Tag: TPS

Posted on

Part 4 – Which HDD for Content Applications – Database Workloads

Part 4 – Which HDD for Content Applications – Database Workloads

data base server storage I/O trends

Updated 1/23/2018
Which enterprise HDD to use with a content server platform for database workloads

Insight for effective server storage I/O decision making
Server StorageIO Lab Review

Which enterprise HDD to use for content servers

This is the fourth in a multi-part series (read part three here) based on a white paper hands-on lab report I did compliments of Servers Direct and Seagate that you can read in PDF form here. The focus is looking at the Servers Direct (www.serversdirect.com) converged Content Solution platforms with Seagate Enterprise Hard Disk Drive (HDD’s). In this post the focus expands to database application workloads that were run to test various HDD’s.

Database Reads/Writes

Transaction Processing Council (TPC) TPC-C like workloads were run against the SUT from the STI. These workloads simulated transactional, content management, meta-data and key-value processing. Microsoft SQL Server 2012 was configured and used with databases (each 470GB e.g. scale 6000) created and workload generated by virtual users via Dell Benchmark Factory (running on STI Windows 2012 R2).

A single SQL Server database instance (8) was used on the SUT, however unique databases were created for each HDD set being tested. Both the main database file (.mdf) and the log file (.ldf) were placed on the same drive set being tested, keep in mind the constraints mentioned above. As time was a constraint, database workloads were run concurrent (9) with each other except for the Enterprise 10K RAID 1 and RAID 10. Workload was run with two 10K HDD’s in a RAID 1 configuration, then another workload run with a four drive RAID 10. In a production environment, ideally the .mdf and .ldf would be placed on separate HDD’s and SSDs.

To improve cache buffering the SQL Server database instance memory could be increased from 16GB to a larger number that would yield higher TPS numbers. Keep in mind the objective was not to see how fast I could make the databases run, rather how the different drives handled the workload.

(Note 8) The SQL Server Tempdb was placed on a separate NVMe flash SSD, also the database instance memory size was set to 16GB which was shared by all databases and virtual users accessing it.

(Note 9) Each user step was run for 90 minutes with a 30 minute warm-up preamble to measure steady-state operation.

Users

TPCC Like TPS

Single Drive Cost per TPS

Drive Cost per TPS

Single Drive Cost / Per GB Raw Cap.

Cost / Per GB Usable (Protected) Cap.

Drive Cost (Multiple Drives)

Protect
Space Over head

Cost per usable GB per TPS

Resp. Time (Sec.)

ENT 15K R1

1

23.9

$24.94

$49.89

$0.99

$0.99

$1,190

100%

$49.89

0.01

ENT 10K R1

1

23.4

$37.38

$74.77

$0.49

$0.49

$1,750

100%

$74.77

0.01

ENT CAP R1

1

16.4

$24.26

$48.52

$0.20

$0.20

$ 798

100%

$48.52

0.03

ENT 10K R10

1

23.2

$37.70

$150.78

$0.49

$0.97

$3,500

100%

$150.78

0.07

ENT CAP SWR5

1

17.0

$23.45

$117.24

$0.20

$0.25

$1,995

20%

$117.24

0.02

ENT 15K R1

20

362.3

$1.64

$3.28

$0.99

$0.99

$1,190

100%

$3.28

0.02

ENT 10K R1

20

339.3

$2.58

$5.16

$0.49

$0.49

$1,750

100%

$5.16

0.01

ENT CAP R1

20

213.4

$1.87

$3.74

$0.20

$0.20

$ 798

100%

$3.74

0.06

ENT 10K R10

20

389.0

$2.25

$9.00

$0.49

$0.97

$3,500

100%

$9.00

0.02

ENT CAP SWR5

20

216.8

$1.84

$9.20

$0.20

$0.25

$1,995

20%

$9.20

0.06

ENT 15K R1

50

417.3

$1.43

$2.85

$0.99

$0.99

$1,190

100%

$2.85

0.08

ENT 10K R1

50

385.8

$2.27

$4.54

$0.49

$0.49

$1,750

100%

$4.54

0.09

ENT CAP R1

50

103.5

$3.85

$7.71

$0.20

$0.20

$ 798

100%

$7.71

0.45

ENT 10K R10

50

778.3

$1.12

$4.50

$0.49

$0.97

$3,500

100%

$4.50

0.03

ENT CAP SWR5

50

109.3

$3.65

$18.26

$0.20

$0.25

$1,995

20%

$18.26

0.42

ENT 15K R1

100

190.7

$3.12

$6.24

$0.99

$0.99

$1,190

100%

$6.24

0.49

ENT 10K R1

100

175.9

$4.98

$9.95

$0.49

$0.49

$1,750

100%

$9.95

0.53

ENT CAP R1

100

59.1

$6.76

$13.51

$0.20

$0.20

$ 798

100%

$13.51

1.66

ENT 10K R10

100

560.6

$1.56

$6.24

$0.49

$0.97

$3,500

100%

$6.24

0.14

ENT CAP SWR5

100

62.2

$6.42

$32.10

$0.20

$0.25

$1,995

20%

$32.10

1.57

Table-2 TPC-C workload results various number of users across different drive configurations

Figure-2 shows TPC-C TPS (red dashed line) workload scaling over various number of users (1, 20, 50, and 100) with peak TPS per drive shown. Also shown is the used space capacity (in green), with total raw storage capacity in blue cross hatch. Looking at the multiple metrics in context shows that the 600GB Enterprise 15K HDD with performance enhanced cache is a premium option as an alternative, or, to complement flash SSD solutions.

database TPCC transactional workloads
Figure-2 472GB Database TPS scaling along with cost per TPS and storage space used

In figure-2, the 1.8TB Enterprise 10K HDD with performance enhanced cache while not as fast as the 15K, provides a good balance of performance, space capacity and cost effectiveness. A good use for the 10K drives is where some amount of performance is needed as well as a large amount of storage space for less frequently accessed content.

A low cost, low performance option would be the 2TB Enterprise Capacity HDD’s that have a good cost per capacity, however lack the performance of the 15K and 10K drives with enhanced performance cache. A four drive RAID 10 along with a five drive software volume (Microsoft WIndows) are also shown. For apples to apples comparison look at costs vs. capacity including number of drives needed for a given level of performance.

Figure-3 is a variation of figure-2 showing TPC-C TPS (blue bar) and response time (red-dashed line) scaling across 1, 20, 50 and 100 users. Once again the Enterprise 15K with enhanced performance cache feature enabled has good performance in an apples to apples RAID 1 comparison.

Note that the best performance was with the four drive RAID 10 using 10K HDD’s Given popularity, a four drive RAID 10 configuration with the 10K drives was used. Not surprising the four 10K drives performed better than the RAID 1 15Ks. Also note using five drives in a software spanned volume provides a large amount of storage capacity and good performance however with a larger drive footprint.

database TPCC transactional workloads scaling
Figure-3 472GB Database TPS scaling along with response time (latency)

From a cost per space capacity perspective, the Enterprise Capacity drives have a good cost per GB. A hybrid solution for environment that do not need ultra-high performance would be to pair a small amount of flash SSD (10) (drives or PCIe cards), as well as the 10K and 15K performance enhanced drives with the Enterprise Capacity HDD (11) along with cache or tiering software.

(Note 10) Refer to Seagate 1200 12 Gbps Enterprise SAS SSD StorageIO lab review

(Note 11) Refer to Enterprise SSHD and Flash SSD Part of an Enterprise Tiered Storage Strategy

Where To Learn More

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

If your environment is using applications that rely on databases, then test resources such as servers, storage, devices using tools that represent your environment. This means moving up the software and technology stack from basic storage I/O benchmark or workload generator tools such as Iometer among others instead using either your own application, or tools that can replay or generate various workloads that represent your environment.

Continue reading part five in this multi-part series here where the focus shifts to large and small file I/O processing workloads.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

Which Enterprise HDD for Content Applications General I/O Performance

Which HDD for Content Applications general I/O Performance

hdd general i/o performance server storage I/O trends

Updated 1/23/2018

Which enterprise HDD to use with a content server platform general I/O performance Insight for effective server storage I/O decision making
Server StorageIO Lab Review

Which enterprise HDD to use for content servers

This is the sixth in a multi-part series (read part five here) based on a white paper hands-on lab report I did compliments of Servers Direct and Seagate that you can read in PDF form here. The focus is looking at the Servers Direct (www.serversdirect.com) converged Content Solution platforms with Seagate Enterprise Hard Disk Drive (HDD’s). In this post the focus is around general I/O performance including 8KB and 128KB IOP sizes.

General I/O Performance

In addition to running database and file (large and small) processing workloads, Vdbench was also used to collect basic small (8KB) and large (128KB) sized I/O operations. This consisted of random and sequential reads as well as writes with the results shown below. In addition to using vdbench, other tools that could be used include Microsoft Diskspd, fio, iorate and iometer among many others.

These workloads used Vdbench configured (13) to do direct I/O to a Windows file system mounted device using as much of the available disk space as possible. All workloads used 16 threads and were run concurrently similar to database and file processing tests.

(Note 13) Sample vdbench configuration for general I/O, note different settings were used for various tests

Table-7 shows workload results for 8KB random IOPs 75% reads and 75% writes including IOPs, bandwidth and response time.

 

ENT 15K RAID1

ENT 10K RAID1

ENT CAP RAID1

ENT 10K R10
(4 Drives)

ECAP SW RAID (5 Drives)

 

75% Read

25% Read

75% Read

25% Read

75% Read

25% Read

75% Read

25% Read

75% Read

25% Read

I/O Rate (IOPs)

597.11

559.26

514

475

285

293

979

984

491

644

MB/sec

4.7

4.4

4.0

3.7

2.2

2.3

7.7

7.7

3.8

5.0

Resp. Time (Sec.)

25.9

27.6

30.2

32.7

55.5

53.7

16.3

16.3

32.6

24.8

Table-7 8KB sized random IOPs workload results

Figure-6 shows small (8KB) random I/O (75% read and 25% read) across different HDD configurations. Performance including activity rates (e.g. IOPs), bandwidth and response time for mixed reads / writes are shown. Note how response time increases with the Enterprise Capacity configurations vs. other performance optimized drives.

general 8K random IO
Figure-6 8KB random reads and write showing IOP activity, bandwidth and response time

Table-8 below shows workload results for 8GB sized I/Os 100% sequential with 75% reads and 75% writes including IOPs, MB/sec and response time in seconds.

