. If you aren’t running something like that usually you can configure email alerts on error to go out. Proactive is the name of the game.

Don’t take my word for it….

Short list of papers to get you started on your path to paranoia.

Google Disk Failure analysis

Original RAID Paper

NetApp disk failure analysis

CERN data corruption tests

Silent Data Corruption in SATA arrays

Series To Date:
  1. Introduction
  2. The Basics of Spinning Disks
  3. The System Bus
  4. Disk Controllers, Host Bus Adapters and Interfaces
  5. RAID, An Introduction
  6. RAID and Hard Disk Reliability, Under The Covers – You are here!
  7. Stripe Size, Block Size, and IO Patterns
  8. Capturing IO Patterns
  9. Testing IO Systems