ENT 15K RAID1

ENT 10K RAID1

ENT CAP RAID1

ENT 10K R10
(4 Drives)

ECAP SW RAID (5 Drives)

75% Read

25% Read

75% Read

25% Read

75% Read

25% Read

75% Read

25% Read

75% Read

25% Read

I/O Rate (IOPs)

3,778

3,414

3,761

3,986

3,379

1,274

11,840

8,368

2,891

1,146

MB/sec

29.5

26.7

29.4

31.1

26.4

10.0

92.5

65.4

22.6

9.0

Resp. Time (Sec.)

2.2

3.1

2.3

2.4

2.7

10.9

1.3

1.9

5.5

14.0

Table-8 8KB sized sequential workload results

Figure-7 shows small 8KB sequential mixed reads and writes (75% read and 75% write), while the Enterprise Capacity 2TB HDD has a large amount of space capacity, its performance in a RAID 1 vs. other similar configured drives is slower.

8KB Sequential
Figure-7 8KB sequential 75% reads and 75% write showing bandwidth activity

Table-9 shows workload results for 100% sequential, 100% read and 100% write 128KB sized I/Os including IOPs, bandwidth and response time.

ENT 15K RAID1

ENT 10K RAID1

ENT CAP RAID1

ENT 10K R10
(4 Drives)

ECAP SW RAID (5 Drives)

Read

Write

Read

Write

Read

Write

Read

Write

Read

Write

I/O Rate (IOPs)

1,798

1,771

1,716

1,688

921

912

3,552

3,486

780

721

MB/sec

224.7

221.3

214.5

210.9

115.2

114.0

444.0

435.8

97.4

90.1

Resp. Time (Sec.)

8.9

9.0

9.3

9.5

17.4

17.5

4.5

4.6

19.3

20.2

Table-9 128KB sized sequential workload results

Figure-8 shows sequential or streaming operations of larger I/O (100% read and 100% write) requests sizes (128KB) that would be found with large content applications. Figure-8 highlights the relationship between lower response time and increased IOPs as well as bandwidth.

128K Sequential
Figure-8 128KB sequential reads and write showing IOP activity, bandwidth and response time

Where To Learn More

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

Some content applications are doing small random I/Os for database, key value stores or repositories as well as meta data processing while others are doing large sequential I/O. 128KB sized I/O may be large for your environment, on the other hand, with an increasing number of applications, file systems, software defined storage management tools among others, 1 to 10MB or even larger I/O sizes are becoming common. Key is selecting I/O sizes and read write as well as random sequential along with I/O or queue depths that align with your environment.

Continue reading part seven the final post in this multi-part series here where the focus is around how HDD’s continue to evolve including performance beyond traditional RPM based execrations along with wrap up.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

Big Files Lots of Little File Processing Benchmarking with Vdbench

Big Files Lots of Little File Processing Benchmarking with Vdbench


server storage data infrastructure i/o File Processing Benchmarking with Vdbench

Updated 2/10/2018

Need to test a server, storage I/O networking, hardware, software, services, cloud, virtual, physical or other environment that is either doing some form of file processing, or, that you simply want to have some extra workload running in the background for what ever reason? An option is File Processing Benchmarking with Vdbench.

I/O performance

Getting Started


Here’s a quick and relatively easy way to do it with Vdbench (Free from Oracle). Granted there are other tools, both for free and for fee that can similar things, however we will leave those for another day and post. Here’s the con to this approach, there is no Uui Gui like what you have available with some other tools Here’s the pro to this approach, its free, flexible and limited by your creative, amount of storage space, server memory and I/O capacity.

If you need a background on Vdbench and benchmarking, check out the series of related posts here (e.g. www.storageio.com/performance).

Get and Install the Vdbench Bits and Bytes


If you do not already have Vdbench installed, get a copy from the Oracle or Source Forge site (now points to Oracle here).

Vdbench is free, you simply sign-up and accept the free license, select the version down load (it is a single, common distribution for all OS) the bits as well as documentation.

Installation particular on Windows is really easy, basically follow the instructions in the documentation by copying the contents of the download folder to a specified directory, set up any environment variables, and make sure that you have Java installed.

Here is a hint and tip for Windows Servers, if you get an error message about counters, open a command prompt with Administrator rights, and type the command:

$ lodctr /r


The above command will reset your I/O counters. Note however that command will also overwrite counters if enabled so only use it if you have to.

Likewise *nix install is also easy, copy the files, make sure to copy the applicable *nix shell script (they are in the download folder), and verify Java is installed and working.

You can do a vdbench -t (windows) or ./vdbench -t (*nix) to verify that it is working.

Vdbench File Processing

There are many options with Vdbench as it has a very robust command and scripting language including ability to set up for loops among other things. We are only going to touch the surface here using its file processing capabilities. Likewise, Vdbench can run from a single server accessing multiple storage systems or file systems, as well as running from multiple servers to a single file system. For simplicity, we will stick with the basics in the following examples to exercise a local file system. The limits on the number of files and file size are limited by server memory and storage space.

You can specify number and depth of directories to put files into for processing. One of the parameters is the anchor point for the file processing, in the following examples =S:\SIOTEMP\FS1 is used as the anchor point. Other parameters include the I/O size, percent reads, number of threads, run time and sample interval as well as output folder name for the result files. Note that unlike some tools, Vdbench does not create a single file of results, rather a folder with several files including summary, totals, parameters, histograms, CSV among others.


Simple Vdbench File Processing Commands

For flexibility and ease of use I put the following three Vdbench commands into a simple text file that is then called with parameters on the command line.
fsd=fsd1,anchor=!fanchor,depth=!dirdep,width=!dirwid,files=!numfiles,size=!filesize

fwd=fwd1,fsd=fsd1,rdpct=!filrdpct,xfersize=!fxfersize,fileselect=random,fileio=random,threads=!thrds

rd=rd1,fwd=fwd1,fwdrate=max,format=yes,elapsed=!etime,interval=!itime

Simple Vdbench script

# SIO_vdbench_filesystest.txt

#

# Example Vdbench script for file processing

#

# fanchor = file system place  where directories and files will be created

# dirwid = how wide should the directories be (e.g. how many directories wide)

# numfiles = how many files per directory

# filesize = size in in k, m, g e.g. 16k = 16KBytes

# fxfersize = file I/O transfer size in kbytes

# thrds = how many threads or workers

# etime = how long to run in minutes (m) or hours (h)

# itime = interval sample time e.g. 30 seconds

# dirdep = how deep the directory tree

# filrdpct = percent of reads e.g. 90 = 90 percent reads

# -p processnumber = optional specify a process number, only needed if running multiple vdbenchs at same time, number should be unique

# -o output file that describes what being done and some config info

#

# Sample command line shown for Windows, for *nix add ./

#

# The real Vdbench script with command line parameters indicated by !=

#


fsd=fsd1,anchor=!fanchor,depth=!dirdep,width=!dirwid,files=!numfiles,size=!filesize


fwd=fwd1,fsd=fsd1,rdpct=!filrdpct,xfersize=!fxfersize,fileselect=random,fileio=random,threads=!thrds


rd=rd1,fwd=fwd1,fwdrate=max,format=yes,elapsed=!etime,interval=!itime

Big Files Processing Script


With the above script file defined, for Big Files I specify a command line such as the following.
$ vdbench -f SIO_vdbench_filesystest.txt fanchor=S:\SIOTemp\FS1 dirwid=1 numfiles=60 filesize=5G fxfersize=128k thrds=64 etime=10h itime=30 numdir=1 dirdep=1 filrdpct=90 -p 5576 -o SIOWS2012R220_NOFUZE_5Gx60_BigFiles_64TH_STX1200_020116

Big Files Processing Example Results


The following is one of the result files from the folder of results created via the above command for Big File processing showing totals.



Run totals


21:09:36.001 Starting RD=format_for_rd1


Feb 01, 2016 .Interval. .ReqstdOps.. ...cpu%...  read ....read.... ...write.... ..mb/sec... mb/sec .xfer.. ...mkdir... ...rmdir... ..create... ...open.... ...close... ..delete...

                          rate  resp total  sys   pct   rate  resp   rate  resp  read write  total    size  rate  resp  rate  resp  rate  resp  rate  resp  rate  resp  rate  resp

21:23:34.101   avg_2-28 2848.2  2.70   8.8 8.32   0.0    0.0  0.00 2848.2  2.70  0.00 356.0 356.02  131071   0.0  0.00   0.0  0.00   0.1 109176   0.1  0.55   0.1  2006   0.0  0.00


21:23:35.009 Starting RD=rd1; elapsed=36000; fwdrate=max. For loops: None


07:23:35.000 avg_2-1200 4939.5  1.62  18.5 17.3  90.0 4445.8  1.79  493.7  0.07 555.7 61.72 617.44  131071   0.0  0.00   0.0  0.00   0.0  0.00   0.1  0.03   0.1  2.95   0.0  0.00

Lots of Little Files Processing Script


For lots of little files, the following is used.



$ vdbench -f SIO_vdbench_filesystest.txt fanchor=S:\SIOTEMP\FS1 dirwid=64 numfiles=25600 filesize=16k fxfersize=1k thrds=64 etime=10h itime=30 dirdep=1 filrdpct=90 -p 5576 -o SIOWS2012R220_NOFUZE_SmallFiles_64TH_STX1200_020116

Lots of Little Files Processing Example Results


The following is one of the result files from the folder of results created via the above command for Big File processing showing totals.
Run totals


09:17:38.001 Starting RD=format_for_rd1


Feb 02, 2016 .Interval. .ReqstdOps.. ...cpu%...  read ....read.... ...write.... ..mb/sec... mb/sec .xfer.. ...mkdir... ...rmdir... ..create... ...open.... ...close... ..delete...

                          rate  resp total  sys   pct   rate  resp   rate  resp  read write  total    size  rate  resp  rate  resp  rate  resp  rate  resp  rate  resp  rate  resp

09:19:48.016    avg_2-5  10138  0.14  75.7 64.6   0.0    0.0  0.00  10138  0.14  0.00 158.4 158.42   16384   0.0  0.00   0.0  0.00 10138  0.65 10138  0.43 10138  0.05   0.0  0.00


09:19:49.000 Starting RD=rd1; elapsed=36000; fwdrate=max. For loops: None


19:19:49.001 avg_2-1200 113049  0.41  67.0 55.0  90.0 101747  0.19  11302  2.42 99.36 11.04 110.40    1023   0.0  0.00   0.0  0.00   0.0  0.00  7065  0.85  7065  1.60   0.0  0.00

Where To Learn More

View additional NAS, NVMe, SSD, NVM, SCM, Data Infrastructure and HDD related topics via the following links.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

The above examples can easily be modified to do different things particular if you read the Vdbench documentation on how to setup multi-host, multi-storage system, multiple job streams to do different types of processing. This means you can benchmark a storage systems, server or converged and hyper-converged platform, or simply put a workload on it as part of other testing. There are even options for handling data footprint reduction such as compression and dedupe.

Ok, nuff said, for now.

Gs

Greg Schulz - Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

How to test your HDD SSD or all flash array (AFA) storage fundamentals

How to test your HDD SSD AFA Hybrid or cloud storage

server storage data infrastructure i/o hdd ssd all flash array afa fundamentals

Updated 2/14/2018

Over at BizTech Magazine I have a new article 4 Ways to Performance Test Your New HDD or SSD that provides a quick guide to verifying or learning what the speed characteristic of your new storage device are capable of.

An out-take from the article used by BizTech as a "tease" is:

These four steps will help you evaluate new storage drives. And … psst … we included the metrics that matter.

Building off the basics, server storage I/O benchmark fundamentals

The four basic steps in the article are:

  • Plan what and how you are going to test (what’s applicable for you)
  • Decide on a benchmarking tool (learn about various tools here)
  • Test the test (find bugs, errors before a long running test)
  • Focus on metrics that matter (what’s important for your environment)

Server Storage I/O performance

Where To Learn More

View additional NAS, NVMe, SSD, NVM, SCM, Data Infrastructure and HDD related topics via the following links.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

To some the above (read the full article here) may seem like common sense tips and things everybody should know otoh there are many people who are new to servers storage I/O networking hardware software cloud virtual along with various applications, not to mention different tools.

Thus the above is a refresher for some (e.g. Dejavu) while for others it might be new and revolutionary or simply helpful. Interested in HDD’s, SSD’s as well as other server storage I/O performance along with benchmarking tools, techniques and trends check out the collection of links here (Server and Storage I/O Benchmarking and Performance Resources).

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

Server Storage I/O Benchmark Performance Resource Tools

Server Storage I/O Benchmarking Performance Resource Tools

server storage I/O trends

Updated 1/23/2018

Server storage I/O benchmark performance resource tools, various articles and tips. These include tools for legacy, virtual, cloud and software defined environments.

benchmark performance resource tools server storage I/O performance

The best server and storage I/O (input/output operation) is the one that you do not have to do, the second best is the one with the least impact.

server storage I/O locality of reference

This is where the idea of locality of reference (e.g. how close is the data to where your application is running) comes into play which is implemented via tiered memory, storage and caching shown in the figure above.

Cloud virtual software defined storage I/O

Server storage I/O performance applies to cloud, virtual, software defined and legacy environments

What this has to do with server storage I/O (and networking) performance benchmarking is keeping the idea of locality of reference, context and the application workload in perspective regardless of if cloud, virtual, software defined or legacy physical environments.

StorageIOblog: I/O, I/O how well do you know about good or bad server and storage I/Os?
StorageIOblog: Server and Storage I/O benchmarking 101 for smarties
StorageIOblog: Which Enterprise HDDs to use for a Content Server Platform (7 part series with using benchmark tools)
StorageIO.com: Enmotus FuzeDrive MicroTiering lab test using various tools
StorageIOblog: Some server storage I/O benchmark tools, workload scripts and examples (Part I) and (Part II)
StorageIOblog: Get in the NVMe SSD game (if you are not already)
Doridmen.com: Transcend SSD360S Review with tips on using ATTO and Crystal benchmark tools
ComputerWeekly: Storage performance metrics: How suppliers spin performance specifications

Via StorageIO Podcast: Kevin Closson discusses SLOB Server CPU I/O Database Performance benchmarks
Via @KevinClosson: SLOB Use Cases By Industry Vendors. Learn SLOB, Speak The Experts’ Language
Via BeyondTheBlocks (Reduxio): 8 Useful Tools for Storage I/O Benchmarking
Via CCSIObench: Cold-cache Sequential I/O Benchmark
Doridmen.com: Transcend SSD360S Review with tips on using ATTO and Crystal benchmark tools
CISJournal: Benchmarking the Performance of Microsoft Hyper-V server, VMware ESXi and Xen Hypervisors (PDF)
Microsoft TechNet:Windows Server 2016 Hyper-V large-scale VM performance for in-memory transaction processing
InfoStor: What’s The Best Storage Benchmark?
StorageIOblog: How to test your HDD, SSD or all flash array (AFA) storage fundamentals
Via ATTO: Atto V3.05 free storage test tool available
Via StorageIOblog: Big Files and Lots of Little File Processing and Benchmarking with Vdbench

Via StorageIO.com: Which Enterprise Hard Disk Drives (HDDs) to use with a Content Server Platform (White Paper)
Via VMware Blogs: A Free Storage Performance Testing Tool For Hyperconverged
Microsoft Technet: Test Storage Spaces Performance Using Synthetic Workloads in Windows Server
Microsoft Technet: Microsoft Windows Server Storage Spaces – Designing for Performance
BizTech: 4 Ways to Performance-Test Your New HDD or SSD
EnterpriseStorageForum: Data Storage Benchmarking Guide
StorageSearch.com: How fast can your SSD run backwards?
OpenStack: How to calculate IOPS for Cinder Storage ?
StorageAcceleration: Tips for Measuring Your Storage Acceleration

server storage I/O STI and SUT

Spiceworks: Determining HDD SSD SSHD IOP Performance
Spiceworks: Calculating IOPS from Perfmon data
Spiceworks: profiling IOPs

vdbench server storage I/O benchmark
Vdbench example via StorageIOblog.com

StorageIOblog: What does server storage I/O scaling mean to you?
StorageIOblog: What is the best kind of IO? The one you do not have to do
Testmyworkload.com: Collect and report various OS workloads
Whoishostingthis: Various SQL resources
StorageAcceleration: What, When, Why & How to Accelerate Storage
Filesystems.org: Various tools and links
StorageIOblog: Can we get a side of context with them IOPS and other storage metrics?

flash ssd and hdd

BrightTalk Webinar: Data Center Monitoring – Metrics that Matter for Effective Management
StorageIOblog: Enterprise SSHD and Flash SSD Part of an Enterprise Tiered Storage Strategy
StorageIOblog: Has SSD put Hard Disk Drives (HDD’s) On Endangered Species List?

server storage I/O bottlenecks and I/O blender

Microsoft TechNet: Measuring Disk Latency with Windows Performance Monitor (Perfmon)
Via Scalegrid.io: How to benchmark MongoDB with YCSB? (Perfmon)
Microsoft MSDN: List of Perfmon counters for sql server
Microsoft TechNet: Taking Your Server’s Pulse
StorageIOblog: Part II: How many IOPS can a HDD, HHDD or SSD do with VMware?
CMG: I/O Performance Issues and Impacts on Time-Sensitive Applications

flash ssd and hdd

Virtualization Practice: IO IO it is off to Storage and IO metrics we go
InfoStor: Is HP Short Stroking for Performance and Capacity Gains?
StorageIOblog: Is Computer Data Storage Complex? It Depends
StorageIOblog: More storage and IO metrics that matter
StorageIOblog: Moving Beyond the Benchmark Brouhaha
Yellow-Bricks: VSAN VDI Benchmarking and Beta refresh!

server storage I/O benchmark example

YellowBricks: VSAN performance: many SAS low capacity VS some SATA high capacity?
YellowBricsk: VSAN VDI Benchmarking and Beta refresh!
StorageIOblog: Seagate 1200 12Gbs Enterprise SAS SSD StorgeIO lab review
StorageIOblog: Part II: Seagate 1200 12Gbs Enterprise SAS SSD StorgeIO lab review
StorageIOblog: Server Storage I/O Network Benchmark Winter Olympic Games

flash ssd and hdd

VMware VDImark aka View Planner (also here, here and here) as well as VMmark here
StorageIOblog: SPC and Storage Benchmarking Games
StorageIOblog: Speaking of speeding up business with SSD storage
StorageIOblog: SSD and Storage System Performance

Hadoop server storage I/O performance
Various Server Storage I/O tools in a hadoop environment

Michael-noll.com: Benchmarking and Stress Testing an Hadoop Cluster With TeraSort, TestDFSIO
Virtualization Practice: SSD options for Virtual (and Physical) Environments Part I: Spinning up to speed on SSD
StorageIOblog: Storage and IO metrics that matter
InfoStor: Storage Metrics and Measurements That Matter: Getting Started
SilvertonConsulting: Storage throughput vs. IO response time and why it matters
Splunk: The percentage of Read / Write utilization to get to 800 IOPS?

flash ssd and hdd
Various server storage I/O benchmarking tools

Spiceworks: What is the best IO IOPs testing tool out there
StorageIOblog: How many IOPS can a HDD, HHDD or SSD do?
StorageIOblog: Some Windows Server Storage I/O related commands
Openmaniak: Iperf overview and Iperf.fr: Iperf overview
StorageIOblog: Server and Storage I/O Benchmark Tools: Microsoft Diskspd (Part I and Part II)
Quest: SQL Server Perfmon Poster (PDF)
Server and Storage I/O Networking Performance Management (webinar)
Data Center Monitoring – Metrics that Matter for Effective Management (webinar)
Flash back to reality – Flash SSD Myths and Realities (Industry trends & benchmarking tips), (MSP CMG presentation)
DBAstackexchange: How can I determine how many IOPs I need for my AWS RDS database?
ITToolbox: Benchmarking the Performance of SANs

server storage IO labs

StorageIOblog: Dell Inspiron 660 i660, Virtual Server Diamond in the rough (Server review)
StorageIOblog: Part II: Lenovo TS140 Server and Storage I/O Review (Server review)
StorageIOblog: DIY converged server software defined storage on a budget using Lenovo TS140
StorageIOblog: Server storage I/O Intel NUC nick knack notes First impressions (Server review)
StorageIOblog & ITKE: Storage performance needs availability, availability needs performance
StorageIOblog: Why SSD based arrays and storage appliances can be a good idea (Part I)
StorageIOblog: Revisiting RAID storage remains relevant and resources

Interested in cloud and object storage visit our objectstoragecenter.com page, for flash SSD checkout storageio.com/ssd page, along with data protection, RAID, various industry links and more here.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

Watch for additional links to be added above in addition to those that appear via comments.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

I/O, I/O how well do you know good bad ugly server storage I/O iops?

How well do you know good bad ugly I/O iops?

server storage i/o iops activity data infrastructure trends

Updated 2/10/2018

There are many different types of server storage I/O iops associated with various environments, applications and workloads. Some I/Os activity are iops, others are transactions per second (TPS), files or messages per time (hour, minute, second), gets, puts or other operations. The best IO is one you do not have to do.

What about all the cloud, virtual, software defined and legacy based application that still need to do I/O?

If no IO operation is the best IO, then the second best IO is the one that can be done as close to the application and processor as possible with the best locality of reference.

Also keep in mind that aggregation (e.g. consolidation) can cause aggravation (server storage I/O performance bottlenecks).

aggregation causes aggravation
Example of aggregation (consolidation) causing aggravation (server storage i/o blender bottlenecks)

And the third best?

It’s the one that can be done in less time or at least cost or effect to the requesting application, which means moving further down the memory and storage stack.

solving server storage i/o blender and other bottlenecks
Leveraging flash SSD and cache technologies to find and fix server storage I/O bottlenecks

On the other hand, any IOP regardless of if for block, file or object storage that involves some context is better than those without, particular involving metrics that matter (here, here and here [webinar] )

Server Storage I/O optimization and effectiveness

The problem with IO’s is that they are a basic operations to get data into and out of a computer or processor, so there’s no way to avoid all of them, unless you have a very large budget. Even if you have a large budget that can afford an all flash SSD solution, you may still meet bottlenecks or other barriers.

IO’s require CPU or processor time and memory to set up and then process the results as well as IO and networking resources to move data too their destination or retrieve them from where they are stored. While IO’s cannot be eliminated, their impact can be greatly improved or optimized by, among other techniques, doing fewer of them via caching and by grouping reads or writes (pre-fetch, write-behind).

server storage I/O STI and SUT

Think of it this way: Instead of going on multiple errands, sometimes you can group multiple destinations together making for a shorter, more efficient trip. However, that optimization may also mean your drive will take longer. So, sometimes it makes sense to go on a couple of quick, short, low-latency trips instead of one larger one that takes half a day even as it accomplishes many tasks. Of course, how far you have to go on those trips (i.e., their locality) makes a difference about how many you can do in a given amount of time.

Locality of reference (or proximity)

What is locality of reference?

This refers to how close (i.e., its place) data exists to where it is needed (being referenced) for use. For example, the best locality of reference in a computer would be registers in the processor core, ready to be acted on immediately. This would be followed by levels 1, 2, and 3 (L1, L2, and L3) onboard caches, followed by main memory, or DRAM. After that comes solid-state memory typically NAND flash either on PCIe cards or accessible on a direct attached storage (DAS), SAN, or NAS device. 

server storage I/O locality of reference

Even though a PCIe NAND flash card is close to the processor, there still remains the overhead of traversing the PCIe bus and associated drivers. To help offset that impact, PCIe cards use DRAM as cache or buffers for data along with meta or control information to further optimize and improve locality of reference. In other words, this information is used to help with cache hits, cache use, and cache effectiveness vs. simply boosting cache use.

SSD to the rescue?

What can you do the cut the impact of IO’s?

There are many steps one can take, starting with establishing baseline performance and availability metrics.

The metrics that matter include IOP’s, latency, bandwidth, and availability. Then, leverage metrics to gain insight into your application’s performance.

Understand that IO’s are a fact of applications doing work (storing, retrieving, managing data) no matter whether systems are virtual, physical, or running up in the cloud. But it’s important to understand just what a bad IO is, along with its impact on performance. Try to identify those that are bad, and then find and fix the problem, either with software, application, or database changes. Perhaps you need to throw more software caching tools, hypervisors, or hardware at the problem. Hardware may include faster processors with more DRAM and faster internal busses.

Leveraging local PCIe flash SSD cards for caching or as targets is another option.

You may want to use storage systems or appliances that rely on intelligent caching and storage optimization capabilities to help with performance, availability, and capacity.

Where to gain insight into your server storage I/O environment

There are many tools that you can be used to gain insight into your server storage I/O environment across cloud, virtual, software defined and legacy as well as from different layers (e.g. applications, database, file systems, operating systems, hypervisors, server, storage, I/O networking). Many applications along with databases have either built-in or optional tools from their provider, third-party, or via other sources that can give information about work activity being done. Likewise there are tools to dig down deeper into the various data information infrastructure to see what is happening at the various layers as shown in the following figures.

application storage I/O performance
Gaining application and operating system level performance insight via different tools

windows and linux storage I/O performance
Insight and awareness via operating system tools on Windows and Linux

In the above example, Spotlight on Windows (SoW) which you can download for free from Dell here along with Ubuntu utilities are shown, You could also use other tools to look at server storage I/O performance including Windows Perfmon among others.

vmware server storage I/O
Hypervisor performance using VMware ESXi / vsphere built-in tools

vmware server storage I/O performance
Using Visual ESXtop to dig deeper into virtual server storage I/O performance

vmware server storage i/o cache
Gaining insight into virtual server storage I/O cache performance

Wrap up and summary

There are many approaches to address (e.g. find and fix) vs. simply move or mask data center and server storage I/O bottlenecks. Having insight and awareness into how your environment along with applications is important to know to focus resources. Also keep in mind that a bit of flash SSD or DRAM cache in the applicable place can go along way while a lot of cache will also cost you cash. Even if you cant eliminate I/Os, look for ways to decrease their impact on your applications and systems.

Where To Learn More

View additional NAS, NVMe, SSD, NVM, SCM, Data Infrastructure and HDD related topics via the following links.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

>Keep in mind: SSD including flash and DRAM among others are in your future, the question is where, when, with what, how much and whose technology or packaging.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

Revisiting RAID data protection remains relevant resource links

Revisiting RAID data protection remains relevant and resources

Storage I/O trends

Updated 2/10/2018

RAID data protection remains relevant including erasure codes (EC), local reconstruction codes (LRC) among other technologies. If RAID were really not relevant anymore (e.g. actually dead), why do some people spend so much time trying to convince others that it is dead or to use a different RAID level or enhanced RAID or beyond raid with related advanced approaches?

When you hear RAID, what comes to mind?

A legacy monolithic storage system that supports narrow 4, 5 or 6 drive wide stripe sets or a modern system support dozens of drives in a RAID group with different options?

RAID means many things, likewise there are different implementations (hardware, software, systems, adapters, operating systems) with various functionality, some better than others.

For example, which of the items in the following figure come to mind, or perhaps are new to your RAID vocabulary?

RAID questions

There are Many Variations of RAID Storage some for the enterprise, some for SMB, SOHO or consumer. Some have better performance than others, some have poor performance for example causing extra writes that lead to the perception that all parity based RAID do extra writes (some actually do write gathering and optimization).

Some hardware and software implementations using WBC (write back cache) mirrored or battery backed-BBU along with being able to group writes together in memory (cache) to do full stripe writes. The result can be fewer back-end writes compared to other systems. Hence, not all RAID implementations in either hardware or software are the same. Likewise, just because a RAID definition shows a particular theoretical implementation approach does not mean all vendors have implemented it in that way.

RAID is not a replacement for backup rather part of an overall approach to providing data availability and accessibility.

data protection and durability

What’s the best RAID level? The one that meets YOUR needs

There are different RAID levels and implementations (hardware, software, controller, storage system, operating system, adapter among others) for various environments (enterprise, SME, SMB, SOHO, consumer) supporting primary, secondary, tertiary (backup/data protection, archiving).

RAID comparison
General RAID comparisons

Thus one size or approach does fit all solutions, likewise RAID rules of thumbs or guides need context. Context means that a RAID rule or guide for consumer or SOHO or SMB might be different for enterprise and vise versa, not to mention on the type of storage system, number of drives, drive type and capacity among other factors.

RAID comparison
General basic RAID comparisons

Thus the best RAID level is the one that meets your specific needs in your environment. What is best for one environment and application may be different from what is applicable to your needs.

Key points and RAID considerations include:

· Not all RAID implementations are the same, some are very much alive and evolving while others are in need of a rest or rewrite. So it is not the technology or techniques that are often the problem, rather how it is implemented and then deployed.

· It may not be RAID that is dead, rather the solution that uses it, hence if you think a particular storage system, appliance, product or software is old and dead along with its RAID implementation, then just say that product or vendors solution is dead.

· RAID can be implemented in hardware controllers, adapters or storage systems and appliances as well as via software and those have different features, capabilities or constraints.

· Long or slow drive rebuilds are a reality with larger disk drives and parity-based approaches; however, you have options on how to balance performance, availability, capacity, and economics.

· RAID can be single, dual or multiple parity or mirroring-based.

· Erasure and other coding schemes leverage parity schemes and guess what umbrella parity schemes fall under.

· RAID may not be cool, sexy or a fun topic and technology to talk about, however many trendy tools, solutions and services actually use some form or variation of RAID as part of their basic building blocks. This is an example of using new and old things in new ways to help each other do more without increasing complexity.

·  Even if you are not a fan of RAID and think it is old and dead, at least take a few minutes to learn more about what it is that you do not like to update your dead FUD.

Wait, Isn’t RAID dead?

There is some dead marketing that paints a broad picture that RAID is dead to prop up something new, which in some cases may be a derivative variation of parity RAID.

data dispersal
Data dispersal and durability

RAID rebuild improving
RAID continues to evolve with rapid rebuilds for some systems

Otoh, there are some specific products, technologies, implementations that may be end of life or actually dead. Likewise what might be dead, dying or simply not in vogue are specific RAID implementations or packaging. Certainly there is a lot of buzz around object storage, cloud storage, forward error correction (FEC) and erasure coding including messages of how they cut RAID. Catch is that some object storage solutions are overlayed on top of lower level file systems that do things such as RAID 6, granted they are out of sight, out of mind.

RAID comparison
General RAID parity and erasure code/FEC comparisons

Then there are advanced parity protection schemes which include FEC and erasure codes that while they are not your traditional RAID levels, they have characteristic including chunking or sharding data, spreading it out over multiple devices with multiple parity (or derivatives of parity) protection.

Bottom line is that for some environments, different RAID levels may be more applicable and alive than for others.

Via BizTech – How to Turn Storage Networks into Better Performers

  • Maintain Situational Awareness
  • Design for Performance and Availability
  • Determine Networked Server and Storage Patterns
  • Make Use of Applicable Technologies and Techniques

If RAID is alive, what to do with it?

If you are new to RAID, learn more about the past, present and future keeping mind context. Keeping context in mind means that there are different RAID levels and implementations for various environments. Not all RAID 0, 1, 1/0, 10, 2, 3, 4, 5, 6 or other variations (past, present and emerging) are the same for consumer vs. SOHO vs. SMB vs. SME vs. Enterprise, nor are the usage cases. Some need performance for reads, others for writes, some for high-capacity with low performance using hardware or software. RAID Rules of thumb are ok and useful, however keep them in context to what you are doing as well as using.

What to do next?

Take some time to learn, ask questions including what to use when, where, why and how as well as if an approach or recommendation are applicable to your needs. Check out the following links to read some extra perspectives about RAID and keep in mind, what might apply to enterprise may not be relevant for consumer or SMB and vise versa.

Some advise needed on SSD’s and Raid (Via Spiceworks)
RAID 5 URE Rebuild Means The Sky Is Falling (Via BenchmarkReview)
Double drive failures in a RAID-10 configuration (Via SearchStorage)
Industry Trends and Perspectives: RAID Rebuild Rates (Via StorageIOblog)
RAID, IOPS and IO observations (Via StorageIOBlog)
RAID Relevance Revisited (Via StorageIOBlog)
HDDs Are Still Spinning (Rust Never Sleeps) (Via InfoStor)
When and Where to Use NAND Flash SSD for Virtual Servers (Via TheVirtualizationPractice)
What’s the best way to learn about RAID storage? (Via Spiceworks)
Design considerations for the host local FVP architecture (Via Frank Denneman)
Some basic RAID fundamentals and definitions (Via SearchStorage)
Can RAID extend nand flash SSD life? (Via StorageIOBlog)
I/O Performance Issues and Impacts on Time-Sensitive Applications (Via CMG)
The original RAID white paper (PDF) that while over 20 years old, it provides a basis, foundation and some history by Katz, Gibson, Patterson et al
Storage Interview Series (Via Infortrend)
Different RAID methods (Via RAID Recovery Guide)
A good RAID tutorial (Via TheGeekStuff)
Basics of RAID explained (Via ZDNet)
RAID and IOPs (Via VMware Communities)

Where To Learn More

View additional NAS, NVMe, SSD, NVM, SCM, Data Infrastructure and HDD related topics via the following links.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

What is my favorite or preferred RAID level?

That depends, for some things its RAID 1, for others RAID 10 yet for others RAID 4, 5, 6 or DP and yet other situations could be a fit for RAID 0 or erasure codes and FEC. Instead of being focused on just one or two RAID levels as the solution for different problems, I prefer to look at the environment (consumer, SOHO, small or large SMB, SME, enterprise), type of usage (primary or secondary or data protection), performance characteristics, reads, writes, type and number of drives among other factors. What might be a fit for one environment would not be a fit for others, thus my preferred RAID level along with where implemented is the one that meets the given situation. However also keep in mind is tying RAID into part of an overall data protection strategy, remember, RAID is not a replacement for backup.

What this all means

Like other technologies that have been declared dead for years or decades, aka the Zombie technologies (e.g. dead yet still alive) RAID continues to be used while the technologies evolves. There are specific products, implementations or even RAID levels that have faded away, or are declining in some environments, yet alive in others. RAID and its variations are still alive, however how it is used or deployed in conjunction with other technologies also is evolving.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

Can we get a side of context with them IOPS server storage metrics?

Can we get a side of context with them server storage metrics?

Whats the best server storage I/O network metric or benchmark? It depends as there needs to be some context with them IOPS and other server storage I/O metrics that matter.

There is an old saying that the best I/O (Input/Output) is the one that you do not have to do.

In the meantime, let’s get a side of some context with them IOPS from vendors, marketers and their pundits who are tossing them around for server, storage and IO metrics that matter.

Expanding the conversation, the need for more context

The good news is that people are beginning to discuss storage beyond space capacity and cost per GByte, TByte or PByte for both DRAM or nand flash Solid State Devices (SSD), Hard Disk Drives (HDD) along with Hybrid HDD (HHDD) and Solid State Hybrid Drive (SSHD) based solutions. This applies to traditional enterprise or SMB IT data center with physical, virtual or cloud based infrastructures.

hdd and ssd iops

This is good because it expands the conversation beyond just cost for space capacity into other aspects including performance (IOPS, latency, bandwidth) for various workload scenarios along with availability, energy effective and management.

Adding a side of context

The catch is that IOPS while part of the equation are just one aspect of performance and by themselves without context, may have little meaning if not misleading in some situations.

Granted it can be entertaining, fun to talk about or simply make good press copy for a million IOPS. IOPS vary in size depending on the type of work being done, not to mention reads or writes, random and sequential which also have a bearing on data throughout or bandwidth (Mbytes per second) along with response time. Not to mention block, file, object or blob as well as table.

However, are those million IOP’s applicable to your environment or needs?

Likewise, what do those million or more IOPS represent about type of work being done? For example, are they small 64 byte or large 64 Kbyte sized, random or sequential, cached reads or lazy writes (deferred or buffered) on a SSD or HDD?

How about the response time or latency for achieving them IOPS?

In other words, what is the context of those metrics and why do they matter?

storage i/o iops
Click on image to view more metrics that matter including IOP’s for HDD and SSD’s

Metrics that matter give context for example IO sizes closer to what your real needs are, reads and writes, mixed workloads, random or sequential, sustained or bursty, in other words, real world reflective.

As with any benchmark take them with a grain (or more) of salt, they key is use them as an indicator then align to your needs. The tool or technology should work for you, not the other way around.

Here are some examples of context that can be added to help make IOP’s and other metrics matter:

  • What is the IOP size, are they 512 byte (or smaller) vs. 4K bytes (or larger)?
  • Are they reads, writes, random, sequential or mixed and what percentage?
  • How was the storage configured including RAID, replication, erasure or dispersal codes?
  • Then there is the latency or response time and IO queue depths for the given number of IOPS.
  • Let us not forget if the storage systems (and servers) were busy with other work or not.
  • If there is a cost per IOP, is that list price or discount (hint, if discount start negotiations from there)
  • What was the number of threads or workers, along with how many servers?
  • What tool was used, its configuration, as well as raw or cooked (aka file system) IO?
  • Was the IOP’s number with one worker or multiple workers on a single or multiple servers?
  • Did the IOP’s number come from a single storage system or total of multiple systems?
  • Fast storage needs fast serves and networks, what was their configuration?
  • Was the performance a short burst, or long sustained period?
  • What was the size of the test data used; did it all fit into cache?
  • Were short stroking for IOPS or long stroking for bandwidth techniques used?
  • Data footprint reduction (DFR) techniques (thin provisioned, compression or dedupe) used?
  • Were write data committed synchronously to storage, or deferred (aka lazy writes used)?

The above are just a sampling and not all may be relevant to your particular needs, however they help to put IOP’s into more contexts. Another consideration around IOPS are the configuration of the environment, from an actual running application using some measurement tool, or are they generated from a workload tool such as IOmeter, IOrate, VDbench among others.

Sure, there are more contexts and information that would be interesting as well, however learning to walk before running will help prevent falling down.

Storage I/O trends

Does size or age of vendors make a difference when it comes to context?

Some vendors are doing a good job of going for out of this world record-setting marketing hero numbers.

Meanwhile other vendors are doing a good job of adding context to their IOP or response time or bandwidth among other metrics that matter. There is a mix of startup and established that give context with their IOP’s or other metrics, likewise size or age does not seem to matter for those who lack context.

Some vendors may not offer metrics or information publicly, so fine, go under NDA to learn more and see if the results are applicable to your environments.

Likewise, if they do not want to provide the context, then ask some tough yet fair questions to decide if their solution is applicable for your needs.

Storage I/O trends

Where To Learn More

View additional NAS, NVMe, SSD, NVM, SCM, Data Infrastructure and HDD related topics via the following links.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

What this means is let us start putting and asking for metrics that matter such as IOP’s with context.

If you have a great IOP metric, if you want it to matter than include some context such as what size (e.g. 4K, 8K, 16K, 32K, etc.), percentage of reads vs. writes, latency or response time, random or sequential.

IMHO the most interesting or applicable metrics that matter are those relevant to your environment and application. For example if your main application that needs SSD does about 75% reads (random) and 25% writes (sequential) with an average size of 32K, while fun to hear about, how relevant is a million 64 byte read IOPS? Likewise when looking at IOPS, pay attention to the latency, particular if SSD or performance is your main concern.

Get in the habit of asking or telling vendors or their surrogates to provide some context with them metrics if you want them to matter.

So how about some context around them IOP’s (or latency and bandwidth or availability for that matter)?

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

Part II: How many IOPS can a HDD HHDD SSD do with VMware?

How many IOPS can a HDD HHDD SSD do with VMware?

server storage data infrastructure i/o iop hdd ssd trends

Updated 2/10/2018

This is the second post of a two-part series looking at storage performance, specifically in the context of drive or device (e.g. mediums) characteristics of How many IOPS can a HDD HHDD SSD do with VMware. In the first post the focus was around putting some context around drive or device performance with the second part looking at some workload characteristics (e.g. benchmarks).

A common question is how many IOPS (IO Operations Per Second) can a storage device or system do?

The answer is or should be it depends.

Here are some examples to give you some more insight.

For example, the following shows how IOPS vary by changing the percent of reads, writes, random and sequential for a 4K (4,096 bytes or 4 KBytes) IO size with each test step (4 minutes each).

IO Size for test
Workload Pattern of test
Avg. Resp (R+W) ms
Avg. IOP Sec (R+W)
Bandwidth KB Sec (R+W)
4KB
100% Seq 100% Read
0.0
29,736
118,944
4KB
60% Seq 100% Read
4.2
236
947
4KB
30% Seq 100% Read
7.1
140
563
4KB
0% Seq 100% Read
10.0
100
400
4KB
100% Seq 60% Read
3.4
293
1,174
4KB
60% Seq 60% Read
7.2
138
554
4KB
30% Seq 60% Read
9.1
109
439
4KB
0% Seq 60% Read
10.9
91
366
4KB
100% Seq 30% Read
5.9
168
675
4KB
60% Seq 30% Read
9.1
109
439
4KB
30% Seq 30% Read
10.7
93
373
4KB
0% Seq 30% Read
11.5
86
346
4KB
100% Seq 0% Read
8.4
118
474
4KB
60% Seq 0% Read
13.0
76
307
4KB
30% Seq 0% Read
11.6
86
344
4KB
0% Seq 0% Read
12.1
82
330

Dell/Western Digital (WD) 1TB 7200 RPM SATA HDD (Raw IO) thread count 1 4K IO size

In the above example the drive is a 1TB 7200 RPM 3.5 inch Dell (Western Digital) 3Gb SATA device doing raw (non file system) IO. Note the high IOP rate with 100 percent sequential reads and a small IO size which might be a result of locality of reference due to drive level cache or buffering.

Some drives have larger buffers than others from a couple to 16MB (or more) of DRAM that can be used for read ahead caching. Note that this level of cache is independent of a storage system, RAID adapter or controller or other forms and levels of buffering.

Does this mean you can expect or plan on getting those levels of performance?

I would not make that assumption, and thus this serves as an example of using metrics like these in the proper context.

Building off of the previous example, the following is using the same drive however with a 16K IO size.

IO Size for test
Workload Pattern of test
Avg. Resp (R+W) ms
Avg. IOP Sec (R+W)
Bandwidth KB Sec (R+W)
16KB
100% Seq 100% Read
0.1
7,658
122,537
16KB
60% Seq 100% Read
4.7
210
3,370
16KB
30% Seq 100% Read
7.7
130
2,080
16KB
0% Seq 100% Read
10.1
98
1,580
16KB
100% Seq 60% Read
3.5
282
4,522
16KB
60% Seq 60% Read
7.7
130
2,090
16KB
30% Seq 60% Read
9.3
107
1,715
16KB
0% Seq 60% Read
11.1
90
1,443
16KB
100% Seq 30% Read
6.0
165
2,644
16KB
60% Seq 30% Read
9.2
109
1,745
16KB
30% Seq 30% Read
11.0
90
1,450
16KB
0% Seq 30% Read
11.7
85
1,364
16KB
100% Seq 0% Read
8.5
117
1,874
16KB
60% Seq 0% Read
10.9
92
1,472
16KB
30% Seq 0% Read
11.8
84
1,353
16KB
0% Seq 0% Read
12.2
81
1,310

Dell/Western Digital (WD) 1TB 7200 RPM SATA HDD (Raw IO) thread count 1 16K IO size

The previous two examples are excerpts of a series of workload simulation tests (ok, you can call them benchmarks) that I have done to collect information, as well as try some different things out.

The following is an example of the summary for each test output that includes the IO size, workload pattern (reads, writes, random, sequential), duration for each workload step, totals for reads and writes, along with averages including IOP’s, bandwidth and latency or response time.

disk iops

Want to see more numbers, speeds and feeds, check out the following table which will be updated with extra results as they become available.

Device
Vendor
Make

Model

Form Factor
Capacity
Interface
RPM Speed
Raw
Test Result
HDD
HGST
Desktop
HK250-160
2.5
160GB
SATA
5.4K
HDD
Seagate
Mobile
ST2000LM003
2.5
2TB
SATA
5.4K
HDD
Fujitsu
Desktop
MHWZ160BH
2.5
160GB
SATA
7.2K
HDD
Seagate
Momentus
ST9160823AS
2.5
160GB
SATA
7.2K
HDD
Seagate
MomentusXT
ST95005620AS
2.5
500GB
SATA
7.2K(1)
HDD
Seagate
Barracuda
ST3500320AS
3.5
500GB
SATA
7.2K
HDD
WD/Dell
Enterprise
WD1003FBYX
3.5
1TB
SATA
7.2K
HDD
Seagate
Barracuda
ST3000DM01
3.5
3TB
SATA
7.2K
HDD
Seagate
Desktop
ST4000DM000
3.5
4TB
SATA
HDD
HDD
Seagate
Capacity
ST6000NM00
3.5
6TB
SATA
HDD
HDD
Seagate
Capacity
ST6000NM00
3.5
6TB
12GSAS
HDD
HDD
Seagate
Savio 10K.3
ST9300603SS
2.5
300GB
SAS
10K
HDD
Seagate
Cheetah
ST3146855SS
3.5
146GB
SAS
15K
HDD
Seagate
Savio 15K.2
ST9146852SS
2.5
146GB
SAS
15K
HDD
Seagate
Ent. 15K
ST600MP0003
2.5
600GB
SAS
15K
SSHD
Seagate
Ent. Turbo
ST600MX0004
2.5
600GB
SAS
SSHD
SSD
Samsung
840 PRo
MZ-7PD256
2.5
256GB
SATA
SSD
HDD
Seagate
600 SSD
ST480HM000
2.5
480GB
SATA
SSD
SSD
Seagate
1200 SSD
ST400FM0073
2.5
400GB
12GSAS
SSD

Performance characteristics 1 worker (thread count) for RAW IO (non-file system)

Note: (1) Seagate Momentus XT is a Hybrid Hard Disk Drive (HHDD) based on a 7.2K 2.5 HDD with SLC nand flash integrated for read buffer in addition to normal DRAM buffer. This model is a XT I (4GB SLC nand flash), may add an XT II (8GB SLC nand flash) at some future time.

As a starting point, these results are raw IO with file system based information to be added soon along with more devices. These results are for tests with one worker or thread count, other results will be added with such as 16 workers or thread counts to show how those differ.

The above results include all reads, all writes, mix of reads and writes, along with all random, sequential and mixed for each IO size. IO sizes include 4K, 8K, 16K, 32K, 64K, 128K, 256K, 512K, 1024K and 2048K. As with any workload simulation, benchmark or comparison test, take these results with a grain of salt as your mileage can and will vary. For example you will see some what I consider very high IO rates with sequential reads even without file system buffering. These results might be due to locality of reference of IO’s being resolved out of the drives DRAM cache (read ahead) which vary in size for different devices. Use the vendor model numbers in the table above to check the manufactures specs on drive DRAM and other attributes.

If you are used to seeing 4K or 8K and wonder why anybody would be interested in some of the larger sizes take a look at big fast data or cloud and object storage. For some of those applications 2048K may not seem all that big. Likewise if you are used to the larger sizes, there are still applications doing smaller sizes. Sorry for those who like 512 byte or smaller IO’s as they are not included. Note that for all of these unless indicated a 512 byte standard sector or drive format is used as opposed to emerging Advanced Format (AF) 4KB sector or block size. Watch for some more drive and device types to be added to the above, along with results for more workers or thread counts, along with file system and other scenarios.

Using VMware as part of a Server, Storage and IO (aka StorageIO) test platform

vmware vexpert

The above performance results were generated on Ubuntu 12.04 (since upgraded to 14.04 which was hosted on a VMware vSphere 5.1 (upgraded to 5.5U2) purchased version (you can get the ESXi free version here) with vCenter enabled system. I also have VMware workstation installed on some of my Windows-based laptops for doing preliminary testing of scripts and other activity prior to running them on the larger server-based VMware environment. Other VMware tools include vCenter Converter, vSphere Client and CLI. Note that other guest virtual machines (VMs) were idle during the tests (e.g. other guest VMs were quiet). You may experience different results if you ran Ubuntu native on a physical machine or with different adapters, processors and device configurations among many other variables (that was a disclaimer btw ;) ).

Storage I/O trends

All of the devices (HDD, HHDD, SSD’s including those not shown or published yet) were Raw Device Mapped (RDM) to the Ubuntu VM bypassing VMware file system.

Example of creating an RDM for local SAS or SATA direct attached device.

vmkfstools -z /vmfs/devices/disks/naa.600605b0005f125018e923064cc17e7c /vmfs/volumes/dat1/RDM_ST1500Z110S6M5.vmdk

The above uses the drives address (find by doing a ls -l /dev/disks via VMware shell command line) to then create a vmdk container stored in a dat. Note that the RDM being created does not actually store data in the .vmdk, it’s there for VMware management operations.

If you are not familiar with how to create a RDM of a local SAS or SATA device, check out this post to learn how.This is important to note in that while VMware was used as a platform to support the guest operating systems (e.g. Ubuntu or Windows), the real devices are not being mapped through or via VMware virtual drives.

vmware iops

The above shows examples of RDM SAS and SATA devices along with other VMware devices and dats. In the next figure is an example of a workload being run in the test environment.

vmware iops

One of the advantages of using VMware (or other hypervisor) with RDM’s is that I can quickly define via software commands where a device gets attached to different operating systems (e.g. the other aspect of software defined storage). This means that after a test run, I can quickly simply shutdown Ubuntu, remove the RDM device from that guests settings, move the device just tested to a Windows guest if needed and restart those VMs. All of that from where ever I happen to be working from without physically changing things or dealing with multi-boot or cabling issues.

Where To Learn More

View additional NAS, NVMe, SSD, NVM, SCM, Data Infrastructure and HDD related topics via the following links.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

So how many IOPs can a device do?

That depends, however have a look at the above information and results.

Check back from time to time here to see what is new or has been added including more drives, devices and other related themes.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

How many I/O iops can flash SSD or HDD do?

How many i/o iops can flash ssd or hdd do with vmware?

sddc data infrastructure Storage I/O ssd trends

Updated 2/10/2018

A common question I run across is how many I/O iopsS can flash SSD or HDD storage device or system do or give.

The answer is or should be it depends.

This is the first of a two-part series looking at storage performance, and in context specifically around drive or device (e.g. mediums) characteristics across HDD, HHDD and SSD that can be found in cloud, virtual, and legacy environments. In this first part the focus is around putting some context around drive or device performance with the second part looking at some workload characteristics (e.g. benchmarks).

What about cloud, tape summit resources, storage systems or appliance?

Lets leave those for a different discussion at another time.

Getting started

Part of my interest in tools, metrics that matter, measurements, analyst, forecasting ties back to having been a server, storage and IO performance and capacity planning analyst when I worked in IT. Another aspect ties back to also having been a sys admin as well as business applications developer when on the IT customer side of things. This was followed by switching over to the vendor world involved with among other things competitive positioning, customer design configuration, validation, simulation and benchmarking HDD and SSD based solutions (e.g. life before becoming an analyst and advisory consultant).

Btw, if you happen to be interested in learn more about server, storage and IO performance and capacity planning, check out my first book Resilient Storage Networks (Elsevier) that has a bit of information on it. There is also coverage of metrics and planning in my two other books The Green and Virtual Data Center (CRC Press) and Cloud and Virtual Data Storage Networking (CRC Press). I have some copies of Resilient Storage Networks available at a special reader or viewer rate (essentially shipping and handling). If interested drop me a note and can fill you in on the details.

There are many rules of thumb (RUT) when it comes to metrics that matter such as IOPS, some that are older while others may be guess or measured in different ways. However the answer is that it depends on many things ranging from if a standalone hard disk drive (HDD), Hybrid HDD (HHDD), Solid State Device (SSD) or if attached to a storage system, appliance, or RAID adapter card among others.

Taking a step back, the big picture

hdd image
Various HDD, HHDD and SSD’s

Server, storage and I/O performance and benchmark fundamentals

Even if just looking at a HDD, there are many variables ranging from the rotational speed or Revolutions Per Minute (RPM), interface including 1.5Gb, 3.0Gb, 6Gb or 12Gb SAS or SATA or 4Gb Fibre Channel. If simply using a RUT or number based on RPM can cause issues particular with 2.5 vs. 3.5 or enterprise and desktop. For example, some current generation 10K 2.5 HDD can deliver the same or better performance than an older generation 3.5 15K. Other drive factors (see this link for HDD fundamentals) including physical size such as 3.5 inch or 2.5 inch small form factor (SFF), enterprise or desktop or consumer, amount of drive level cache (DRAM). Space capacity of a drive can also have an impact such as if all or just a portion of a large or small capacity devices is used. Not to mention what the drive is attached to ranging from in internal SAS or SATA drive bay, USB port, or a HBA or RAID adapter card or in a storage system.

disk iops
HDD fundamentals

How about benchmark and performance for marketing or comparison tricks including delayed, deferred or asynchronous writes vs. synchronous or actually committed data to devices? Lets not forget about short stroking (only using a portion of a drive for better IOP’s) or even long stroking (to get better bandwidth leveraging spiral transfers) among others.

Almost forgot, there are also thick, standard, thin and ultra thin drives in 2.5 and 3.5 inch form factors. What’s the difference? The number of platters and read write heads. Look at the following image showing various thickness 2.5 inch drives that have various numbers of platters to increase space capacity in a given density. Want to take a wild guess as to which one has the most space capacity in a given footprint? Also want to guess which type I use for removable disk based archives along with for onsite disk based backup targets (compliments my offsite cloud backups)?

types of disks
Thick, thin and ultra thin devices

Beyond physical and configuration items, then there are logical configuration including the type of workload, large or small IOPS, random, sequential, reads, writes or mixed (various random, sequential, read, write, large and small IO). Other considerations include file system or raw device, number of workers or concurrent IO threads, size of the target storage space area to decide impact of any locality of reference or buffering. Some other items include how long the test or workload simulation ran for, was the device new or worn in before use among other items.

Tools and the performance toolbox

Then there are the various tools for generating IO’s or workloads along with recording metrics such as reads, writes, response time and other information. Some examples (mix of free or for fee) include Bonnie, Iometer, Iorate, IOzone, Vdbench, TPC, SPC, Microsoft ESRP, SPEC and netmist, Swifttest, Vmark, DVDstore and PCmark 7 among many others. Some are focused just on the storage system and IO path while others are application specific thus exercising servers, storage and IO paths.

performance tools
Server, storage and IO performance toolbox

Having used Iometer since the late 90s, it has its place and is popular given its ease of use. Iometer is also long in the tooth and has its limits including not much if any new development, never the less, I have it in the toolbox. I also have Futremark PCmark 7 (full version) which turns out has some interesting abilities to do more than exercise an entire Windows PC. For example PCmark can use a secondary drive for doing IO to.

PCmark can be handy for spinning up with VMware (or other tools) lots of virtual Windows systems pointing to a NAS or other shared storage device doing real world type activity. Something that could be handy for testing or stressing virtual desktop infrastructures (VDI) along with other storage systems, servers and solutions. I also have Vdbench among others tools in the toolbox including Iorate which was used to drive the workloads shown below.

What I look for in a tool are how extensible are the scripting capabilities to define various workloads along with capabilities of the test engine. A nice GUI is handy which makes Iometer popular and yes there are script capabilities with Iometer. That is also where Iometer is long in the tooth compared to some of the newer generation of tools that have more emphasis on extensibility vs. ease of use interfaces. This also assumes knowing what workloads to generate vs. simply kicking off some IOPs using default settings to see what happens.

Another handy tool is for recording what’s going on with a running system including IO’s, reads, writes, bandwidth or transfers, random and sequential among other things. This is where when needed I turn to something like HiMon from HyperIO, if you have not tried it, get in touch with Tom West over at HyperIO and tell him StorageIO sent you to get a demo or trial. HiMon is what I used for doing start, stop and boot among other testing being able to see IO’s at the Windows file system level (or below) including very early in the boot or shutdown phase.

Here is a link to some other things I did awhile back with HiMon to profile some Windows and VDI activity test profiling.

What’s the best tool or benchmark or workload generator?

The one that meets your needs, usually your applications or something as close as possible to it.

disk iops
Various 2.5 and 3.5 inch HDD, HHDD, SSD with different performance

Where To Learn More

View additional NAS, NVMe, SSD, NVM, SCM, Data Infrastructure and HDD related topics via the following links.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

That depends, however continue reading part II of this series to see some results for various types of drives and workloads.

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

Trick or treat and vendor fun games

In the spirit of Halloween and zombies season, a couple of thoughts come to mind about vendor tricks and treats. This is an industry trends and perspectives post, part of an ongoing series looking at various technology and fun topics.

The first trick or treat game pertains to the blame game; you know either when something breaks, or at the other extreme, before you have even made a decision to buy something. The trick or treat game for decision-making goes something like this.

StorageIO industry trends cloud, virtualization and big data

Vendor “A” says products succeed with their solution while failure results with a solution from “B” when doing “X”. Otoh, vendor “B” claims that “X” will fail when using a solution from vendor “A”. In fact, you can pick what you want to substitute for “X”, perhaps VDI, PCIe, Big Data, Little Data, Backup, Archive, Analytics, Private Cloud, Public Cloud, Hybrid Cloud, eDiscovery you name it.

This is not complicated math or big data problem requiring a high-performance computing (HPC) platform. A HPC Zetta-Flop processing ability using 512 bit addressing of 9.9 (e.g. 1 nine) PettaBytes of battery-backed DRAM and an IO capability of 9.99999 (e.g. 5 9’s) trillion 8 bit IOPS to do table pivots or runge kutta numerical analysis, map reduce, SAS or another modeling with optional iProduct or Android interface are not needed.

image of StorageIO big data HPC cloud storageimage of StorageIO big data HPC cloud storage
StorageIO images of touring Texas Advanced Computing (e.g. HPC) Center

Can you solve this equation? Hint it does not need a PhD or any other advanced degree. Another hint, if you have ever been at any side of the technology product and services decision-making table, regardless of the costume you wore, you should know the answer.

Of course the question of would “X” fail regardless of who or what “A” or “B” let alone a “C”, “D” or “F”? In other words, it is not the solution, technology, vendor or provider, rather the problem or perhaps even lack thereof that is the issue. Or is it a case where there is a solution from “A”, “B” or any others that is looking for a problem, and if it is the wrong problem, there can be a wrong solution thus failure?

StorageIO industry trends cloud, virtualization and big data

Another trick or treat game is vendors public relations (PR) or analyst relations (AR) people to ask for one thing and delivery or ask another. For example, some vendor, service provider, their marketing AR and PR people or surrogates make contact wanting to tell of various success and failure story. Of course, this is usually their success and somebody else’s failure, or their victory over something or someone who sometimes can be interesting. Of course, there are also the treats to get you to listen to the above, such as tempt you with a project if you meet with their subject, which may be a trick of a disappearing treat (e.g. magic, poof it is gone after the discussion).

There are another AR and PR trick and treat where they offer on behalf of their representative organization or client to a perspective or exclusive insight on their competitor. Of course, the treat from their perspective is that they will generously expose all that is wrong with what a competitor is saying about their own (e.g. the competitors) product.

StorageIO industry trends cloud, virtualization and big data

Let me get this straight, I am not supposed to believe what somebody says about his or her own product, however, supposed to believe what a competitor says is wrong with the competition’s product, and what is right with his or her own product.

Hmm, ok, so let me get this straight, a competitor say “A” wants to tell me what somebody say from “B” has told me is wrong and I should schedule a visit with a truth squad member from “A” to get the record set straight about “B”?

Does that mean then that I go to “B” for a rebuttal, as well as an update about “A” from “B”, assuming that what “A” has told me is also false about themselves, and perhaps about “B” or any other?

Too be fair, depending on your level of trust and confidence in either a vendor, their personal or surrogates, you might tend to believe more from them vs. others, or at least until you been tricked after given treats. There may be some that have been tricked, or they tried applying to many treats to present a story that behind the costume might be a bit scary.

StorageIO industry trends cloud, virtualization and big data

Having been through enough of these, and I candidly believe that sometimes “A” or “B” or any other party actually do believe that they have more or better info about their competitor and that they can convince somebody about what their competitor is doing better than the competitor can. I also believe that there are people out there who will go to “A” or “B” and believe what they are told by based on their preference, bias or interests.

When I hear from vendors, VARs, solution or service providers and others, it’s interesting hearing point, counterpoint and so forth, however if time is limited, I’am more interested in hearing from such as “A” about them, what they are doing, where success, where challenges, where going and if applicable, under NDA go into more detail.

StorageIO industry trends cloud, virtualization and big data

Customer success stories are good, however again, if interested in what works, what kind of works, or what does not work, chances are when looking for G2 vs. GQ, a non-scripted customer conversation or perspective of the good, the bad and the ugly is preferred, even if under NDA. Again, if time is limited which it usually is, focus on what is being done with your solution, where it is going and if compelled send follow-up material that can of course include MUD and FUD about others if that is your preference.

Then there is when during a 30 minute briefing, the vendor or solution provider is still talking about trends, customer pain points, what competitors are doing at 21 minutes into the call with no sign of an announcement, update or news in site

Lets not forget about the trick where the vendor marketing or PR person reaches out and says that the CEO, CMO, CTO or some other CxO or Chief Jailable Officer (CJO) wants to talk with you. Part of the trick is when the CxO actually makes it to the briefing and is not ready, does not know why the call is occurring, or, thinks that a request for an audience has been made with them for an interview or something else.

StorageIO industry trends cloud, virtualization and big data

A treat is when 3 to 4 minutes into a briefing, the vendor or solution provider has already framed up what and why they are doing something. This means getting to what they are announcing or planning on doing and getting into a conversation to discuss what they are doing and making good follow-up content and resources available.

StorageIO industry trends cloud, virtualization and big data

Sometimes a treat is when a briefer goes on autopilot nailing their script for 29 of a 30 minute session then use the last-minute to ask if there are any questions. The reason autopilot briefings can be a treat is when they are going over what is in the slide deck, webex, or press release thus affording an opportunity to get caught up on other things while talk at you. Hmm, perhaps need to consider playing some tricks in reward for those kind of treats? ;)

StorageIO industry trends cloud, virtualization and big data

Do not be scared, not everybody is out to trick you with treats, and not all treats have tricks attached to them. Be prepared, figure out who is playing tricks with treats, and who has treats without tricks.

Oh, and as a former IT customer, vendor and analyst, one of my favorites is contact information of my dogs to vendors who require registration on their websites for basic things such as data sheets. Another is supplying contact information of competing vendors sales reps to vendors who also require registration for basic data sheets or what should otherwise be generally available information as opposed to more premium treats. Of course there are many more fun tricks, however lets leave those alone for now.

Note: Zombie voting rules apply which means vote early, vote often, and of course vote for those who cannot include those that are dead (real or virtual).

Where To Learn More

View additiona related material via the following links.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

Watch out for tricks and treats, have a safe and fun Zombie (aka Halloween) season. See you while out and about this fall and don’t forget to take part in the ongoing zombie technology poll. Oh, and be safe with trick or treat and vendor fun games

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2018. Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

What is the best kind of IO? The one you do not have to do

What is the best kind of IO? The one you do not have to do

data infrastructure server storage I/O trends

Updated 2/10/2018

What is the best kind of IO? If no IO (input/output) operation is the best IO, than the second best IO is the one that can be done as close to the application and processor with best locality of reference. Then the third best IO is the one that can be done in less time, or at least cost or impact to the requesting application which means moving further down the memory and storage stack (figure 1).

Storage and IO or I/O locality of reference and storage hirearchy
Figure 1 memory and storage hierarchy

The problem with IO is that they are basic operation to get data into and out of a computer or processor so they are required; however, they also have an impact on performance, response or wait time (latency). IO require CPU or processor time and memory to set up and then process the results as well as IO and networking resources to move data to their destination or retrieve from where stored. While IOs cannot be eliminated, their impact can be greatly improved or optimized by doing fewer of them via caching, grouped reads or writes (pre-fetch, write behind) among other techniques and technologies.

Think of it this way, instead of going on multiple errands, sometimes you can group multiple destinations together making for a shorter, more efficient trip; however, that optimization may also take longer. Hence sometimes it makes sense to go on a couple of quick, short low latency trips vs. one single larger one that takes half a day however accomplishes many things. Of course, how far you have to go on those trips (e.g. locality) makes a difference of how many you can do in a given amount of time.

What is locality of reference?

Locality of reference refers to how close (e.g location) data exists for where it is needed (being referenced) for use. For example, the best locality of reference in a computer would be registers in the processor core, then level 1 (L1), level 2 (L2) or level 3 (L3) onboard cache, followed by dynamic random access memory (DRAM). Then would come memory also known as storage on PCIe cards such as nand flash solid state device (SSD) or accessible via an adapter on a direct attached storage (DAS), SAN or NAS device. In the case of a PCIe nand flash SSD card, even though physically the nand flash SSD is closer to the processor, there is still the overhead of traversing the PCIe bus and associated drivers. To help offset that impact, PCIe cards use DRAM as cache or buffers for data along with Meta or control information to further optimize and improve locality of reference. In other words, help with cache hits, cache use and cache effectiveness vs. simply boosting cache utilization.

Where To Learn More

View additional NAS, NVMe, SSD, NVM, SCM, Data Infrastructure and HDD related topics via the following links.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

What can you do the cut the impact of IO

  • Establish baseline performance and availability metrics for comparison
  • Realize that IOs are a fact of IT virtual, physical and cloud life
  • Understand what is a bad IO along with its impact
  • Identify why an IO is bad, expensive or causing an impact
  • Find and fix the problem, either with software, application or database changes
  • Throw more software caching tools, hyper visors or hardware at the problem
  • Hardware includes faster processors with more DRAM and fast internal busses
  • Leveraging local PCIe flash SSD cards for caching or as targets
  • Utilize storage systems or appliances that have intelligent caching and storage optimization capabilities (performance, availability, capacity).
  • Compare changes and improvements to baseline, quantify improvement

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

As the Hard Disk Drive HDD continues to spin

As the Hard Disk Drive HDD continues to spin

server storage data infrastructure i/o iop hdd ssd trends

Updated 2/10/2018

Despite having been repeatedly declared dead at the hands of some new emerging technology over the past several decades, the Hard Disk Drive (HDD) continues to spin and evolve as it moves towards its 60th birthday.

More recently HDDs have been declared dead due to flash SSD that according to some predictions, should have caused the HDD to be extinct by now.

Meanwhile, having not yet died in addition to having qualified for its AARP membership a few years ago, the HDD continues to evolve in capacity, smaller form factor, performance, reliability, density along with cost improvements.

Back in 2006 I did an article titled Happy 50th, hard drive, but will you make it to 60?

IMHO it is safe to say that the HDD will be around for at least a few more years if not another decade (or more).

This is not to say that the HDD has outlived its usefulness or that there are not other tiered storage mediums to do specific jobs or tasks better (there are).

Instead, the HDD continues to evolve and is complimented by flash SSD in a way that HDDs are complimenting magnetic tape (another declared dead technology) each finding new roles to support more data being stored for longer periods of time.

After all, there is no such thing as a data or information recession!

What the importance of this is about technology tiering and resource alignment, matching the applicable technology to the task at hand.

Technology tiering (Servers, storage, networking, snow removal) is about aligning the applicable resource that is best suited to a particular need in a cost as well as productive manner. The HDD remains a viable tiered storage medium that continues to evolve while taking on new roles coexisting with SSD and tape along with cloud resources. These and other technologies have their place which ideally is finding or expanding into new markets instead of simply trying to cannibalize each other for market share.

Here is a link to a good story by Lucas Mearian on the history or evolution of the hard disk drive (HDD) including how a 1TB device that costs about $60 today would have cost about a trillion dollars back in the 1950s. FWIW, IMHO the 1 trillion dollars is low and should be more around 2 to 5 trillion for the one TByte if you apply common costs for management, people, care and feeding, power, cooling, backup, BC, DR and other functions.

Where To Learn More

View additional NAS, NVMe, SSD, NVM, SCM, Data Infrastructure and HDD related topics via the following links.

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What This All Means

IMHO, it is safe to say that the HDD is here to stay for at least a few more years (if not decades) or at least until someone decides to try a new creative marketing approach by declaring it dead (again).

Ok, nuff said, for now.

Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2017 (vSAN and vCloud). Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.

Posted on

What is DFR or Data Footprint Reduction?

What is DFR or Data Footprint Reduction?

What is DFR or Data Footprint Reduction?

Updated 10/9/2018

What is DFR or Data Footprint Reduction?

Data Footprint Reduction (DFR) is a collection of techniques, technologies, tools and best practices that are used to address data growth management challenges. Dedupe is currently the industry darling for DFR particularly in the scope or context of backup or other repetitive data.

However DFR expands the scope of expanding data footprints and their impact to cover primary, secondary along with offline data that ranges from high performance to inactive high capacity.

Consequently the focus of DFR is not just on reduction ratios, its also about meeting time or performance rates and data protection windows.

This means DFR is about using the right tool for the task at hand to effectively meet business needs, and cost objectives while meeting service requirements across all applications.

Examples of DFR technologies include Archiving, Compression, Dedupe, Data Management and Thin Provisioning among others.

Read more about DFR in Part I and Part II of a two part series found here and here.

Where to learn more

Learn more about data footprint reducton (DFR), data footprint overhead and related topics via the following links:

Additional learning experiences along with common questions (and answers), as well as tips can be found in Software Defined Data Infrastructure Essentials book.

Software Defined Data Infrastructure Essentials Book SDDC

What this all means

That is all for now, hope you find these ongoing series of current or emerging Industry Trends and Perspectives posts of interest.

Ok, nuff said, for now.

Cheers Gs

Greg Schulz – Microsoft MVP Cloud and Data Center Management, VMware vExpert 2010-2018. Author of Software Defined Data Infrastructure Essentials (CRC Press), as well as Cloud and Virtual Data Storage Networking (CRC Press), The Green and Virtual Data Center (CRC Press), Resilient Storage Networks (Elsevier) and twitter @storageio. Courteous comments are welcome for consideration. First published on https://storageioblog.com any reproduction in whole, in part, with changes to content, without source attribution under title or without permission is forbidden.

All Comments, (C) and (TM) belong to their owners/posters, Other content (C) Copyright 2006-2024 Server StorageIO and UnlimitedIO. All Rights Reserved. StorageIO is a registered Trade Mark (TM) of Server StorageIO.